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Knowledge and Digitalisation Against Corruption and Fraud

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Abstract

It is with great pleasure that we present the first of three monographs describing the research results on combating corruption and fraud. Combating corruption begins with awareness of the problem. Sharing the knowledge of the Visegrad Group countries and Ukraine in counteracting corrupt behaviour has a significant cognitive and educational aspect. Additionally, the inclusion of technological tools allows for reducing the negative consequences of such behaviour.
edited by
Piotr Luty, Nataliia Versal, Pavel Semerád
Publishing House of Wroclaw University of Economics and Business
Knowledge
and Digitalisation
Against Corruption and Fraud
The project is co-financed by the Governments of Czechia, Hungary, Poland and Slovakia through
Visegrad Grants from Interna�onal Visegrad Fund. The mission of the fund is to advance ideas for
sustainable regional coopera�on in Central Europe
edited by
Piotr Luty, Nataliia Versal, Pavel Semerád
Knowledge
and Digitalisation
Against Corruption and Fraud
The project is co-financed by the Governments of Czechia, Hungary, Poland and Slovakia through
Visegrad Grants from Interna�onal Visegrad Fund. The mission of the fund is to advance ideas for
sustainable regional coopera�on in Central Europe
Publishing House of Wroclaw University of Economics and Business
Wroclaw 2024
Reviewer
Marek Masztalerz
Copyeding
Elżbieta Macauley, Tim Macauley, Agnieszka Flasińska
Proofreading
Marcin Orszulak
Typeseng
Małgorzata Myszkowska
Cover design
Beata Dębska
The publicaon is available under Creave Commons Aribuon-ShareAlike 4.0
Internaonal License (CC BY-SA 4.0). To view a copy of this license, visit,
hps://creavecommons.org/licenses/by-sa/4.0/deed.pl
ISBN 978-83-67899-96-3
DOI: 10.15611/2024.96.3
Quote as: Luty, P., Versal, N., & Semerád, P. (Eds.). (2024). Knowledge and Digitalisaon Against Cor-
rupon and Fraud. Publishing House of Wroclaw University of Economics and Business.
Contents
Foreword ............................................................................................................................ 5
1. Fight Against Corruption in the Czech Republic and Ukraine (Veronika
Solilova, Nataliia Versal) .................................................................................... 7
1.1. Introducon ............................................................................................................ 7
1.2. Corrupon: Meaning, Types, Measures .................................................................. 8
1.3. Policy Response ....................................................................................................... 13
1.3.1. Ukraine .................................................................................................................... 13
1.3.2. The Czech Republic ................................................................................................. 15
1.4. Conclusions ............................................................................................................. 20
2. The Use of Digital Technology in the Fight Against Welfare Fraud:
Comparative Analysis of Selected National Experiences (Łukasz Jurek) 23
2.1. Introducon ............................................................................................................ 23
2.2. Digital Welfare State: Theorecal Approach ........................................................... 24
2.3. Welfare Fraud and Welfare Surveillance ................................................................. 26
2.4. Digital Welfare Surveillance in Selected Countries.................................................. 29
2.5. Conclusions ............................................................................................................. 31
3. Exchange of Experience in the Use of Digital Procurement Tools to Prevent
Corruption in the Public and Business Sectors in Ukraine and V4 (Oleksiy
Poburko, Nataliya Synyutka, Pavlo Horyslavets, Andriana Mazur, Oksana
Kurylo) ................................................................................................................... 36
3.1. Introducon ............................................................................................................ 36
3.2. Exchange of Experience in the Use of Digital Procurement Tools ........................... 38
3.3. Conclusions ............................................................................................................. 43
4. New Forms of Non-Standard Employment and Fighting Shadow
Economy (Antonina Sholoiko, Vasyl Erastov) ................................................ 45
4.1. Introducon ............................................................................................................ 45
4.2. Forms of Non-Standard Employment...................................................................... 46
4.3. Conclusions ............................................................................................................. 55
5. The Transformation of Payment Systems in Eastern Europe: Past Trends
and Future Innovation (Bogdan Adamyk, Anetta Zielińska, Oksana
Adamyk) ................................................................................................................ 57
5.1. Introducon ............................................................................................................ 57
5.2. The Opportunies for and Impact of Payments Innovaons .................................. 59
5.2.1. The Drivers of Payment Innovaon ......................................................................... 60
5.2.2. The Economic Impact of Payment Innovaon ......................................................... 61
5.3. The Rise of Non-Cash Payments in Eastern Europe................................................. 63
5.3.1. Non-Cash Payments ................................................................................................ 63
Knowledge and Digitalisaon Against Corrupon and Fraud 4
5.3.2. Financial Parcipaon ............................................................................................. 68
5.3.3. E-commerce ............................................................................................................ 69
5.3.4. POS-terminals ......................................................................................................... 71
5.3.5. Shadow Economy .................................................................................................... 72
5.4. Future Prospects: Bank or Non-Bank? .................................................................... 72
5.4.1. FinTech Payment Startups ....................................................................................... 72
5.4.2. Mobile Payments .................................................................................................... 73
5.4.3. Cryptocurrencies, Blockchain and CBDC ................................................................. 73
5.5. Conclusions ............................................................................................................. 75
6. Electronic Records of Sales in the Czech Republic (Pavel Semerád,
Lucie Semerádová, Marian Dobranschi) ........................................................ 78
6.1. Introducon ............................................................................................................ 78
6.2. Electronic Records of Sales ..................................................................................... 80
6.3. Results of the Electronic Records of Sales System .................................................. 82
6.4. Consequences of the Abolion of the Electronic Records of the Sales System ...... 83
6.5. Conclusions ............................................................................................................. 85
7. Fighting the VAT Gap – The Polish Experience (Alicja Brodzka, Krzysztof
Biernacki) ............................................................................................................. 88
7.1. Introducon ............................................................................................................ 88
7.2. VAT Gap ................................................................................................................... 89
7.3. VAT Gap in Poland ................................................................................................... 90
7.4. VAT Compliance Measures Implemented in Poland ............................................... 93
7.5. Procedures of Vericaon Tax Liabilies and the VAT Gap ..................................... 95
7.6. Conclusions ............................................................................................................. 98
Aerword .......................................................................................................................... 101
List of Figures...................................................................................................................... 102
List of Tables ....................................................................................................................... 103
Foreword
It is with great pleasure that we present the rst of three monographs describing the research
results on combang corrupon and fraud. Combang corrupon begins with awareness of the
problem. Sharing the knowledge of the Visegrad Group countries and Ukraine in counteracng
corrupt behaviour has a signicant cognive and educaonal aspect. Addionally, the inclusion
of technological tools allows for reducing the negave consequences of such behaviour.
In the rst chapter, the study focuses on trends in corrupon indices in Ukraine and the Czech
Republic and assesses policy responses to corrupon. The results indicate posive trends
in both naons. Over the last decade (2012-2022), the Corrupon Percepon Index (CPI)
improved from 26 to 33 in Ukraine and 49 to 56 in the Czech Republic. However, Ukraine’s
CPI score remains considerably lower, with the gap unchanged at 23 points compared to the
Czech Republic, suggesng that the Czech Republic is generally more eecve in ghng
corrupon. Nonetheless, according to the Corrupon Forecast, Ukraine has made substanal
progress in reducing corrupon opportunies, mainly through implemenng digital plaorms
like Diia and Prozorro, which have digised a vast array of public services and enhanced budget
transparency. In conclusion, both countries demonstrate notable improvements through
instuonal and legislave changes aimed at ghtening measures against corrupon.
The chapter describes digital transformaon in combang welfare fraud, however, the
author’s experience with digital surveillance has not been so far encouraging. The most
advanced countries in this regard, the Netherlands and Austria, have suered spectacular
failures in recent years. The author presents the cases of these countries, providing the basis
for a discussion of the main problems with the use of modern technology in the ght against
irregularies.
The third chapter covers an important issue related to compliance with the principles of
transparency in the public procurement process. The authors analysed the state of legal
regulaons in European countries, emphasising recommendaons for Ukraine.
The fourth chapter deals with ghng the shadow economy by introducing new forms of
employment. Global labour market changes, globalisaon, and consequences of the pandemic
created space for the evoluon of forms of employment. New employment approaches are
becoming a widespread phenomenon. Thus, the primary purpose of this invesgaon was to
highlight the main non-standard forms of employment and to create recommendaons for
ghng the shadow economy in Ukraine, which needs to full a set of tasks. First, the pros
and cons of each non-standard employment form were generalised. Some can be considered
applicable for all forms, but some were form-specic. Next, recommendaons on how to ght
the shadow economy in Ukraine were suggested. The advantages and disadvantages can be
both general and form-specic. For Ukraine, the best soluon for now, will be smulang the
creaon of sole proprietors and, if applicable, transforming them into gig specialists (only for
the IT sphere and Diia residents).
The h chapter examines the development of payment systems in Eastern Europe over the last
decade and the opportunity for further improvement through adopng new digital payment
technologies, including potenally introducing central bank digital currency. It compares the
experience of six Eastern European countries that have joined the European Union (including
Knowledge and Digitalisaon Against Corrupon and Fraud 6
all countries of the V4 Group) with three post-soviet countries (including Ukraine) that remain
outside the European Union. It documents the development of non-cash payments, and
idenes barriers to developing non-cash payments in Eastern Europe, seeking to explain
the dierences between these countries. Finally, it assesses the inuence of ntech startups,
cryptocurrencies and blockchain technologies on the recent and future development of non-
-cash payments in Eastern Europe, where the opportunies for the development of e-money
are limited. The insignicant development of e-money and the fact that there is no growth
in the volume of payments with the help of e-money is associated with the comprehensive
development and deep penetraon of card payment systems, mobile banks, and ntech
startups based on payment cards in all areas.
The sixth chapter deals with electronic evidence of sales in the Czech Republic. Combang
tax fraud is a long-standing and essenal objecve of the nancial administraon. If this were
not the case, and the authority abandoned meeng this requirement, it could destabilise and
irreversibly damage the enre entrepreneurial environment. Furthermore, the electronic
records of the sales system could have been used to re-distribute shared taxes more fairly,
allowing residents to request a proper tax receipt, as it would automacally mean that a poron
of the entrepreneur’s nal tax would be re-distributed to their municipality as per rao. This
bonding within communies could help movate proper sales reporng. Instead, the electronic
records of the sales system became a polical issue that helped the current government win the
elecons, even though digital informaon exchange between entrepreneurs and government
is a natural part of business life in most EU countries. What the Czech government did was an
unfortunate step against this trend.
The last, seventh chapter analyses the instruments implemented in Poland to minimise the
VAT gap. The hypothesis proposed in this chapter concerns the synergy eects of acons in the
legislave issue and the actual approach of the naonal tax authories iniang tax validaon
procedures. The chapter uses materials published by the Polish Ministry of Finance, Polish
Supreme Audit Oce (NIK), Internaonal Monetary Fund and European Commission together
with CASE, as well as data obtained as a result of a request on 16 December 2023 to the
Minister of Finance under the provisions of the Access to Public Informaon Act.
Chapter 1
Fight Against Corruption in the Czech Republic
and Ukraine
Veronika Solilova
Associate Professor, Prague University of Economics and Business
ORCID: 0000-0002-9122-539X
Nataliia Versal
Associate Professor, Taras Shevchenko Naonal University of Kyiv
ORCID: 0000-0002-8801-6351
© 2024 Veronika Solilova, Nataliia Versal
This work is licensed under the Creave Commons Aribuon-ShareAlike 4.0 Internaonal License.
To view a copy of this license, visit hp://creavecommons.org/licenses/by-sa/4.0/
Quote as: Solilova, V., & Versal, N. (2024). Fight Against Corruption in the Czech Republic and
Ukraine. In P. Luty, N. Versal, & P. Semerád (Eds.), Knowledge and Digitalisation Against Corruption
and Fraud (pp. 7-22). Publishing House of Wroclaw University of Economics and Business.
DOI: 10.15611/2024.96.3.01
1.1. Introduction
Ukraine and the Czech Republic share a parcular common past: the Ukrainian Soviet Socialist
Republic and the Czechoslovak Socialist Republic, respecvely. Ukraine gained independence
in 1991, while Czechoslovakia did so in 1990, spling into the Czech Republic and Slovakia in
1993. This shared ‘socialist’ past has signicantly inuenced Ukraine and the Czech Republic.
However, unlike Ukraine, the Czech Republic has successfully overcome this legacy.
While the Czech Republic became increasingly economically developed, established a rule-of-
-law state free from oligarchic dominance, and achieved the status of a developed economy,
Ukraine remained a developing country plagued by powerful oligarchic clans and weak
legislave, judicial, and execuve bodies. According to World Bank data, in terms of GDP per
capita PPP, for Ukraine this value in 1993 was 5784.657 USD, reaching 12675.44 USD in 2022,
whilst for the Czech Republic it was 12124.34 USD and 49194.96 USD, respecvely. Over
30 years, Ukraine reached the economic level the Czech Republic had at the start of its
independence. Ukraine’s limited economic growth is partly aributed to corrupon
(Internaonal Monetary Fund, 2017), which has inltrated almost all spheres of society.
As a result, Ukraine embarked on a challenging journey to combat corrupon. Since 2017,
there have been four waves of surveys on corrupon percepon among individuals and
businesses. The latest wave (2022) indicated a slight posive trend. As perceived by the
respondents, the corrupon prevalence index was 4.49 points (out of a maximum of 5) in 2017
and 4.25 in 2022; for businesses, it was 4.52 and 3.98, respecvely. Delving deeper, experience
of corrupon was reported in areas such as law enforcement acvies (32.7% in 2022 versus
Knowledge and Digitalisaon Against Corrupon and Fraud 8
50.1% in 2021), services related to electricity, gas, water supply, and sewage (28.7% and
28.8%), higher educaon instuons (25.7% and 38.4%), public and municipal healthcare
(24.8% and 39.4%), relaons in construcon and use of land (23.9% and 45.3%), educaon
services (kindergartens) (15.5% and 33.3%), and primary and secondary educaon services
(13.0% and 33.5%). From these data, two things are evident: corrupon remains high, but
there is progress in the ght against it (InfoSapiens, 2022).
As regards the Czech Republic, based on the latest research (Bašna et al., 2023), the general
percepon of corrupon was around 11% and has a posive trend (improved during the last
decade). A similar result was presented by the Global Corrupon Barometer (Kukutschka, 2021),
however the percepon of the corrupon in individual sectors was dierent, and was mainly
aected by the corrupon scandals. For example, in the health sector the corrupon prevalence
index is 10% based on the Global Corrupon Barometer (hereinaer GCB) and 6% based on the
Eurobarometer (European Commission, 2023), although the percepon of corrupon in this
sector was, according to Bašna et al. (2023), more widespread than a decade ago, when
respondents very oen met with the oer of the trip to luxury hotels in exoc desnaons.
Another area was sports sector, considered very corrupt (Transparency Internaonal, 2016).
However, the current research highlights the fact that the percepon of corrupon was lower
in the Czech Republic, even though there were more forms of corrupon than in the last decade.
For example, bribing coaches by parents, inuencing match results, and the abuse of subsidies
are more widespread, and according to the respondents, range between 6 and 8% (Bašna et al.,
2023). In educaon, according to the Eurobarometer, the corrupon index was 15% (European
Commission, 2023), 6% based on the GCB (Kukutschka, 2021), and according to Bašna et al.
(2023), this sector was considered not to be so corrupt and the corrupon was generally less
widespread. However, corrupon was rife in public procurement and building/planning
procedures sectors. Based on the CEEC Research (2009) and Lidovky.cz (2017), more than 40%
of the respondents were asked to give bribes as a condion for receiving the tender (public
procurement) in the Czech Republic. Moreover, based on the Eurobarometer data, this kind of
corrupon is now more widespread, and its index is at the 21% level. According to Bašna et al.
(2023), more than 10% of the respondents considered such corrupon as generally widespread
and common, and more than 50% thought that the condions of the tender procurement were
set with the parcular applicant/bidder in mind. According to Transparency Internaonal
(2023), the Czech Republic was ranked for the purpose of corrupon as 41st out of 180 countries,
with a score of 57 points out of 100 (i.e., 16th in the European Union); the worst posion was
noted for Italy, Slovenia, Slovakia, Poland, Croaa, and other Balkan countries. Thus, similarly,
as in the case of Ukraine, corrupon is sll signicant in the Czech Republic.
Therefore, this study aimed to explore the specic features of corrupon in Ukraine and the
Czech Republic, as well as the an-corrupon measures being implemented to combat it.
1.2. Corruption: Meaning, Types, Measures
Before delving into the specics of combang corrupon, it is essenal to understand what
exactly is meant by it. Here, one immediately encounters a problem: corrupon has many
faces, and importantly, it has not always been viewed as evil in the past. Even today, it is not
always seen as such, and can be tolerated by society. In certain cultures what might be deemed
corrupt pracces, such as the necessity of giving gis, are considered normal due to cultural
nuances. One book on corrupon begins with this premise:
V. Solilova, N. Versal: Fight Against Corrupon in the Czech Republic and Ukraine 9
the darker aspect of polical trade, that is, the realm of corrupon, whose history is as long and
twisted as that of mankind’s aempt to live by the rule of law. Variously tolerated or fought,
depending on me and place, the very denion of corrupon has shied frequently, as
praconers of corrupon have encountered the ideas, laws, and customs of dierent peoples
(Brioschi, 2017, p. 1).
Perhaps one of the shortest denions of corrupon is found in Dante’s Commedia Divina:
“Describing the city of Lucca, Dante provides the single most succinct denion of a bribe:
Lucca is where No becomes Yes for money” (Noonan, 1987, p. 746). Such a scenario is possible
in any sphere. This can be applied to any associaon of people, whether at state level or within
corporaons. This is why the OECD, in its document (Corrupon: A Glossary of Internaonal
Standards in Criminal Law), does not provide a denion of corrupon but rather “establishes
the oences for a range of corrupt behavior” (OECD, 2008, p. 19). However, for the purposes
of “an-corrupon strategies, acon plans, and corrupon prevenon measures,” it is proposed
to consider corrupon as “abuse of public or private oce for personal gain” (OECD, 2008,
p. 19). According to the European Commission (2023), corrupon is the abuse of power for
private gain, which can take many forms, such as bribes, inuence peddling, and abuse of
oce, but it can also be hidden behind neposm, conicts of interest, ‘revolving doors’
between the public and private sectors. Given the study’s objecve comparing an-corrupon
measures in Ukraine and the Czech Republic, and considering the signicant dierences
between these countries, it is within this context that the authors examined corrupon.
Corrupon is manifested in numerous forms, and it is challenging to compile an exhausve list
of all of them. This analysis relied on the typology proposed by Andersen, which includes
bribery, embezzlement, neposm, extoron, ‘kickbacks’, money laundering, fraud, and
conicts of interest (Andersen, 2023). Table 1.1 provides case studies of corrupon in Ukraine
and the Czech Republic, encompassing one or mulple types of corrupon.
Thus, corrupon is a mulfaceted phenomenon, complicang the evaluaon of its level. This
is why various methodologies exist to measure corrupon.
Table 1.1. Case studies of corruption in Ukraine and the Czech Republic
Type
of corruption Ukraine The Czech Republic
Bribery
A deputy of the Kyiv City Council, who also
headed the city improvement commission,
was involved in organizing a corrupt
scheme designed to obtain illicit benefits
from entrepreneurs seeking permission to
place seasonal mobile kiosks. Specifically,
negotiations covered seven locations in
different districts of Kyiv in 2021, with
an agreement to illicitly obtain a total
of UAH 1.39 million (approximately USD
50 thousand), payable in two separate
instalments. The investigation into this case
was officially completed on 17 June 2022.
NCOZ officers charged 7 individuals and 2 legal entities
with the offences of arranging advantage in commissioning
public contract, public contest and public auction,
machinations in the commission of public contract
and public contest and fraud. The case concerned the
manipulation of tenders for the provision of the substitute
bus transportation in the course of scheduled rail closures
announced by the Czech Railways.
On 14 June 2022, NCOZ police officers conducted an action
day in the STOKA II case. From at least January 2014 to
March 2019, the accused persons influenced small-scale
contracts on repairs and maintenance of the real estate
premises of one state institution located in the South
Moravian Region and the Vysočina Region and one legal
entity with a seat in Brno. A certain percentage of the
prices of the contracts was meant for bribes. NCOZ police
officers came to the conclusion that dozens of contracts
were influenced in this way.
Kickbacks
Knowledge and Digitalisaon Against Corrupon and Fraud 10
Embezzlement
In October 2014, VAB Bank, identified as
‘troubled’, asked for a stabilisation loan
from the National Bank of Ukraine, using
real estate as collateral. The National Bank
of Ukraine approved a two-year stabilisation
loan of UAH 1.2 billion (approximately
USD 92 million) to VAB Bank. Subsequent
investigations revealed that the provided
valuation reports contained misleading
information, wherein the value of the real
estate was exaggerated almost 25 times.
VAB Bank, however, failed to repay this loan
at the end of the stipulated period.
On 16 and 17 May 2022 NCOZ carried out a police
operation related to the manipulation of tenders awarded
by the Radioactive Waste Repository Authority as the
contracting authority. At present, 6 individuals and 3 legal
entities are being prosecuted for the offence of arranging
advantage in commission of public contract, public
contest and public auction. The individuals are reasonably
suspected of organised crime comprising the manipulation
of two tenders of this particular contracting authority
between 2021 and 2022.
On 8 June 2022 NCOZ officers filed a motion for indictment
to the State Prosecutor of the High Public Prosecutor’s
Office in Prague against 21 natural persons and 1 legal
entity for the offence of influencing football matches
results in the Czech Football League and Fortuna: National
League and further for unauthorised withdrawal of funds
from Pilsen’s Regional Football Association.
Conflicts of interest
In the autumn of 2016, the head of the
National Police Department, leveraging
his official position, initiated a deal to
purchase equipment and specialist uniforms
from an acquaintance who was a private
entrepreneur. The specifications of these
items were set in such a way as to avoid
competition. As a result, the National
Police paid UAH 3 million, out of which the
private entrepreneur transferred UAH 980
thousand (approximately USD 38 thousand)
as payment for legal services to a company,
the beneficiary of which was that head of
the department.
The 2013 Czech political corruption scandal involved an
anti-corruption raid, launched by the organised crime
unit. It resulted in the arrest of the prime minister’s Chief
of Staff, Jana Nagyová, and seven others. Jana Nečasová
(Nagyová) was being investigated on suspicion
of corruption. In exchange for luxury gifts, she was
supposed to give the donors access to Prime Minister
Nečas or provide them with other benefits. Due to lack of
evidence, she was only charged with tax evasion. Another
part of the case concerns the misuse of the Military
Intelligence Service to monitor the former wife of Prime
Minister Nečas in 2012.
Money laundering
The State Investment Company, managed
by Derzhinvestproekt, received funding
in 2012-2014 for the implementation of
national projects “Quality Water” and
“Olympic Hope-2022”. Later investigations
revealed that over UAH 250 million
(approximately USD 31 million) had
been transferred to the accounts of
foreign companies based in Cyprus. It
was discovered that the brother of the
former head of “Derzhinvestproekt”
used this money to acquire shares in
Ukrainian companies that, between 2013
and 2015, purchased over 700 land plots
(approximately 1000 hectares) from
Ukrainian citizens.
NCOZ officers finalised their investigation of a case of tax
evasion and money laundering totalling approximately CZK
700 million. Within the OCTAVIAN case, 11 persons were
prosecuted. The defendants committed the crimes from
September 2009 until April 2012 by submitting excessive
VAT deductions within the companies they controlled.
NCOZ officers managed to seize assets corresponding to
the full amount of losses suffered by the Czech Republic
as a replacement. The case was pursued by the Tax Cobra
team in close cooperation with Czech FIU (FAÚ).
Fraud
In the Panama Papers case, many Czech citizens were
involved, particularly regarding foreign investments in the
Czech real-estate sector for the purpose of obscuring the
real ultimate beneficiaries of wealth (for further detail see
Holcova, 2016).
The motion to indict 66 persons of ČKD Praha DIZ for VAT
evasion dated 7 Jan2022: NCOZ officers filed an indictment
motion against 32 persons for the offence of tax evasion
committed for the benefit of an organised criminal group
or participation in the form of aiding this crime. The
suspects are believed to have included fake invoices related
to fictitious taxable transactions into the ČKD Praha DIZ
accounts, or have intended to do so. The VAT loss caused
by their concerted action to the state budget totalled
approximately CZK 438 million.
Source: (Dufková & Kotouček-Mikolášková, 2018; Holcova, 2016; NABU, 2021, 2022, 2023; NCOZ, 2022).
V. Solilova, N. Versal: Fight Against Corrupon in the Czech Republic and Ukraine 11
Firstly, the study considered the Corrupon Percepon Index (CPI) proposed by Transparency
Internaonal. This index is represented by the CPI Score (from zero to a maximum of 100 points:
the higher the rate, the beer the situaon) and the CPI Rank, where a higher rank correlates
with a greater level of corrupon. The СPI Score is calculated as the average value of data from
12 dierent sources, reecng experts’ percepon of the level of corrupon in the public
sector (Transparency Internaonal, 2023).
The CPI trends for Ukraine and the Czech Republic over the past decade, as illustrated in
Figure 1.1, reveal a signicantly higher corrupon level in Ukraine compared to the Czech
Republic. Despite the observed improvements in both countries, their disparity remains
substanal (on average 25 points in CPI Score). This is the case even with Ukraine’s considerable
eorts to combat corrupon.
0
20
40
60
80
100
120
140
160
0
10
20
30
40
50
60
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
CPI Rank
CPI Score
Ukraine CPI Rank The Czech Republic CPI Rank
Ukraine CPI Score The Czech Republic CPI Score
Fig. 1.1. CPI Score and Rank of Ukraine and the Czech Republic in 2012-2022
Source: (Transparency International, 2023).
The second one is the Index of Control of Corrupon proposed by the World Bank, and it
captures percepons of the extent to which public power is exercised for private gain, including
both pey and grand forms of corrupon, as well as ‘capture’ of the state by elites and private
interests. The esmate gives the country’s score on the aggregate indicator, in units of a standard
normal distribuon, i.e. ranging from approximately –2.5 to 2.5 (World Bank, 2023).
The lower the index, the higher the corrupon. According to Figure 1.2, an upward trend of this
index was observed in both countries, which is posive, however the average rate of change in
Ukraine is higher than in the Czech Republic. The authors emphasise once again that the eorts
made by Ukraine in the ght against corrupon are extraordinary, nevertheless, the pervasive
nature of corrupon and its level there hinders rapid progress in overcoming this issue.
One limitaon of the previously menoned indices is their reliance on expert subjecve
evaluaons. To address this, a novel methodology for index construcon has been developed by
Mungiu-Pippidi & Dadašov (2016) at the European Research Center for An-Corrupon and
State-Building. This new approach incorporates the evaluaon of causes of corrupon, thereby
enabling forecasts of its future levels, hence the third methodology considers the evaluaon of
Knowledge and Digitalisaon Against Corrupon and Fraud 12
two indices. The rst is the Index of Public Integrity with a maximum score of 10, comprising two
components: Opportunies for Corrupon and Constraints on Corrupon. The second is the
Transparency Index, which has a maximum score of 20. A more in-depth analysis of corrupon
allows to idenfy areas where each country is making signicant progress in combang it.
y = 0.0317x + 0.3105
y = 0.0453x – 1.1833
–1.2
–1
–0.8
–0.6
–0.4
–0.2
0
0.2
0.4
0.6
2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
The Czech RepublicUkraine
Linear (The Czech Republic) Linear (Ukraine)
Fig. 1.2. Index of control of corrupon of Ukraine and the Czech Republic in 2012-2022
Source: own elaboration based on (World Bank, 2023).
For instance, Ukraine has shown a notable posive trend in the dynamics of Online Services
and E-Cizenship, advancing by +3.51 points, in contrast to the Czech Republic’s improvement
in Online Services (+1.14) and E-Cizenship (+0.96) (Table 1.2). However, Ukraine signicantly
lags behind in crucial areas like Judicial Independence, despite eorts to reform this sector.
Overall, consistent with previous indices, the Czech Republic demonstrates beer outcomes in
the ght against corrupon.
Table 1.2. Ukraine’s and the Czech Republic’s corruption forecast
Indicators Max
2013 2023 Change
Ukraine The Czech
Republic Ukraine The Czech
Republic Ukraine The Czech
Republic
Opportunities for corruption
Budget Transparency 10 7.42 8.08 8.4 8.6 0.98 0.52
Online Services 10 4.82 5.88 8.33 7.02 3.51 1.14
Constraints on corruption
Judicial Independence 10 3.27 5.02 4.08 6.59 0.81 1.57
Press Freedom 10 6.69 9.08 6.51 8.52 –0.18 –0.56
E–Citizenship 10 4.82 5.56 8.33 6.52 3.51 0.96
Index of Public Integrity 10 6.37 8.14
Transparency Index 20 14.0 15.5
Source: (Corruptionrisk.org, 2023).
V. Solilova, N. Versal: Fight Against Corrupon in the Czech Republic and Ukraine 13
1.3. Policy Response
1.3.1. Ukraine
Legislation and anti-corruption bodies
The ght against corrupon in Ukraine is accompanied by the adopon of relevant legal acts,
notably: the Law of Ukraine on Prevenon of Corrupon dated 2014, the Law of Ukraine on
Naonal An-Corrupon Policy of Ukraine for 2021-2025 dated 2022, and the 2023 Cabinet of
Ministers of Ukraine resoluon on the approval of the Naonal An-Corrupon Programme
for 2023-2025.
The law on Prevenon of Corrupon established the Naonal Agency on Corrupon Prevenon
(NACP), which is “a central execuve body with a special status responsible for the development
of an-corrupon policy and prevenon of corrupon” (NACP, 2023). It develops An-
-Corrupon Strategy and State Programme, and administers: the Unied State Register of
Declaraons of Persons Authorized to Perform the Funcons of the State or Local Government;
the Unied State Register of Persons that Commied Corrupon or Corrupon-Related
Oences; the Unied State Register of Financial Reports of Polical Pares.
One more important instuon is the Naonal An-Corrupon Bureau of Ukraine (NABU), with
the main task “to combat corrupon and other criminal oences commied by top ocials,
which pose a threat to the naonal security of Ukraine, as well as to take other ancorrupon
measures under the Law” with the slogan “Eradicate and Prevent!” (NABU, 2023).
Also created were the High An-Corrupon Court (HACC) and Asset Recovery and Management
Agency (ARMA), each of which has its own area of responsibility.
Despite the creaon of specialised an-corrupon instuons, all levels of Ukrainian
government are engaged in an-corrupon eorts. Table 1.3 illustrates how the public and
business sectors perceive the eecveness of these eorts. Noted that businesses tend to be
more informed about the acvies of these an-corrupon bodies than the general populaon.
Table 1.3. Assessment by the individuals and business of the effectiveness of anti-corruption efforts
by government agencies 2021-2022
Institution Individuals Business
2021 2022 2021 2022
President of Ukraine / Office of the President of Ukraine 1.92 2.9 2.28 2.98
Security Service of Ukraine (SSU) 1.91 2.58 2.44 2.82
Local authorities 1.8 2.39 2.34 2.45
National Police of Ukraine 1.8 2.37 2.45 2.67
State Financial Monitoring Service of Ukraine 1.87 2.36 2.51 2.7
Regional authorities 1.79 2.35 2.3 2.39
Asset Recovery and Management Agency (ARMA) 1.8 2.34 2.2 2.62
National Anti-Corruption Bureau of Ukraine (NABU) 1.82 2.32 2.38 2.82
State Bureau of Investigation (SBI) 1.79 2.29 2.32 2.78
Knowledge and Digitalisaon Against Corrupon and Fraud 14
Specialised Anti-Corruption Prosecutor’s Office (SAPO) 1.85 2.25 2.38 2.79
National Agency on Corruption Prevention (NAPC) 1.77 2.23 2.27 2.66
High Anti-Corruption Court (HACC) 1.89 2.19 2.32 2.64
Prosecutorial authorities (other than the Specialised Anti-Corruption
Prosecutor’s Office) 1.85 2.16 2.22 2.41
Courts (other than the High Anti-Corruption Court) 1.69 2.12 2.23 2.36
Cabinet of Ministers of Ukraine, ministries, and other central executive
authorities 1.74 2.1 2.15 2.51
Parliament of Ukraine 1.67 2.09 2.02 2.34
Average score on a 5-point scale, where 1 means that anti-corruption efforts are completely ineffective, and 5
means that they are highly effective.
Source: (InfoSapiens, 2022).
The ght against corruption
Combang corrupon is a complex task. Unfortunately, the enactment of good and proper
laws, the imposion of stricter penales for corrupt acons, and the establishment of an-
-corrupon bodies do not always adequately respond to this challenge. Much depends on
society’s readiness to change its atude towards corrupon. Moving forward, the authors
demonstrated several examples from dierent sectors where the ght against corrupon can
be considered successful.
The sectors where corrupon is possible can be generalised as educaon, healthcare, and
administrave services. Currently, signicant progress is evident in all these sectors.
Numerous reforms have been implemented in educaon to prevent corrupon, such as the
centralised preparaon of examinaon tasks for both Bachelor’s and Master’s degree
admissions and eliminang corrupon at the level of higher educaonal instuons. There are
special electronic queues for kindergarten admissions, etc. In 2022, a survey of Ukrainians
indicated experiences of corrupon in higher educaon instuons at 11.9%, elementary and
secondary educaon at 21.4%, and kindergartens at 8.3% (InfoSapiens, 2022).
In healthcare, electronic sick leaves have been introduced, and basic services provided to the
populaon are clearly listed in each medical facility, including available medicaons and free
services. However, this sector remains corrupt, with 51% of Ukrainians having direct corrupon
experience in 2022 (InfoSapiens, 2022).
At the level of state authories, corrupon has signicantly decreased due to the
implementaon of Diia a “state in a smartphone” iniave. Many documents, previously
requiring signicant me to obtain, are now accessible with one click. However, issues remain
in areas involving direct contact with public ocials. For example, in the acvies of
administrave service centres, 20.4% of Ukrainians experienced corrupon in 2021, which
increased to 22.8% in 2022 (InfoSapiens, 2022).
Thus, it is clear that progress is being made and remains stable where direct contact between
interested pares is removed, because consumers of services can also be iniators of pey
corrupon, creang a vicious circle.
V. Solilova, N. Versal: Fight Against Corrupon in the Czech Republic and Ukraine 15
In the business sector, the ght against corrupon connues. In 2022, corrupon experiences
were reported as follows: 11.3% in customs, 8.5% in construcon and land use, 9.0% in services
related to power, gas, water supply, and sewer systems, 8.0% in the judicial system (including
enforcement of court decisions), 9.4% in monitoring and oversight of business acvies, 14.0%
in the acvies of law enforcement authories, and 23.2% in the acvies of tax authories
(InfoSapiens, 2022).
At the same me, one of the most signicant achievements in Ukraine is the implementaon
of the Prozorro system in the sphere of public procurement. Prior to 2016, the public
procurement sector in Ukraine was plagued by non-transparency and systemic corrupon.
Informaon pertaining to tender processes was disseminated exclusively through the Bullen
of State Procurements, a publicaon with limited circulaon. The submission of procurement
proposals was conned to paper format, resulng in their occasional loss. Through
a collaborave eort involving the civil organizaon Transparency Internaonal Ukraine,
private electronic plaorms, the IT company Quintagroup, and the Ministry of Economy, the
electronic plaorm Prozorro, recognised for its transparency, was developed. Currently, this
system is state-owned and subject to oversight by the Cabinet of Ministers (Khutor et al., 2024;
Prozorro, 2024).
From 1 April 2016, the Prozorro system became mandatory for central government enes and
monopolies, expanding its reach to encompass other public procurement enes from 1 August
2016 onwards. As a result, any individual in Ukraine can now track procurements and assess the
adequacy of prices, as well as idenfy the parcipants in tenders. Thanks to this system, numerous
instances of corrupt acvies have been exposed and addressed (Prozorro, 2024).
Currently, Prozorro and the NACP have intensied their collaboraon, including integrang
their electronic procurement system with the Unied State Register of Persons who have
commied corrupt or corrupon-related oenses (Prozorro, 2024).
1.3.2. The Czech Republic
Legislation and anti-corruption bodies
Based on internaonal comparisons in recent years, it has emerged that the Czech Republic
has been stagnang in its ght against corrupon and, accordingly, in the evaluaon metrics.
For this reason, the current government is striving to implement a number of correcve
measures. One of the signicant documents is the Government Concept for Combang
Corrupon for the period 2023 to 2026 (hereinaer the Government Concept), which was
approved by Resoluon No. 228 of the Government of the Czech Republic on 5 April 2023, that
idenes priority areas for combang corrupon (Figure 1.3).
Another equally signicant document is the Acon Plan to Combat Corrupon (for the years
2023 and 2024), which is regularly compiled for specic periods and was approved by
Government Resoluon No. 508 on 12 July 2023. The aim of the Acon Plan was to specify the
tasks of individual legislave and non-legislave measures for the priority areas of the
government’s an-corrupon policy, and to determine the responsible authority for their
implementaon. Emphasis is placed parcularly on the eecve implementaon of an-
-corrupon standards rather than their quanty.
Knowledge and Digitalisaon Against Corrupon and Fraud 16
Ecient
and independent
public power
Transparency
and open access
to informaon
Economical
management
of state property
Development
of civil society
Fig. 1.3. Priority areas for combang corrupon in the Czech Republic
Source: compiled based on the Government Concept for Combating Corruption for the period 2023 to 2026.
The measures of the Acon Plan will complement other signicant strategic documents, such
as the Strategic Framework Czech Republic 2030, the Concept of Client-oriented Public
Administraon 2030, and the Digital Czech Republic strategy, as well as reforms, including
component 4.3 An-Corrupon reforms of the Naonal Recovery Plan of the Czech Republic,
which is funded by the EU.
As already menoned, the Czech Republic has been engaged in the ght against corrupon for
over a decade. A signicant milestone was the establishment of the Open Government
Partnership (OGP), a voluntary iniave of the United States administraon aimed at promong
openness, transparency, combang corrupon, and increasing civic engagement. Since its
founding in 2011, OGP has grown to include 75 countries and 104 local jurisdicons. The Czech
Republic joined this internaonal iniave by Government resoluon No. 691 on September
14, 2011, with the aim of transforming state instuons to be more open, ecient, and
accountable. The country is also part of internaonal assessments in the ght against
corrupon. Currently, anyone encountering any form of corrupon can report such situaons.1
Furthermore, among other measures, in 2014, Government resoluon No. 629 approved the
Government Council for the Coordinaon and Evaluaon of the Fight against Corrupon,
which replaced the former Government Commiee for the Coordinaon of the Fight against
Corrupon established in 2012. Currently, it includes a total of 20 members from among
ministers, the Naonal Centre against Organised Crime (NCOZ), heads of the Associaon of
Regions and the Union of Towns and Municipalies, as well as non-governmental organisaons,
the academic community, and professional chambers.2
1 The website for the announcement of the corrupon is: hps://nahlasitkorupci.transparency.cz/#/
2 The list of members is available at: hps://korupce.cz/wp-content/uploads/2023/09/Seznam-clenu-Rady-
vlady-pro-koordinaci-boje-s-korupci_zari_2023.pdf
V. Solilova, N. Versal: Fight Against Corrupon in the Czech Republic and Ukraine 17
A signicant achievement of the Government Commiee was the introducon of the
mandatory assessment of corrupon risks, i.e. Corrupon Impact Assessment (CIA), alongside
the exisng Regulatory Impact Assessment (RIA) within the government’s legislave rules.
The core of the methodology is a straighorward evaluaon of corrupon risks associated
with proposed legislaon, allowing for the consideraon of criteria for reducing corrupt
opportunies when draing legal proposals. Since the incepon of the Government Commiee
and the respecve Acon Plans, the goal has been to more rigorously monitor the
implementaon of RIA and CIA within the legislave process. The successor Government
Council recommended connuing to use this methodology for RIA and CIA in the preparaon
of legislave proposals.
In addion to the aforemenoned methodologies, the Czech Republic has implemented the
Framework Resort Internal An-Corrupon Programme (RRIPP), which sets out the framework
for these internal programs (RIPP), thus standardising the structural and content-related form
of RIPP. Furthermore, a RIPP report is regularly prepared every two years, for which
methodological guidelines – recommendaons for RIPP evaluaon are also created.
The Czech Republic has also established the Interdepartmental Coordinaon Group for An-
-Corrupon based on the Government’s An-Corrupon Strategy, currently overseen by the
Ministry of Jusce An-Corrupon Department. The aim of this working group is to dene
key priories of government an-corrupon policy, acvely idenfy areas of public
administraon performance that are most at risk of corrupon, propose measures to eliminate
these risks, and monitor and evaluate an-corrupon measures, including monitoring the
legislave process in this area.
The An-Corrupon Department, under the Ministry of Jusce, is currently a strategic division
that gathers all news, legislave and non-legislave measures related to the ght against
corrupon, an-corrupon documents, departmental/interdepartmental groups, and other
collaboraons on its website.3 The An-Corrupon Department is part of the Conict of
Interest and An-Corrupon Division within the Secon for Coordinang Legislaon and
Corrupon Prevenon at the Ministry of Jusce. Its main agenda involves coordinang various
departments (resorts) in the ght against corrupon, including providing methodological
support and ensuring compliance with commitments in this area arising from internaonal
convenons, memberships, and other internaonal organizaons.
The direcons of the an-corrupon agenda, which is a summary of legislave and non-
-legislave measures and procedures applied in the ght against corrupon, are as follows:
Establishment of an independent, ecient, professional, integrated, and corrupon-
-resistant public administraon.
Independence of the public prosecutor’s oce from polical inuences.
Transparency and eciency of decision-making and legislave processes.
Streamlining the system of free access to informaon.
Expansion and rigorous applicaon of Regulatory Impact Assessments (RIA) and Corrupon
Impact Assessments (CIA) in legislaon.
More eecve prevenon of conicts of interest.
Clear rules for nancing polical pares, as well as electoral campaigns.
Creaon of binding standards for the nominaon of state representaves to corporaons
and state-owned enterprises.
3 hps://korupce.cz
Knowledge and Digitalisaon Against Corrupon and Fraud 18
Adopon of prevenve measures to limit corrupon risks in the management of public
funds.
Strengthening of managerial and control mechanisms in public administraon.
Protecon of corrupon whistleblowers.
Implementaon of the Framework Resort Internal An-Corrupon Programme (RRIPP)
and Resort Internal An-Corrupon Programmes (RIPP).
Table 1.4 lists the most signicant legislave and non-legislave regulaons in the ght against
corrupon that have been proposed or are currently under consideraon.
Table 1.4. Anti-corruption regulations in the Czech Republic
Legislative and non-legislative anticorruption regulations Responsible authority
Update of the Framework Resort Internal Anti-Corruption Programme Ministry of Justice
Amendment to Act No. 283/1993 Coll., on Public Prosecution Ministry of Justice
Amendment to Act No. 7/2002 Coll., on Proceedings Concerning Judges, State
Prosecutors, and Judicial Executors, as amended, and other related laws
Ministry of Justice
Implementation of the project “Intensifying the Fight Against Corruption by
Increasing Awareness in the Public Sector with a Focus on Judges, Authorities
Involved in Criminal Proceedings, and Public Administration” – Professional and
Ethical Codes of Judges and State Prosecutors
Ministry of Justice
Proposal of the Law on Lobbying and Related Amendment Act Ministry of Justice
Processing an analysis aimed at identifying potential issues with Act No.
159/2006 Coll., on Conflict of Interest, as amended
Working Commission
of the Chairman of the
Government Council for
Coordination of the Fight
against Corruption on
Conflict of Interest / Ministry
of Justice
Creation of the Action Plan of the Czech Republic for the Open Government
Partnership for the years 2025 to 2026.
Ministry of Justice
Implementation of the commitment of the Sixth Action Plan: Transparency of
state-provided subsidies.
Ministry of Finance /
Ministry for Regional
Development
Implementation of the commitment of the Sixth Action Plan: Strengthening the
quality of data in the register of beneficial owners – analysis and proposal of
measures.
Ministry of Justice
Proposal of the law amending Act No. 134/2016 Coll., on Public Procurement,
as amended.
Ministry for Regional
Development
Implementation of the commitment of the Sixth Action Plan: Involving the
public in monitoring public procurement.
Ministry for Regional
Development
/ Ministry of Labour and
Social Affairs
Implementation of the commitment of the Sixth Action Plan: Increasing
transparency and methodological support for the procurement of small-scale
public contracts.
Ministry for Regional
Development
Continuation of methodological support for Act No. 253/2008 Coll., on
certain measures against the legalisation of proceeds from crime and
terrorist financing, as amended, its development, updating, and expansion of
methodological support including issues related to politically exposed persons.
Financial Analytical Office
/ Ministry of Finance The
substantive intent of the law
on the management and
control of public finances
Ministry of Finance
V. Solilova, N. Versal: Fight Against Corrupon in the Czech Republic and Ukraine 19
Implementation of measures from the Strategy for Combating Fraud and
Corruption within EU Funds incorporated into the Single National Framework.
Ministry for Regional
Development
Completion of the legislative process of proposals of laws transposing Directive
2019/1937 of the European Parliament and of the Council on the protection of
persons reporting breaches of Union law.
Ministry of Justice
Implementation of the commitment of the Sixth Action Plan: Improving
the position of whistleblowers, including increasing awareness of reporting
wrongdoing.
Ministry of Justice
Continue supporting anti-corruption activities of non-governmental non-
-profit organizations through the grant program for the Prevention of Corrupt
Practices.
Ministry of Justice
Proposal for the implementation of recommendations from the project: The
Corruption in Selected Sectors in the Czech Republic and possibilities for its
reduction.
Ministry of Justice
Source: (Ministry of Justice, 2023).
Another signicant legislave measure is the compleon of the legislave process and
subsequent implementaon of the Whistleblower Protecon Act (Whistleblowing Regulaon4),
adopon of lobbying regulaon5, or adopon of an amendment to the Public Prosecuon Act,
stemming from the regular evaluaon report of GRECO (Group of States against Corrupon,
the Council of Europe). From the latest h round6 of GRECO evaluaons, it also emerged that
the Czech Republic should take measures regarding the integrity of individuals in top execuve
posions (i.e. introducon of a code of conduct, including integrity tests for advisors, ministers,
and deputy ministers before appointment) including expanding the regulaon of conicts of
interest aer terminaon of employment. In the case of conicts of interest, GRECO
recommends strengthening the obligaon to report a given conict ad hoc. The Ministry of
Jusce is conducng the necessary analysis to idenfy changes to the Conicts of Interest Law
to propose necessary amendments. The Ministry of Jusce also, upon GRECO’s recommendaon,
allows for the publicaon of asset declaraons of public ocials upon request. In response to
GRECO’s recommendaons, the Czech Republic will inform GRECO about the measures taken
by 31 December 2024.
The ght against corruption
The An-Corrupon Department, under the Ministry of Jusce, also oversees a range of
programmes and projects. One of these acvies was the project “Intensifying the Fight
Against Corrupon by Increasing Awareness in the Public Sector with a Focus on Judges,
4 The comprehensive legal regulaon of whistleblowing came into eect on August 2023, through Act
No. 171/2023 Coll., on the protecon of whistleblowers, including the accompanying amending Act No.
172/2023 Coll., transposing into Czech law Direcve 2019/1937 of the European Parliament and of the
Council of the European Union of 23rd October 2019 on the protecon of persons who report breaches of EU
law. Available at: hps://eur-lex.europa.eu/legal-content/CS/TXT/PDF/?uri=CELEX:32019L1937&from=CS
5 Proposal of the Law on Lobbying and Related Amendment Act was submied to the Government of the
Czech Republic by the Ministry of Jusce on 9th May 2023. Currently, they are being discussed in the Chamber
of Depues. The eecveness is expected by 1st July 2025. Its introducon is advocated by non-governmental
organizaons, the OECD, and the Council of Europe. According to the proposal, a lobbyist for the most serious
type of oenses may be ned up to 1 million CZK or be subject to a ban on acvies.
6 Informaon about the acvies of the GRECO group and their assessment reports is available on the website:
www.coe.int/greco. Report for Czechia is available at: hps://rm.coe.int/grecoeval5rep-2022-7-nal-eng-
evaluaon-report-czech-republic-public/1680aeb6aa
Knowledge and Digitalisaon Against Corrupon and Fraud 20
Authories Acve in Criminal Proceedings, and Public Administraon” supported by the EEA
Funds 2014-2021. The project lasted for almost three years (ending in October 2023) and was
performed by the Ministry of Jusce in partnership with the Supreme Public Prosecutor’s
Oce and the Judicial Academy. As part of the project, brochures on Whistleblower Protecon,
Conict of Interest among Public Ocials, and Ethical Codes for Judges and Prosecutors were
produced. Comparave studies addressing these issues were also conducted.
Another signicant project supported by the Ministry of Jusce as the implemenng guarantor
and by the Grant agency Technology Agency of the Czech Republic (TAČR) is the project
“Corrupon in Selected Sectors in the Czech Republic and Opons for Its Reducon” carried
out by the Sociological Instute of the Czech Academy of Sciences for three years (concluded
on 31 December 2023). The project presented tools for replicable, eecve, and valid
measurement of direct and indirect experiences with corrupon in dierent sectors. The
project’s results were reected in two strategic documents: the Government Concept for the
years 2023 to 2026 and the Acon Plan for 2023 and 2024. Based on the project, percepons
of corrupon and its actual occurrence among the respondents in various sectors were
measured (Bašná et al., 2023).
1.4. Conclusions
This study has comprehensively explored the corrupon in Ukraine and the Czech Republic,
providing a comparave insight into how each country has addressed this pervasive issue
through various legislave and an-corrupon strategies.
Despite signicant eorts and reforms in Ukraine, corrupon connues to impede economic
and social development. Introducing systems like Prozorro for public procurement transparency
shows promise in reducing corrupon levels, but the overall eecveness remains constrained
by persistent systemic issues. The legislave frameworks and an-corrupon bodies such as
the NACP and NABU underscore a robust commitment to combang corrupon. However, the
public percepon and business experiences suggest that these measures must be more deeply
embedded in the societal and polical fabric to eect substanal change.
Conversely, with a stronger instuonal framework and higher economic development, the
Czech Republic has demonstrated more substanal progress in its an-corrupon eorts.
Adopng the Government Concept for Combang Corrupon and subsequent acon plans
illustrates a proacve approach to rening the governance landscape. However, the study
idenes that despite these advancements, the country sll faces challenges in fully eradicang
corrupon, parcularly in sectors prone to corrupon scandals. The ongoing eorts need to
focus on enhancing transparency, reducing opportunies for corrupon, and fostering a culture
of integrity within all levels of government and society.
The connuous improvement in the corrupon percepon indexes over the years for both
countries indicates a posive trend, but it also highlights the need for sustained and intensied
eorts.
Moving forward, Ukraine and the Czech Republic must connue to innovate and adapt their
an-corrupon strategies based on naonal needs and evolving global standards. Strengthening
the legal and instuonal frameworks, ensuring the independence of judicial systems, and
promong a societal shi towards transparency and accountability will be crucial in making
signicant headway against corrupon.
V. Solilova, N. Versal: Fight Against Corrupon in the Czech Republic and Ukraine 21
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Chapter 2
The Use of Digital Technology in the Fight Against
Welfare Fraud: Comparative Analysis
of Selected National Experiences
Łukasz Jurek
Assistant Professor, Wroclaw University of Economics and Business
ORCID: 0000-0002-0078-471X
© 2024 Łukasz Jurek
This work is licensed under the Creave Commons Aribuon-ShareAlike 4.0 Internaonal License.
To view a copy of this license, visit hp://creavecommons.org/licenses/by-sa/4.0/
Quote as: Jurek, Ł. (2024). The Use of Digital Technology in the Fight Against Welfare Fraud: Compara-
ve Analysis of Selected Naonal Experiences. In P. Luty, N. Versal, & P. Semerád (Eds.), Knowledge and
Digitalisaon Against Corrupon and Fraud (pp. 23-35). Publishing House of Wroclaw University of
Economics and Business.
DOI: 10.15611/2024.96.3.02
2.1. Introduction
The term ‘welfare state’ is ambiguous. It was coined in England during the Second World War
in contrast to another term that was common at that me, ‘warfare state’. The replacement of
‘warfare’ by ‘welfare’ was intended to be a symbolic shi from an economy focused on pro-
arms producon, which provided cizens with military security, to pro-social producon
supposed to provide cizens with social security.
The welfare state was developed for both equity and eciency reasons. Thus, according to
Barr (2020), it can be thought of as (1) a set of instuons that provide poverty relief,
redistribute income and wealth, and seek to reduce social exclusion (the ‘Robin Hood’ funcon),
and (2) a set of instuons that provide insurance and a mechanism for redistribuon over the
life cycle (the ‘piggy bank’ funcon).
The design of the welfare state varies from country to country (Esping-Andersen, 1990).
Despite some dierences, the overall size (tasks, funds, administrators) of the welfare state is
systemacally increasing in Western countries (Quadagno, 1987), due to the growth of
tradional issues caused by demographic change and shis in industrial relaons. There is also
the emergence of new risks related to, for example, epidemiological issues. All this increases
the pressure on public authories to extend a safety net for cizens.
The development of the welfare state has enabled to overcome crucial social problems,
however it also raised a number of concerns about operang costs and administrave
eciency. Excessive bureaucracy hampers social policy programmes, especially at the stage of
benet distribuon. The mulplicity of procedures and ineecve control make the welfare
system open to various types of abuse and fraud. Public funds that were to serve good causes
Knowledge and Digitalisaon Against Corrupon and Fraud 24
are being extorted by unauthorised persons. This problem, although for a long me overlooked
and/or neglected, is now becoming a major challenge for theorists and policy-makers. The use
of modern technology seems to be the only reasonable soluon in this situaon. Mass data
collecon, automaon, and arcial intelligence can essenally increase eciency in detecng
and combang welfare fraud. It is crucial therefore, as stated by Henman (2022, p. 536), “to
bring the ‘digital’ into ‘social policy’”.
So far, only a few countries have digised their welfare infrastructure. Sociees where local
governments have developed AI-driven technologies to eliminate non-compliance have been
involved in a massive experiment. Their experience has shown that while technology reduces
old problems such as low operaonal eciency and high bureaucrac costs, it also creates
a new set of problems and concerns, with the emerging crical issues of data protecon,
privacy and e-exclusion. In retrospect, the overall outcome is mixed and to some extent
controversial. For this reason, the general narraves in the literature range from the techno-
-opmisc to the techno-pessimisc (Fugletveit & Sørhaug, 2023).
This chapter describes the experiences of two countries (the Netherlands and Australia) in
using digital technologies to detect and combat welfare fraud, and also aempts to assess the
strengths and weaknesses of such a digital transformaon. It is both analycal and descripve,
and based on analysis of literature and ocial documents.
2.2. Digital Welfare State: Theoretical Approach
The world is changing fast, and the technological revoluon we are witnessing today touches
all areas of society. Every aspect of human existence is more or less aected by modernity,
with technologies penetrang every aspect of life. However, the pace of this diusion varies in
dierent areas. Public administraon has tradionally been very conservave and resistant to
change, hence innovaons do not aect it as quickly as, for example, the corporate world.
Somemes it is necessary to smulate this development, in order to encourage the adaptaon
of new tools based on technology.
In general, digital transformaon may be described as the transion from ‘analogue’ to ‘digital’.
This shi has also aected the welfare state. In order to emphasise the scale and quality of
change, various load-bearing labels are used in the literature, such as: digital social policy,
social policy 4.0, and digital welfare state (Szatur-Jaworska, 2023).
In 2014, on the iniave of the OECD Council, member countries adopted Recommendaon of
the Council on Digital Government Strategies (OECD, 2014). The document called on
governments to develop and implement digital strategies in order to achieve digital
transformaon. Technologies were to be a strategic driver to create an open, parcipatory,
and trustworthy public sector, to improve social inclusiveness and government accountability,
and to bring together government and non-government actors and develop innovave
approaches to contribute to naonal development and long-term sustainable growth.
Digital transformaon in the public sector responds to the need to modernise public services.
This change seems inevitable in the face of new and growing expectaons of the welfare state
and the necessity of state administraon to deal with increasingly complex issues. As such, it has
become a polical imperave to improve the eciency, eecveness and governance of public
services by designing and implemenng innovave technological soluons (OECD, 2016).
Ł. Jurek: The Use of Digital Technology in the Fight Against Welfare Fraud... 25
At normave level, a major contribuon to the digital transformaon of the welfare state has
been made by the United Naons. The notable report on extreme poverty and human rights
(Alston, 2019) highlighted the strategic importance of the digital transformaon of the welfare
state as a transformaon of the relaon between the state and cizens, from analogue to
digital, to improve governance through eciency, integrity, and transparency. The document
established the term ‘digital welfare state’, in which “systems of social protecon and assistance
are increasingly driven by digital data and technologies that are used to automate, predict,
idenfy, survey, detect, target and punish” (Alston, 2019, p. 4). Moreover, it was stressed that
new forms of governance are emerging which rely signicantly on the processing of vast
quanes of digital data from all available sources, use predicve analycs to foresee risk,
automate decision-making and remove discreon from human decision makers […]. In such
a world, cizens become ever more visible to their Governments, but not the other way around.
(Alston, 2019, p. 4)
The concept of the digital welfare state has been subject to much development and modicaon
since then. In their extensive study on datacaon in the context of welfare state, Dencik and
Kaun (2020, p. 2) explored a “shi toward a new regime in public services and welfare provision
intricately linked to digital infrastructures that results in new forms of control and support.
The importance of this technical-driven transformaon of the welfare state was also emphasised
by van Gerven (2022):
The welfare state and its management of social risks is clearly aected by the technological
transformaons of the late tweneth and early twenty-rst centuries. It creates a need to
reorganize and recalibrate welfare state structures and systems to extend social risk protecon
towards a diverse set of risks, including exisng (e.g. changing family structures and labour
market parcipaon paerns) and ‘new’ digitally driven risks (e.g. labour market insecuries
induced by plaorm work and automaon). (p. 254)
According to Henman (2022), the juscaons for the digitalisaon of the welfare state can be
divided into two groups: ‘tradional’ and ‘new’. The ‘tradional’ juscaons have been
behind the transformaon from the beginning and have not changed over me. These are:
eciency, cost reducon, sta savings, consistency of decisions and reducon of errors. The
‘new’ juscaons, on the other hand, have emerged more recently. These are: policy
responsiveness and agility, customer service and service innovaon, personalisaon,
overpayment and fraud detecon, improved governance and enhanced accountability and
democracy.
Technology oers a wide range of soluons to improve the structure and funconing of the
welfare state. The above-menoned United Naons report (Alston, 2019) idened six areas
as being parcularly open to the use of modern technology.
1. Identy vericaon: a veriable identy is essenal for claiming benets, establishing
entlements, receiving benets and appealing against benet denials. Modern
idencaon systems contain both demographic and biometric informaon on all
residents, including an iris scan, photograph and ngerprints.
2. Eligibility assessment: IT systems support decision-making processes and increase the
eciency of analysing large databases. They relieve caseworkers of clerical tasks, and
make decisions independent of subjecve opinion, ensuring transparency and objecvity.
They also allow for connuous monitoring of the situaon of beneciaries in terms of
compliance with entlements.
Knowledge and Digitalisaon Against Corrupon and Fraud 26
3. Welfare benet calculaon and payments: using spreadsheets and algorithms to automate
the calculaon of benets, and paying them out using digised nancial services such as
bank transfers and electronic payment cards.
4. Fraud prevenon and detecon: informac systems allowing to match data from dierent
sources in order to expose decepon and irregularies on the part of welfare applicants.
5. Risk scoring and need classicaon: algorithm-based techniques to determine whether
intervenon is required and, if so, at what level.
6. Communicaon between welfare authories and beneciaries: tradional forms of
communicaon (face-to-face, telephone, leer) are being replaced by online applicaons
and interacons (e.g. chatbots).
Generally, these areas of digitalisaon can be divided into two basic domains: rule-based
systems and predicve systems. A rule-based system helps to verify eligibility for benets and,
if applicable, to calculate the amount of benets. Predicve systems, on the other hand, are
risk-proling tools that sort welfare claimants into dierent levels of intervenon. The risk
assessment is based on indicators that are idened by research and/or mandated by policy.
On this basis a stascal model is formed that gives a probabilisc score for each individual. As
noted by Well et al. (2023, p. 45), “companies, professionals and somemes academics develop
these assessment tools in relaon to a historic comparave populaon and past experiences
of service provision, oen using stakeholder consultaon, trials, validity and usability tesng
and factor analysis”.
Today, the issue of the digitalisaon of the welfare state is becoming a priority for both social
policy theorists and praconers. Many research and implementaon projects in this area are
being undertaken in many countries. Such iniaves are now also taking place at transnaonal
level. One example is AUTO-WELF, the rst project to provide an analysis of automated welfare
provision across dierent European welfare regimes, which examines the implementaon of
automated decision-making (ADM) in the welfare sector across Europe.1
2.3. Welfare Fraud and Welfare Surveillance
Welfare fraud is a complex and muldimensional issue (Jurek, 2024). This term is oen used as
synonymous with ‘welfare abuse’ or ‘welfare crime’, although these are not enrely clear-cut.
Their common feature is non-compliance with the welfare rules, resulng in incorrect
payments, i.e. payments made for the wrong reason or for the wrong amount. However, not
every incorrect payment is a case of welfare fraud. Firstly, the non-compliance may involve
both an over- and understatement of the welfare benet. Second, the overconsumpon may
be the result of unintenonal error or intenonal behaviour. Third, intenonal overconsumpon
may be irraonal but legal (moral hazard) or illegal (fraud). Fourthly, fraud can be of dierent
‘degrees of seriousness’, it can be a minor oence (the so-called crimes of everyday life) or
a serious crime commied on a large scale by organised criminal groups.
The issue of welfare non-compliance has become an important issue in European Union policy.
This is linked to a number of irregularies that have arisen with the increasing coordinaon of
naonal social security systems. In response to these problems, it was decided (Decision No
H5 of 18 March 2010…) to call on the Member States to take appropriate remedial acon in
1 Project website: hps://blogg.sh.se/digitalwelfare
Ł. Jurek: The Use of Digital Technology in the Fight Against Welfare Fraud... 27
this area. EU documents disnguish two types of irregularies: fraud and error (Jorens et al.,
2019). A fraud is dened as any act or omission contrary to naonal legislaon, either in order
to obtain benets from the social security system or to evade the obligaon to pay public
contribuons to maintain this system. An error, on the other hand, is considered to be an
unintenonal mistake or oversight on the part of ocials or cizens.
European countries are developing their own denions of welfare abuse as well as methods
for the prevenon, detecon and deterrence. These measures are parcularly advanced in
Sweden, where in 2021 the country’s government adopted a special ordinance that regulates
iniaves to ensure proper payments from the welfare system (Sveriges Riksdag, 2021). The
coordinaon of these acvies has been entrusted to the Naonal Instuon for Financial
Management (ESV). According to its guidelines (Modin & Lindblom, 2021), a payment from the
social security system is incorrect if it is made even though the condions for receiving the
benet have not been met. The benet may be too high, too low, or completely undue based
on the applicable regulaons. Incorrect payments range from unintenonal errors to large-
-scale, systemac and organised welfare crime. To illustrate this diversity, the welfare
compliance pyramid was used (Fig. 1), which contains four types of incorrect payments that
dier greatly in terms of move, severity, and structure.
Unintended errors
Welfare
abuse
Welfare
fraud
Welfare
crime
Fig. 2.1. Welfare compliance pyramid
Source: (Modin & Lindblom, 2021, p. 11).
Unintended errors are the result of mistakes that are unconscious and unintenonal. Welfare
abuse is the conscious provision of misinformaon in order to misuse welfare entlements.
Welfare fraud is the pracce of extoron and decepon (e.g. bribery, forgery, cheang and
lying) to obtain undue benets, whereas welfare crime is an organised acvity carried out on
a large scale against welfare instuons.
Similar legislaon exists in the Netherlands (Eerste Kamer, 2012). The Dutch legislaon
disnguishes between ‘improper use of benets’ and ‘benet fraud’. Improper use is dened
as “using the entlements in a way that is allowed by law but not in the spirit of the law.
Fraud, on the other hand, is dened as “the use in a manner not permied by law”.
Knowledge and Digitalisaon Against Corrupon and Fraud 28
Kukuła (2016) dened welfare fraud as
acons of natural persons aimed at persuading a social instuon to dispose of its property
in a certain way and obtain material benets not due to them, which full the characteriscs
of a crime, consisng in deliberately misleading or exploing the error of an instuon
dealing with the distribuon of budget funds, aimed exclusively at providing assistance or
material support to people, both those who have a source of income and those who are
temporarily or permanently deprived of it. (p. 28)
It is, therefore, a manifestaon of conscious and deliberate pathologies commied by private
individuals in the use of welfare benets.
By its very nature, welfare abuse is dicult to detect. The main reason is the blurred line between
jused and unjused benet use. As described by McKeever (2012, p. 472), this boundary lies
between need and greed. Usually, it is very dicult to assess whether the use of benets is really
necessary because of a dicult life situaon or whether it is rather a maer of cheang. In the
case of welfare fraud, however, the situaon is clear, as it is a clear violaon of the law.
The extent of welfare fraud is dicult to measure. It is obviously inappropriate to draw conclusions
from the results of inspecons carried out by control bodies, because of the potenally very
large underesmaon bias. This type of data does not show the actual number of frauds
commied, but only the number of cases detected. The relaon between these two gures, i.e.
the number of frauds commied and the number of frauds detected, is unknown and depends
on many factors, the most important of which is the frequency and quality of controls.
The basic problem is that the general structure of the social system was not designed for
monitoring. Administrators generally see the essence of their job as providing benets, not
exercising control. The eecveness of their work is measured by the number of payments
made, not by the number of wrongly withheld payments. In some cases, the rules leave
administrators a lot of room for subjecve judgement, which makes it dicult to idenfy
incorrect payments. In addion, controls tend to be carried out in those areas that are easy to
perform and “produce results” (Korsell et al., 2008).
It can be assumed that the extent of welfare fraud varies from country to country. This is partly
due to instuonal and legal dierences (control measures and severity of sancons), but
above all to socio-cultural condions. This concerns the level of so-called ‘benet morality’, i.e.
the individual reluctance to exploit the welfare state through fraud (Halla et al., 2010;
Heinemann, 2008).
The genesis and development of the ght against welfare fraud, although taking place in
dierent countries and at dierent mes, are to some extent similar. The general trajectory of
events is largely convergent, forming an evoluonary process consisng of four main stages.
The rst stage may be called ‘welfare euphoria’. This is a period of dynamic development of
the welfare state that goes hand in hand with rapid economic growth. Implementaon of
welfare programmes is based on trust and high moral standards in society. The control system
is praccally non-existent.
The second stage may be called a ‘grace’. This period usually coincides with an economic crisis
and scal restricons. The problem of welfare abuse is then noced. The policy-makers implement
a pioneer control system. First inspecons show that the problem of abuse concerns the most
vulnerable. The dominant rhetoric is that fraud is forced by a dicult life situaon and is an act
Ł. Jurek: The Use of Digital Technology in the Fight Against Welfare Fraud... 29
of higher necessity in order to sasfy basic existenal needs. Control measures have a negave
social recepon, being idened with cricism of the welfare state and the punishment of
poverty. In addion, the low cost-eecveness of control acvies is emphasised, i.e. the
potenal gains from the detecon of abuse are usually lower than the costs of the administrave
measures taken. Moreover, the eecveness of the control system is limited by poor instuonal
coordinaon and lack of access to informaon.
The third stage may be called ‘consternaon’. This is when reports appear from public instuons
and/or the media about various cases of benet abuse. These are oen examples of arrogant
and perdious exploitaon of the welfare system. The issue is publicised in the mass media and
becomes a popular polical and journalisc topic. Aenon is drawn to organised criminal
acvity against the system. Fraud is equated with the, and priority is given to prevenng and
combang this problem. Policians make honest aempts to esmate the extent of abuse and
its costs (social and nancial). The infrastructure for monitoring and combang social security
fraud is being put in place: sta are being recruited and given powers, special monitoring and
control instuons are being set up, legislaon is being adapted, and sancons are being made
more severe. However, many of these are ‘shotgun’ measures, as they are taken blindly and
intuively, without a proper understanding of the nature of the problem.
The fourth (last) stage can be described as the ‘surveillance welfare state’. In this case,
monitoring and control acvies are established as a natural public task. A systemac and
organised diagnosis of the problem is carried out (a reliable diagnosis using scienc
methods and techniques). Supervision and control acvies are digised, automated and
computerised. Modern technologies increase the cost-eecveness of control acvies.
The integraon and coordinaon of acvies within dierent instuons takes place in
order to eecvely combat fraud.
2.4. Digital Welfare Surveillance in Selected Countries
The idea of digital surveillance is based on the logic of risk in detecng non-compliances. The
point is that in welfare systems (especially social assistance) it is necessary to monitor the
situaon of beneciaries on an ongoing basis. At the very beginning, when people apply for
a benet, their identy, social situaon and ‘means’ (income, assets) need to be veried. Then,
aer the benet has been granted, connuous monitoring must be maintained in order to
detect changes that may aect the eligibility status of beneciaries. Naturally, there is no
juscaon for checking everyone who uses welfare benets as it would require a huge
administrave eort. Besides, a signicant proporon of beneciaries do not commit fraud.
Controlling them would be a simple waste, and instead it is advisable to select the cases that
require special aenon. To achieve this goal, policy makers are developing tools that calculate
the risk of fraud. Such measures are based on complex stascal models that make it possible
to idenfy (ag) those with an above-average risk and refer them for inspecon. The computer
programmes employ large databases containing informaon on various aspects of life. This
data is analysed using algorithms and (to some extent) machine learning (arcial intelligence).
On this basis, surveillance targets people with certain characteriscs that are predicted to
become involved in incorrect payments (Henman & Marston, 2008).
So far, several countries have implemented such risk-based system to detect welfare fraud,
with others already working at an advanced stage on such soluons. One of these countries is
Slovenia, where the SURVEILWEL project is being implemented with EU funding, which
Knowledge and Digitalisaon Against Corrupon and Fraud 30
will employ qualitave, mul-sited ethnographic eldwork to scrunise the realm of digital
welfare surveillance within Slovenian instuons […]. The project explores how digital welfare
surveillance tools impact welfare eligibility assessments and the invesgaon of suspected
fraudulent acvies. Moreover, its objecve encompasses the development of ecient
intervenons for social and material welfare. (Horizon Europe, 2033)
Similar acvies are also taking place in Sweden. In 2024, the country’s government set up
a special commission to study the possibilies of increasing digitalisaon in the area of social
security, primarily to prevent fraud, but also to ensure a more personalised service and
streamline the processing of benet claims (Sveriges Riksdag, 2024).
To date, the Netherlands had the broadest experience in using digital technology to combat
welfare fraud. Since the 2000s, data from a variety of sources have been used to idenfy
potenal abuses. One example was the ADM system, which used informaon from households
on registered water consumpon to compare it with the number of declared residents. In the
following years, fraud invesgaon became a major applicaon of ‘public sector data analycs’
(Zajko, 2023). As a result, three algorithmic fraud risk detecon systems were successively
implemented, rst ‘Waterproof’ (2004-2007), then ‘Black Box’ (2008-2014) and most recently
‘SyRI’ (since 2015).
SyRI (for ‘System Risk Indicaon’) was described by Van Bekkum and Zuiderveen Borgesius
(2021, p. 325) as ‘a socio-technical infrastructure’. It was designed to idenfy potenal welfare
fraud by generang risk nocaons and sending alerts to administrave bodies. Individuals
are shortlisted and agged as those at high risk of fraudulent behaviour’ by idenfying
discrepancies in their personal data. The system cross-referenced almost all the informaon
the government has on its cizens, relang to: employment, penales and convicons, taxes,
assets, denial of benets, residence, identy, integraon, compliance with the law, educaon,
pension, reintegraon, debts, welfare benets, permits and exempons, and health insurance
(Wieringa, 2023).
SyRI operates on the basis of the ‘black box method’. The system downloads some informaon
about welfare beneciaries and then analysis it using a certain algorithm. However, neither
the sort of data used, nor the risk assessment model remained unknown for a general public
(Van Bekkum & Borgesius, 2021).
From the outset, SyRI has been the subject of much controversy. In parcular, it has been
accused of a lack of transparency in the ow of informaon used. Claimants were not informed
what kind of data, even sensive data, was being used. The system of risk reporng was also
unknown. Decisions were made automacally on the basis of a blind vericaon mechanism
(using pseudonymised data). However, claimants were not warned that they had been agged
as a fraud risk and were not told why they had been agged. There was also cricism that SyRI
was only being used in selected communies, known as ‘problem neighbourhoods’, i.e. those
with high rates of poverty, crime and unemployment. It was perceived by the general public as
an element of vicmisaon and discriminaon that should not be sanconed by the law. Based
on these arguments, in 2018 several civil rights organisaons led a lawsuit against the Dutch
state to stop the use of SyRI. In 2020, the court ruled that neither the legislaon on SyRI nor its
use met the requirements of Arcle 8 of the European Convenon on Human Rights. A fair
balance had not been struck between the public interest in detecng fraud on the one hand
and the human right to privacy on the other. As a result, SyRI was found to be unlawful
(Rachovitsa & Johann, 2022).
Ł. Jurek: The Use of Digital Technology in the Fight Against Welfare Fraud... 31
Another country with a relavely rich experience of digital surveillance is Australia, where
welfare governance has been transformed into a paternalisc concept of welfare for several
decades; the 2007 reform introduced a pioneering income management system called BasicCard.
It allows welfare recipients to buy only ‘essenal’ items (food, fuel, clothing, rent payments,
etc.), and avoid purchasing prohibited products (alcohol, tobacco, pornography, etc.) (Dee,
2013). Moreover, the Australian government has a ‘zero tolerance’ policy towards welfare non-
-compliance. Prevenve measures were targeted in parcular at ‘welfare overpayments’. The
point is that in Australia, as in many other countries, eligibility for welfare support is linked to
nancial situaon. An increase in income may reduce eligibility for benet. However, informaon
about earnings does not ow to the welfare agency in real me and it is the responsibility of the
individual to report any changes in this regard. If they fail to do so (for whatever reason), they
may receive more support than they are entled to and become debtors.
To eliminate this problem, in July 2016 the Department of Human Services (currently known
as Services Australia) implemented an Online Compliance Intervenon (OCI) programme,
commonly known as Robodebt (welfare debt recovery system). It was intended to verify
eligibility to welfare benets without an excessive human-resources burden. The system drew
data from two dierent sources: social welfare data on benet payments (from Centrelink),
and tax data on earnings reports (from the Australian Taxaon Oce). Informaon on earnings
was matched with informaon on received welfare benets. The system automacally detected
discrepancies between the two. On this basis, an algorithm idened ‘suspected’ welfare
recipients and issued them with debt noces (Rinta-Kahila et al., 2022).
Robodebt has been cricised for inaccurate assessments, illegality, shiing the burden of proof
of debt onto welfare recipients, poor support and communicaon, and coercive debt collecon
(Braithwaite, 2020). Thus, in 2017, within a year of its implementaon, it came under scruny
by public bodies, while at the same me, acvists from non-governmental organisaons began
to raise awareness of the system’s shortcomings. The entrenched problems with the scheme
connued unl a legal challenge led the government to suspend the system in 2019 (Rinta-
-Kahila et al., 2024).
2.5. Conclusions
The digital transformaon of the welfare state is a dynamic process taking place in various areas
of infrastructure, management, contact with cizens, service delivery, and control and
monitoring. However, the experience gained so far in implemenng digital surveillance does
not inspire opmism. The examples of the Netherlands and Australia, where the process is
most advanced, revealed a number of crical problems. This is not to say that the projects have
not worked at all and should be enrely abandoned. At this stage, the problems must be treated
as challenges. In order to overcome these problems and advance the digitalisaon process, the
systems need to be adapted to the surrounding condions (legislaon, infrastructure, social
atudes) and, conversely, the surrounding condions (legislaon, infrastructure, social
atudes) also need to be changed and (to some extent) adapted to the system.
The rst crucial problem is transparency. Digital surveillance is accused of lacking clear
informaon about the construcon of the algorithm, i.e. the method of data analysis. The
system operates as a ‘black box’. The general public does not know what data is collected, how
it is analysed and what factors are crucial for idenfying non-compliance.
Knowledge and Digitalisaon Against Corrupon and Fraud 32
This problem should be addressed as a queson of dominant values in the public sphere
what is more important, transparency or eecveness? Clear criteria for decision-making
appear to be at the heart of government accountability and administrave jusce, however
the clarity of assessment rules raises concerns about feedback reacons on behalf of those
subject to control. The situaon can be compared to the ght against trac oences. Eecve
surveillance requires a conspiratorial approach so that drivers do not know when or where
they will be checked, otherwise they will temporarily change their behaviour and drive
according to the rules for a while, only to commit oences at a later stage. One can be sure
that the same is true for welfare fraud. Making the control criteria known to the public triggers
a behavioural reacon, i.e. adjustment to these criteria. Potenal oenders may mimic certain
features just to cheat the algorithm and reduce the risk of being ‘agged’ as a fraudster.
Freedom of informaon is at odds with the eecveness of the surveillance system. It is
therefore necessary to reach a consensus on how and to what extent control is to be carried
out. Auding should ensure clear principles of risk calculaon on the one hand and eciency
of control on the other.
The second crucial problem is operaonal performance. To date, the predicve validity of risk
assessment tools has been very low. Failure to detect welfare fraud has led to various negave
consequences, such as human tragedies (deprivaon, aggression, divorce), as well as a decline
in public trust in the instuons of the state. However, it should be clearly stated that the fault
for these errors is allegedly not with the system but with the human who developed it. The
algorithms were merely ‘decision trees’ that esmated the risk based on the data provided
and the criteria adopted. A sarical scene from the Polish comedy Miś [Bear] comes to mind
here, where one of the characters (a collecon agent) comments on the use of a computer: “it
will always make a mistake when adding, sir. Not a month goes by without it making an error.
This is, of course, a humorous approach to the subject of digitalisaon. In reality, the problem
is not the technology per se, but the ‘input’, i.e. the quality of the stascal model and the
assumpons on which the algorithm is based. The human factor sll plays a dominant role
here.
Risk assessment tools are already used in various areas of the welfare state. Abuse detecon
is no excepon. Algorithms and arcial intelligence will play an increasingly important role,
whether we are in favour of it or not, therefore an appropriate atude should be adopted.
The failures made so far should not be seen as a ‘warning’ about the use of digital technology
in government, but as an important lesson to be learnt. Systems, by denion, require
connuous progress by eliminang errors and adapng to changing external realies. Inial
failures cannot invalidate the whole soluon, but rather highlight the need for modicaon
and improvement.
According to Zajko (2023), digital transformaon only replaces human bureaucrats by
autonomous machinery. Digital technologies are designed to replicate the decisions made by
people in the analogue world. They automate the decision-making process based on parameters
and constraints set by humans. Wrong decisions are therefore the result of wrong assumpons.
In addion, the role of the algorithm is to calculate an individual’s risk score based on an
assessment of a dataset of people claiming benets, in order to idenfy those who are most
likely to be fraudsters. The problem is that this is a very complex issue. The propensity to
commit welfare fraud is condioned by personal and contextual factors. Many of these are not
obvious and are sll poorly recognised. For this reason, it is extremely dicult to create an
algorithm that eecvely predicts human behaviour.
Ł. Jurek: The Use of Digital Technology in the Fight Against Welfare Fraud... 33
Therefore, at the current stage of development, digital technology should only be treated as
a tool to support the decision-making process. Algorithmic governance should take a hybrid
form, with humans making the nal decision on cases that have been algorithmically agged
for scruny.
The third crucial problem is the issue of personal data protecon. To be eecve, digital
surveillance systems need to access various databases, including sensive ones, without the
knowledge or consent of welfare recipients. It is claimed that such scruny violates the right
to privacy. However, as noted by Henman and Martson (2008), such arguments are based on
ideas of personhood and social governance inherited from the early days of western modernity.
They presented three assumpons for data-based surveillance. Firstly, concerns about privacy
are predicated on a liberal ideal of personal property and personhood an independent,
raonal, self-updang human being. Yet in a world of growing interdependence and collecve
desny, the right to be le alone is outdated. Secondly, the noon of privacy is based on
a dichotomy of public and private responsibility, which is problemac from the perspecve of
a welfare state where the boundary between the two is unclear. Thirdly, the image of
surveillance is changing, from an omnipresent panopcon-style vision to the tracking of
a person’s data (‘dataveillance’).
Following the rhetoric of today’s researchers and praconers, one gets the impression that
too much aenon is being paid to the problems and limitaons of digital transformaon and
not enough to its potenal benets. Technology not only facilitates exisng acvies, it opens
up new possibilies. The digitalisaon of the welfare state allows for more individualised and
dierenated decisions, thus opening up a wider path for condionality in social policy (Szatur-
-Jaworska, 2023). This process rests (at least in principle) on three fundamental values:
eciency, integrity and transparency (Alston, 2019).
It may seem that digitalisaon is an inevitable path. Welfare states must undergo this
transformaon, otherwise they will not exist. The queson, then, is why does the development
of digital surveillance meet with such resistance in society? It is associated with ‘disciplining’,
‘punishing’ or ‘criminalising’ (Fenger & Simonse, 2024), however welfare surveillance is in fact
nothing new as controls have been carried out for a long me. Henman and Martson (2008)
argued that digitalisaon re-congures the nature of surveillance. It concentrates the power
and capacity of authories to assert norms, monitor behaviour and enforce compliance.
It means that the form of the relaon between the cizen and the welfare state is changing,
but not its content.
There are many other serious concerns about digital transformaon, such as high costs,
underdeveloped infrastructure and e-exclusion. From a historical perspecve, however, these
problems are only technical details. First of all, digital transformaon should not be seen as
a cost but as an investment that will bring tangible benets in the future. As for e-exclusion,
this is a general problem that needs to be solved, not just in the welfare sector. In addion,
techno-pessimists oen stress the problem of the ‘dehumanisaon’ of social policy. Such an
argument of ‘digital rigidity’ concerns the lack of empathy between the state and the cizen
(Ranchordás, 2022). Paradoxically, this feature is seen by techno-opmists as the main
advantage of digital surveillance. Computer algorithms and big data are culturally constructed
as accurate, objecve and true, and there is no room for subjecve discreon. Simple
compliance with the law, and no excepons to the rules. If someone does not meet the
eligibility criteria, the computer always says “No” (Henman, 2022).
Knowledge and Digitalisaon Against Corrupon and Fraud 34
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Chapter 3
Exchange of Experience in the Use of Digital
Procurement Tools to Prevent Corruption in the
Public and Business Sectors in Ukraine and V4
Oleksiy Poburko
Associate Professor of the Department of Finance, Lviv Polytechnic Naonal University
ORCID: 0000-0002-9140-4099
Nataliya Synyutka
Associate Professor of the Department of Finance, Lviv Polytechnic Naonal University
ORCID: 0000-0002-4294-2149
Pavlo Horyslavets
Associate Professor of the Department of Finance, Lviv Polytechnic Naonal University
ORCID: 0000-0002-1882-2104
Andriana Mazur
Associate Professor of the Department of Finance, Lviv Polytechnic Naonal University
ORCID: 0000-0002-5985-5674
Oksana Kurylo
Associate Professor of the Department of Finance, Lviv Polytechnic Naonal University
ORCID: 0000-0003-0366-0648
© 2024 Oleksiy Poburko, Nataliya Synyutka, Pavlo Horyslavets, Andriana Mazur, Oksana Kurylo
This work is licensed under the Creave Commons Aribuon-ShareAlike 4.0 Internaonal License.
To view a copy of this license, visit hp://creavecommons.org/licenses/by-sa/4.0/
Quote as: Poburko, O., Synyutka, N., Horyslavets, P., Mazur, A., & Kurylo, O. (2024). Exchange of Experi-
ence in the Use of Digital Procurement Tools to Prevent Corrupon in the Public and Business Sectors
in Ukraine and V4. In P. Luty, N. Versal, & P. Semerád (Eds.), Knowledge and Digitalisaon Against Cor-
rupon and Fraud (pp. 36-44). Publishing House of Wroclaw University of Economics and Business.
DOI: 10.15611/2024.96.3.03
3.1. Introduction
The problem of corrupon is, without exaggeraon, relevant for all countries of the world.
Some economists even compare it to an addional tax for businesses and cizens. This arcle
discusses the problems of corrupon risks in public procurement in Ukraine, the measures
taken by Ukraine to adapt its legislaon to the EU legislaon, and a comparison of key public
procurement indicators in Ukraine and the Visegrad countries.
O. Poburko et al.: Exchange of Experience in the Use of Digital Procurement Tools... 37
Corrupon as a phenomenon exists in the vast majority of countries around the world. As the
founder of reforms, not only economic, in Georgia and Ukraine, Kakha Bendukidze, claimed,
corrupon does not arise on equal grounds. It requires the coincidence of three factors: lack
of control over ocials, moral juscaon of corrupon, craving for quick and easy money.
Ukrainian representaves of the internaonal non-governmental organisaon, Transparency
Internaonal, added another factor – the total concealment of informaon (Khmara, 2014).
According to the World Bank, public procurement accounts for an average of 13 to 20% of GDP.
Global procurement spending is esmated at almost USD 9.5 trillion, and according to the
United Naons Oce on Drugs and Crime, between 10 and 25% of the total value of
a government contract can be lost to corrupon. Governments have a strong incenve to
maximise every penny of their budgets, which should be spent transparently and eciently
(World Bank, n.d.).
Digitalisaon, opening of registers, and simplicaon of access are among the key aspects of
public procurement reform in Ukraine and other European countries.
Thanks to the obligaon to publish procurement plans in the public domain, hundreds of
tenders that contained both signs of corrupon and mismanagement have been cancelled in
Ukraine, which has prevented billions of hryvnias from being wasted and most of them stolen
before the procurement announcement.
The Naonal Agency for Corrupon Prevenon of Ukraine idened the following corrupon
risks in public procurement, under maral law (NACP, n.d.):
1) conducng an open tender with only one tender oer;
2) possibility to submit tender oers at a price higher than the expected value;
3) increase in the purchase price as a material term of the contract;
4) abuse of procurement through an electronic catalogue;
5) corrupt pracces through direct contracts;
6) inconsistency of decisions of the appeal body (lack of established/generalised pracce);
7) impossibility to appeal against decisions, acons or omissions of procuring enes during
procurement procedures, including simplied ones;
8) problems with enforcement of decisions of the appeal body and courts;
9) restricons on the rights of parcipants in the course of consideraon of complaints by
the Anmonopoly Commiee of Ukraine;
10) other (non-price) criteria for evaluang proposals;
11) the use of ‘arcial obstacles’ in procurement to favour a parcular parcipant.
In the authors’ opinion, similar risks are inherent in procurement in other countries, including
the European Union and the Visegrad Four. This is conrmed by data from the stascal oces
of the respecve countries.
For example, in Slovakia, the e-procurement system has been in place since 2015, and in 2021,
32.3% of public procurement procedures were completed through the modernised electronic
public procurement system, resulng in contracts that accounted for 46.9% of the monetary
value of procurement (UVO, 2022).
The digitalisaon of public administraon, and not only in the area of public procurement, is
a priority area of development in most countries. The transion to the use of services and data
in electronic format can signicantly simplify me-consuming processes and services, reduce
administrave costs of the authories, eliminate corrupon and increase the compeveness
Knowledge and Digitalisaon Against Corrupon and Fraud 38
of procedures in order to save money. The digitalisaon of public administraon includes the
area of electronic public procurement, which actually opens up procurement data of indivi-
dual business enes to the public and signicantly simplies tender processes for bidders
through the use of automated calculaons and the electronic submission of the necessary
documentaon.
In the process of reforming its public procurement legislaon, the government of Ukraine has
been paying aenon to the standards set by EU direcves in order to meet the requirements
of the Associaon Agreement with the EU and increase the eciency of the public sector.
It is important to note that Ukrainian and EU public procurement legislaon have a common
ulmate goal to ensure the economic eciency of public procurement and transparent
tenders.
According to the OECD Public Governance Brieng Papers Public Procurement Performance:
A Framework for Measuring Eciency, Compliance and Strategic Objecves (OECD, 2023),
public procurement accounts for 13% of GDP in OECD countries. The pressure on public
spending, as well as the need for greater accountability, beer monitoring of public policies
and more eecve risk management, make it increasingly important to measure public
procurement performance. However, many countries have not yet established a formal
performance management system with key performance indicators.
Moreover, the relevant EU legislaon is designed to regulate much more complex relaons
than Ukrainian legislaon currently regulates, primarily due to the deeper standardisaon
of procurement procedures in the EU. In this regard, the authors claried the priority areas
of development of legal support for the funconing of the naonal public procurement
management system. In parcular, they substanated the expediency, taking into account the
provisions of Direcve 2014/24/EU, of changing the concept of ‘customer in the current
legislaon of Ukraine on public procurement, introducing new rules for lling in tender
documents and tender procedures and announcements, updang the procedures for
compeve dialogue and negoaons with several parcipants, expanding the pracce of
maintaining electronic catalogues, and regulang the rules of sub-threshold procurement.
The authors also argued for the expediency of enshrining a new principle of proporonality of
procurement for budgetary funds at the legislave level, regarding Arcle 36 of Direcve
2014/25/EU.
3.2. Exchange of Experience in the Use
of Digital Procurement Tools
The study then compared some procurement indicators of Ukraine and the Visegrad countries
obtained from open sources, for example taking in consideraon the gures for 2021, given
that in 2022, Russia’s aack on Ukraine dramacally changed both the volume and nature and
transparency of public procurement. The number and volume of procurements of goods and
services for naonal defence has increased dramacally in Ukraine, and due to the
circumstances, the vast majority of them are classied.
In 2021, the share of public procurement in Ukraine’s GDP was 17%. The ocial website of the
Polish Central Stascal Oce stated that in 2021, the value of public procurement contracts
concluded with the applicaon of the provisions of the Public Procurement Act was PLN 184.6
O. Poburko et al.: Exchange of Experience in the Use of Digital Procurement Tools... 39
billion in 2021 (PLN 183.5 billion in 2020), approximately 7.04% of gross domesc product
(GDP) in 2021.
In Hungary, the share of public procurement was 16.4%, in Slovakia 12.4%, and in the
Czech Republic 14.1% (European Court of Auditors, 2023). Hence, this concerns large
amounts of money that belong to fellow cizens, who, in turn, have the right to understand
how they are used.
A report by the EU Court of Auditors (European Court of Auditors, 2023) stated that in 2021,
‘no call for tenders’ accounted for about 15.8% of all procurement procedures in the EU
single market reported by Member States on Tenders Electronic Daily. The Chamber’s
analysis also showed that the share of direct contracts varied across EU member states. In
2021, the average rate of direct contracts ranged from 3.1% (Greece) to 42.3% (Cyprus),
indicang signicant dierences in public procurement pracces among EU Member States.
Some of them reduced the use of direct contracts during the reporng period (e.g. Germany),
while others remained stable (e.g. Ireland), or signicantly increased the use of direct
contracts (e.g. Cyprus). An absence rate of more than 10% is considered a red ag, and in
2021 most Member States (23 out of 27) fell into this category, including three Visegrad
countries Hungary, Poland and the Czech Republic. In case of Ukraine, this gure was
higher.
It should be noted that the problem of public procurement has been studied in economic
science for a long me.
From the historical point of view, the discourse on the funconing of the public procurement
instuon in the global economy began in the works of well-known internaonal economists,
such as Keynes, Buchanan, Sgler, Owen, Pey, Pigou, and others, yet their studies did not
take into account the innovave impact of digital technologies on public nance.
Public expenditures are posioned in the works of Heller as an objecve component of the
scal space (Kravets et al., 2021), and the need for their implementaon follows from the
postulates of the theory of public welfare.
Fischer postulated the interdependence of public expenditure with the development of society.
In his opinion, public spending in certain areas, such as telecommunicaons and road
infrastructure, contributes to economic growth and accelerate social development (Fisher, 1997).
Besley & Persson emphasised that budgetary resources spent on public projects means
expenditure on public goods and corrupon rent-seeking, which are already included in the
price of public goods by interested individuals or groups. Scholars stressed the value of
digitalisaon for intervenons in procurement processes in order to reduce corrupon and
increase the ecient ow of budget expenditure to end users (Besley & Persson, 2013).
Joined iniave of OECD and EU (SIGMA Support for Improvement in Governance and
Management) has focused research on facilitang access to public procurement markets for
small and microbusinesses (SMEs) in the European Union through the approval and
implementaon of the relevant EU Direcves in 2014. In SIGMA view, electronic procurement
systems are a crucial tool for engaging SMEs in public consumpon. EU legislaon removes the
barriers that oen hinder SMEs and requires that tools and devices are also used for electronic
communicaon. Their technical specicaons must be non-discriminatory and easily accessible
(Sigma, 2016).
Knowledge and Digitalisaon Against Corrupon and Fraud 40
The work of German sciensts Eßig & Glas explored the impact of dividing public contracts into
smaller batches as a tool for aracng small businesses to public procurement. The main
message of the study was that increased compeon has a posive impact on the success of
SMEs in public procurement, and that the involvement of SMEs increases the innovaon and
exibility of the proposed soluons (Eßig & Glas, 2015).
Some scholars studied the methodology of successful bidding, for example, Plećić et al. (2018)
proposed a mul-criteria methodology for selecng the opmal soluon from the submied
bids within the tender.
Kolosok, Panchenko and Iordanov analysed the state of achievement of long-term goals set
during the reform of the ProZorro procurement system in Ukraine. They studied the level of
corrupon, transparency and accessibility, as well as reliability, eciency and elascity of the
public procurement system aer the introducon of the ProZorro system, and idened
systemic problems in the procurement process and outlined areas for improvement in Ukraine.
In parcular, the decentralised procurement system in Ukraine causes dierences in the
ltering and delivery of announcements to tenderers registered on dierent trading plaorms.
Legislave inconsistency in customer support and the variety of trading plaorm requirements
may lead to unequal opportunies for business parcipants, which worsens compeon in
the procurement market. According to the authors, the number of non-compeve tenders
has increased since the introducon of ProZorro. This situaon may be caused mainly not by
defects or problems of ProZorro, but by improper performance of the funcon of controlling
bodies (Kolosok et al., 2017).
Ukrainian researchers pay considerable aenon to the problems of organising and managing
the public procurement system through the prism of European experience. Miniailo and
Kostenko (2016) systemised the relevant public procurement procedures. The above
publicaons analysed in detail the EU direcves, in parcular, on public procurement of goods,
public procurement of works, and public procurement of services. Ukrainian experts
emphasised that at one me, these documents created the necessary legal basis for the
development of eecve systems of procurement acvies for budgetary funds, but now their
provisions are already outdated to some extent, and some provisions are unclear and rather
contradictory. As a result, there is sll no coherent vision of the prospects for implemenng
and harmonising Ukrainian legislaon with EU direcves on public procurement management.
This signicantly complicates the process of reforming this management system in our country.
In view of this, the purpose of the arcle is to analyse the provisions of EU legislaon on public
procurement management and to clarify the priories for the development of legal support
for their implementaon in Ukraine.
There is diversity of public procurement procedures in certain EU countries.
The level of development of electronic public procurement in EU countries is determined by
the use of electronic data processing methods at dierent stages of the bidding process, these
include:
e-Sourcing – collecng informaon about potenal suppliers and contacng them;
e-Nocaons – publicaon of nocaons and informaon about the start of trading in
electronic format;
e-Tendering divided into e-Access (providing all necessary informaon on tender
documents and standards with the possibility of feedback) and e-Submission (subming
a proposal in electronic format);
O. Poburko et al.: Exchange of Experience in the Use of Digital Procurement Tools... 41
e-Evaluaon evaluaon of tenders for compliance with the criteria set by the government;
e-Contract – the conclusion of a contract between tenderers;
e-Order – placing an order in electronic format;
e-Invoicing – issuance of an invoice (waybill) in electronic format in accordance with the
standards of the Direcves;
e-Payment – payment by the customer for goods, works and services received (Prałat,
2019).
The introducon of full digitalisaon of the public procurement cycle in the EU was planned by
2018: electronic publicaon of procurement noces was to become mandatory by 2016;
electronic submission of proposals through the central procurement authority by 2017;
submission of electronic proposals by 2018 and mandatory e-invoicing by 2019 (Tkachenko,
2016).
Table 3.1 shows the level of digitalisaon (modernisaon) of the public procurement process
in some EU countries in 2019.
Table 3.1. Modernisation of the public procurement process in selected EU countries in 2019
EU country
The state of digitalisation of the e-procurement process
E-Alerts E-Access E-Submission E-Assessment &
E-Contract E-Order E-Invoicing
Austria + + + + + +
Belgium + + + + + +
Greece
Italy + + + + + +
Germany + + + + +
Poland + + + +
Slovakia + + + +
Hungary + + + + +
Finland + + +
France + + + + +
The Czech Republic + +
Sweden + + + + + +
Source: (Tkachenko, 2016).
Therefore, the level of digitalisaon of the procurement process in each EU country is dierent.
For example, in Austria and Belgium in 2019, the enre procurement process was conducted
electronically; in some G7 member states (Italy, Germany and France), e-tendering was almost
fully modernised, except for the e-invoicing stage in Germany and France. In Greece, as of
2019, there was no digitalisaon of public procurement as such, which may be partly explained
by its economic situaon, whilst in the Visegrad countries (Poland, Slovakia, the Czech Republic
and Hungary), the digitalisaon process is unevenly developed.
The organisaon of electronic public procurement in EU countries also diers. For example, in
the Czech Republic a bidder must be registered either in the state-owned Tender Portal (NEN)
or in one of the private plaorms FEN (which oers addional services for a fee). In Hungary
Knowledge and Digitalisaon Against Corrupon and Fraud 42
there is a single plaorm, EKR, which is managed by the Oce of the Prime Minister of Hungary.
Up to now, Slovakia used ISEVO (Modernised Informaon System for Electronic Procurement),
while other paid resources exist (Karlin, 2021). Dierences are also manifested in the models
of payment for services by e-plaorms: in Portugal, the service fee is charged from tenderers,
while in other countries it is the tenderers who pay for registraon in the plaorm and further
parcipaon in the tender (Tkachenko, 2016).
Each EU country can independently determine the lower limit of procurement at the naonal
level. For example, the Czech Republic and Poland have only one threshold, while Hungary has
several above-threshold levels for naonal procurement (Karlin, 2021).
In most EU member states, centralised procurement organisaons operate, which reduce the
costs of bidding for procurement parcipants and save me on the enre procurement process.
In Hungary, procurement through them is mandatory for central-level public instuons, while
in Poland there is no such organisaon at the state level (Karlin, 2021).
One of the parcular characteriscs of Slovakia in the eld of public procurement is that it is
one of the rst countries to develop legislaon for the introducon of ‘green procurement’, i.e.
clear criteria for the availability of environmental cercates and the use of environmentally
friendly producon processes have been established (Karlin, 2021).
In order to determine the specics of public procurement legislaon at naonal level, it is
worth considering the state of public procurement in Poland due to economic and polical
similaries with Ukraine. The legislave regulaon of public procurement in Poland was
reformed by the adopon of the Public Procurement Act of 11 September 2019, which came
into force on 1 January 2021. The purpose of this reform was to increase the role of strategic
procurement (generally related to the already menoned environmental, social and innovaon
goals), the aracveness of the public procurement market for the private sector and the
creaon of eecve communicaon between sectors of the economy (Kania, 2023).
In Poland, several government agencies are responsible for controlling public procurement.
The Polish Supreme Chamber of Control usually conducts post-contract procurement control.
A separate central execuve body is the Public Procurement Agency, which conducts both
scheduled and unscheduled document inspecons of tenders and analyses the procurement
bullen data. If a contracng authority disagrees with the Agency’s conclusions, the Appeals
Chamber makes the nal decision. Public procurement is also monitored by the Oce for the
Protecon of Compeon and Consumer Rights in terms of collusion (Kania, 2023).
According to the Criminal Code of the Republic of Poland, the submission of false documents
or false statements in order to obtain a public procurement order is punishable by imprisonment
for a term of 3 months to 5 years. There is also a penalty for collusion with other bidders
(Ustawa z dnia 6 czerwca 1997…).
In 2020, around 94% of contracts in Slovakia were awarded on the basis of the lowest price
alone. This is signicantly higher than the EU average of 64% and limits compeon based on
quality. It also reduces the possibility of using public procurement strategically to support
other policies, such as green, social and innovaon. In addion, the professional services
sector remains highly regulated.
To sum up, the supranaonal standards set out in the EU Public Procurement Direcves dene
the key requirements that each Member State must comply with when applying above-
-threshold procurement, while below-threshold procurement is carried out in accordance with
O. Poburko et al.: Exchange of Experience in the Use of Digital Procurement Tools... 43
the laws of a parcular country using its own mechanisms and models of organising the tender
process, provided that they are harmonised with the Direcves.
3.3. Conclusions
The chapter conrms the thesis that corrupon is a major problem in most countries of the
world, as evidenced by the stascs of internaonal organisaons. Taking into account the
volume of public procurement and its share in GDP, the state, its cizens and instuons
should comprehensively monitor the eciency of spending taxpayers’ money. In fact, electronic
public procurement is an important element of protecng the interests of taxpayers and
transparency of public procurement. The chapter shows that Ukraine and the Visegrad
countries have many similaries in their approaches to public procurement, although each
country is at dierent stages of implemenng digital public procurement systems.
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share-compare-improve
Chapter 4
New Forms of Non-Standard Employment
and Fighting Shadow Economy
Antonina Sholoiko
Taras Shevchenko Naonal University of Kyiv
ORCID: 0000-0003-1239-4281
Vasyl Erastov
Taras Shevchenko Naonal University of Kyiv
ORCID: 0000-0001-5230-0273
© 2024 Antonina Sholoiko, Vasyl Erastov
This work is licensed under the Creave Commons Aribuon-ShareAlike 4.0 Internaonal License.
To view a copy of this license, visit hp://creavecommons.org/licenses/by-sa/4.0/
Quote as: Sholoiko, A., & Erastov, V. (2024). New Forms of Non-Standard Employment and Fighng
Against Shadow Economy. In P. Luty, N. Versal, & P. Semerád (Eds.), Knowledge and Digitalisaon Against
Corrupon and Fraud (pp. 45-56). Publishing House of Wroclaw University of Economics and Business.
DOI: 10.15611/2024.96.3.04
4.1. Introduction
The global economy is undergoing a massive transformaon, and with it, the tradional
boundaries of employment are being redrawn. New forms of work interacons are emerging,
and many businesses are shiing to alternave work arrangements, such as working from
home, temporary employment, part-me or on-call work, digital labour plaorms, mul-party
employment, disguised employment, etc. These changes are mainly caused by labour
globalisaon, shiing to digitalised communies, and technological changes worldwide.
Standard forms of employment are facing signicant compeon, especially in some specic
industries suering from the downsides of tradional employment models. Full-me
employment, as the basic tradional form, has a lot of drawbacks when it comes to creavely,
technologically, or intellectually rich spheres of human acvies. Employee potenal cannot
be eecvely ulised by seng addional work me and workplace boundaries. Moreover, it
should be menoned that intellectual capital is mostly transferred, and geng a specic
mindset and experse in a tradional way can be costly, in terms of relocaon, and dicult, in
terms of legislave aspects, or simply impossible, in terms of condions or other factors.
Shiing to non-standard forms of employment can be benecial for both employers and
employees, while some formal boundaries are neglected. Ease of geng necessary specialists,
higher salary rate, bigger employment pool, and signicant improvement in results are
considered as the main benets of non-standard forms of employment over those tradional,
while ignoring their considerable downsides such as hidden work relaons, taxaon
opmisaon, and avoidance, lack of social responsibilies, etc.
Knowledge and Digitalisaon Against Corrupon and Fraud 46
To prevent taxaon violaons by ulising new forms of non-standard employment, dierent
approaches can be used. The Ukrainian labour market provides many examples of how to shi
hidden employment relaons towards other forms, less destrucve and opaque for taxaon.
Some measures can be used as a rule of thumb, while some need to be ‘tweaked’ before
implementaon. A thorough study of the current Ukrainian situaon and the overall idea of
non-standard forms of employment can provide signicant insights for both controlling enes
and employers worldwide.
The research aim was to consider main non-standard forms of employment and create
recommendaons for ghng the shadow economy in Ukraine.
This purpose was achieved due to the realisaon of the following: generalising pros and cons
of the main non-standard forms of employment, and creang recommendaons for ghng
the shadow economy in Ukraine.
4.2. Forms of Non-Standard Employment
Many forms of non-standard employment can be now considered new because of the strong
inuence of the digitalisaon processes. Thus, the rst form is working from home. Due to the
Internet and the impact of Covid-19 pandemic, many types of jobs were transformed and
nowadays most of them are available to work from home remotely, which is especially
convenient for women, allowing to combine work with housekeeping.
The Internaonal Labour Organizaon (ILO) explains that working from home is
long associated with labour-intensive, repeve work in the industrial sector (“industrial
homework”), it also encompasses higher-skilled workers on digital labor plaorms, as well as
remote workers (teleworkers) in service industries. […] The ILO esmates that while not all
occupaons can be done at home, many could – approximately one in six at global level, and
just over one in four in advanced countries. (ILO, 2020)
Working from home oers signicant advantages, including me savings by eliminang
commutes, reduced transport expenses, and the exibility to adapt work schedules to personal
needs. However, the me saved oen gets redirected to addional work or household chores,
liming personal benets. It also encourages a sedentary lifestyle, increases health risks, and
can weaken communicaon skills and team-building abilies due to reduced in-person
interacon. Balancing these pros and cons is crucial for maximizing the benets of remote
work (ILO, 2020).
One of the posive sides is me saving. According to the study by Aksoy et al. (2023):
the average daily me saved when working from home was 72 minutes – in this sample. Work
from home saved about 2 hours per week per worker in 2021 and 2022. Workers allocated 40%
of their me saved to their jobs and about 11% to caregiving acvies. People living with
children allocate more of their saved me to caregiving.
As for Ukrainians, negave consequences of remote work include: a decrease in producvity,
dicules due to everyday factors, overme; among the advantages are: a less-busy schedule,
me saving and the ability to work from anywhere (Kochmar-Tymoshenko, 2021).
One can conclude that working from home is characterised by a high level of informality, and
as a result tax avoidance can take place. Thus, to ght the shadow economy in Ukraine, it is
A. Sholoiko, V. Erastov: New Forms of Non-Standard Employment and Fighng Shadow Economy 47
possible to work from home ocially and pay taxes if employers have a distance or hybrid
model of working. However, for independent professionals it is necessary to smulate them to
register as a sole proprietor (SP) (Table 4.1).
Table 4.1. Sole proprietor: groups of single taxpayers
Type
of SP
Hired
workers Annual income
Cooperation
with legal
entities
Rate of the single tax
Single social
contribution
(SSC)
Reports
I
less than
UAH 1 185 700
per year
10% of the subsistence
minimum = UAH
302.80 per month
22% of the
minimum
wage
monthly
declaration
II or less
than 10
workers
less than
UAH 5 921 400
per year
+
20% of the minimum
wage = UAH 1420 per
month
22% of the
minimum
wage
monthly
declaration
III or
unlimited
less than
UAH 8 285 700
per year
+
3% or 5% of income 22% of the
minimum
wage
quarterly
declaration
IV unlimited + from 0.09% to 1.8% of the normative
assessment of the land
annually
Source: compiled by the authors based on (DtKt, 2023; Kosht, 2023).
Table 4.1 shows that dierent types of sole proprietors are based on dierent sizes of individual
business with the appropriate rate of the single tax. Moreover, it is also possible to parcipate
in social insurance and obtain a basic level of social protecon in cases if social risk occurs.
The next form of non-standard employment is temporary employment, divided into xed-
-term, project- or task-based contracts and casual work (Figure 4.1).
Temporary employment – whereby workers are
engaged only for a specific period, includes:
Casual work
Fixed-term, project
or task-based contracts
Fixed-term contracts (FTCs) have always
existed in labour markets and serve specic
purposes. They provide exibility to enter-
prises to respond to changes in demand,
such as due to seasonal uctuaons, to
replace temporarily absent workers, or to
evaluate newly hired employees before
oering them an open-ended contract. Yet,
beyond these tradional reasons, some
enterprises have come to rely heavily on
FTCs, hiring workers recurrently on these
contracts for permanent tasks of the
company.
Fixed-term contracts (FTCs) have always existed in labour
markets and serve specic purposes. They provide
exibility to enterprises to respond to changes in demand,
such as due to seasonal uctuaons, to replace tempo-
rarily absent workers, or to evaluate newly hired
employees before oering them an open-ended contract.
Yet, beyond these tradional reasons, some enterprises
have come to rely heavily on FTCs, hiring workers
recurrently on these contracts for permanent tasks of the
company.
It is also essenal to provide equal condions of work to
workers in temporary employment as compared to
workers in standard employment.
Fig. 4.1. The concept of temporary employment
Source: compiled by the authors based on (ILO, 2016a).
Knowledge and Digitalisaon Against Corrupon and Fraud 48
Temporary employment oers exibility, allowing individuals to combine it with a full-me job
and gain addional income. However, it comes with the risk of temporary unemployment and
uncertainty. Workers in temporary roles may face unequal condions compared to standard
employment, such as limited opportunies for skill development and lower social protecon.
Balancing these factors is crucial when considering temporary work arrangements (ILO, 2016a).
In Ukraine, temporary employment is oen considered by workers not as posive choice, but
as forced necessity. According to sociological studies, 8% of Ukrainians rate their chances of
nding a job in the region where they live as “good”, almost 15% – as “not bad”. Such indicators
show that Ukrainians are ready to leave their homes in search of earnings. However, they do
this not only by going abroad, but also by migrang within the country. Oen, labour migraon
in Ukraine has a temporary and seasonal nature (Legalaid, 2020) (see Table 4.2).
Table 4.2. The difference between seasonal and temporary work in Ukraine
Seasonal work Temporary work
Jobs, which, due to natural and climatic conditions,
can be performed only during a certain period
(season), but not more than six months (for
instance: agriculture).
After the end of the seasonal work, the employees
who were employed are dismissed on the basis
of the termination of the employment contract –
the end of the term. In this case, the last day of
seasonal work is considered the day of dismissal.
If the employee continues to work after the end
of the seasonal work or the duration of such work
exceeds six months, the employment contract with
this employee is considered to be concluded for an
indefinite period.
Such jobs can be accepted by an employee for a period
of up to two months, and to replace temporarily absent
employees, for whom their place of employment is kept,
for up to four months. The list of temporary jobs has not
been established, but the employee must be warned in
writing form that he will work temporarily. The employer
must confirm the circumstances that make it impossible
to conclude an employment contract with the employee
for an indefinite period.
The employment contract of temporary employees is
considered to be extended for an indefinite period if the
employment relationship continues after its termination
and none of the parties wants to terminate it.
Source: compiled by the authors based on (Legalaid, 2020).
Thus, seasonal and temporary works are also characterised by high level of informality. If these
forms of employment are based on xed-term contracts, then everything is legal, and taxes
are paid, whereas in the opposite case it is necessary to:
increase labour literacy as for the rights of workers (within school curriculum as
“Entrepreneurship and nancial literacy<