Technology Improving Safety of Crowdfunding Platforms Functioning in the Context of the Protection of the Start-Up Investors in the Financial and Transport Sectors

Abstract

The information technology models improving security functioning of crowdfunding platforms and advice on a new type of business were developed. The article solves the problem of safety of crowdfunding platform functioning based on developed models: rating assignment system of unified assessment crowdfunding platforms; startup projects assessment; startup projects risk assessment concerning their financing safety level and criminal law protection of investors against the financial fraud. The models are based on the correct usage of fuzzy logic and fuzzy set device to reveal the uncertainty of experts’ consideration that insures authenticity of scientific results.

Full text

Journal of KONBiN 49(2019)
e-ISSN 2083-4608
DOI 10.2478/jok-2019-0016
313
Volodymyr POLISHCHUK1, Miroslav KELEMEN2, Jarosław KOZUBA3
1 Uzhgorod National University
2 Technical University of Košice
3 Silesian University of Technology (Politechnika Śląska)
TECHNOLOGY IMPROVING SAFETY OF
CROWDFUNDING PLATFORMS FUNCTIONING IN
THE CONTEXT OF THE PROTECTION OF THE
START-UP INVESTORS IN THE FINANCIAL
AND TRANSPORT SECTORS
Abstract: The information technology models improving security functioning of
crowdfunding platforms and advice on a new type of business were developed. The article
solves the problem of safety of crowdfunding platform functioning based on developed
models: rating assignment system of unified assessment crowdfunding platforms; startup
projects assessment; startup projects risk assessment concerning their financing safety level
and criminal law protection of investors against the financial fraud. The models are based
on the correct usage of fuzzy logic and fuzzy set device to reveal the uncertainty of experts’
consideration that insures authenticity of scientific results.
Keywords: crowdfunding platform; safety; risks; criteria, expert evaluation; protection of
interests
1. Introduction
Today's experience shows that millions of people, who had nothing in common
with investing, can invest money in start-ups and their economy. “Observing the
development of a large number of start-ups, it is clear that using modern technology
one can find a good alternative to lending” [13].
Crowdfunding ‒ is investing in a start-up that is performed by a lot of people,
including micro investors and business angels.
Crowdfunding has a great potential. In general, in every country there is a huge
amount of money which are not used. Usually, a particular average person has not

Volodymyr Polishchuk, Miroslav Kelemen, Jarosław Kozuba
314
enough spare cash to think about the traditional investment. People do not invest a
small amount of money but waste it. The world economy can get much more if
small amounts of spare cash come in the development of the economy through
crowdfunding platforms. If there are more funded start-ups, there are more work
places, products and services they created.
Therefore, there is urgent primary task of improving the safety of
crowdfunding platforms. It needs to be solved systematically by developing new
models of information technology and the introduction of a reasonable law
regulation and distribution of business [11] especially in the transport sector [14].
The secondary task is to strengthen the criminal protection of investors in the start-
up projects, which also do not avoid financial fraud. These aspects are not in line
with the further safe and sustainable development of society, and required
protection of interests. “Security and law-based research generally points to the
"struggle" with the technical and the anti-social phenomena, which is complex,
lengthy, demanding but socially necessary for the healthy, sustainable and
sustainable development of a democratic society: state security and citizen security,
protection of fundamental human rights and freedoms and other protected interests”
[8]. There exist a wide range of scientific studies proving that the present
understanding of human safety and security consists of several dimensions which
might not be directly linked only to actual war activities but to ensure the security
of protected interest [2, 4, 5, 10].
2. Formulation of the issue
The work is aimed to develop a model of increasing the security of crowd
funding platforms. The development is based on eliminating the disadvantages of
this type of investment. It is necessary to develop a model of information
technology and legal advice on a new type of business. The model will improve the
safety of platforms that will encourage the popularization of modern business and
implement new technologies.
What specific research questions are being tackled? For the first time the model
of rating assignment system of unified assessment crowdfunding platforms; For the
first time criminal law protection of investors against the financial fraud was
systematized and outlined; mathematical model of information technology for
reducing the fraud risk of startup projects which are presented at the platform
related to their financing safety level was improved; further development of
recommendation concerning reducing of commonly known investment
disadvantages by using crowdfunding platforms was obtained.

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315
The main disadvantages of crowd funding are:
1. “The risk of fraud: possibly, under the guise of start-up pyramid scheme
gathers the capital or the platform itself is created for phishing scams.
2. The risk that the required amounts of investments will not be collected and
the project will not be implemented.
3. The risk that the project will be unprofitable and closed, and the investment
will be lost.
4. In many cases, crowdfunding schemes do not correspond to the legislation of
the country, which does not allow to resolve the disputes in court in fairness.
5. Unprofitability - many platforms are closed soon after they were opened.”
(https://simex.bz/about, http://crowdconsulting.ru).
There is a direct correlation between platform safety level, the submitted
projects and the number of investments made. Therefore, it is necessary to develop
scientific approaches to eliminate the disadvantages of crowdfunding that will
improve the safety level of modern investment platforms.
3. The purpose and objectives of the study
The purpose of the paper is the development of technologies improving safety
of crowdfunding platforms functioning within the “fight” against the financial
fraud. Provided we want to protect a subject (a certain interest) in an effective way,
we have to study and research the subject, its surroundings and the relationships
among them [7, 9].
To reach the aim of the research it is necessary to solve the following problems:
– to give recommendations to eliminate the disadvantages of this type of
investment,
– to develop a mathematical model of information technology to reduce the
risk of fraud in start-ups presented; on the platform regarding the level of
security of its funding,
– to create a rating system model of the crowdfunding platforms in order to
reduce the risk of fraud.
4. Methodology and what is novelty
Research methods. To solve the given task we used methods of system
analysis; theory of fuzzy set in the construction of the model for risk assessment of
startup projects and uncertainty disclosure and increase in authenticity of expert

Volodymyr Polishchuk, Miroslav Kelemen, Jarosław Kozuba
316
consideration; multicriterion evaluation methods to build a model of rating
assessment of crowdfunding platform.
Scientific novelty of the results. In the work solved the problem of applied
scientific development of the fraud risk reducing model in startup projects and
crowdfunding platforms that in conjunction is a safety improvement technology of
crowdfunding. Based on the theoretical and practical research, the following results
were obtained:
For the first time the model of rating assignment system of unified assessment
crowdfunding platforms based on aggregated assessment of platform owners’,
integrated risk assessment related to security level of project financing, aggregated
investors’ assessment and evaluation of realized projects success were developed.
For the first time criminal law protection of investors against the financial
fraud was systematized and outlined; mathematical model of information
technology for reducing the fraud risk of startup projects which are presented at the
platform related to their financing safety level was improved; further development
of recommendation concerning the reducing of commonly known investment
disadvantages by using of the crowdfunding platforms was obtained.
5. Technology improving safety of crowdfunding platforms
functioning
5.1. Recommendations for reducing the disadvantages of
crowdfunding investment
The first disadvantage is the risk of fraud.
Either platform that attracts investment in non-existent projects or start-ups
presented in the form of pyramid scheme can turn out to be scammers. Therefore,
it is necessary to reduce the risks of fraud. The main tools for platform security are:
– Accreditation – the platform must meet the legal requirements, to be
registered and obtain a state license.
– Rating System - unified evaluation obtained on the basis of characteristics
system. These indicators may include the assessment of platforms owners;
the rating of start-ups; the estimation of investors; the indicators of
successful performance.
Rating of platform should be assigned automatically while in operation and
updated in real time. The metrics of ranking must be dynamic. It is necessary to
develop a mathematical model to calculate the rating and information technology.

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317
The main means of safety improving and reducing the risk of fraud for start-
up projects are the following:
– Evaluation of start-ups to selection them for the platform to prevent access
of fraudulent pyramid schemes to the platform. "Evaluation model of start-
ups in case of information uncertainty" described in can be used to assess
start-ups.
– Development of a mathematical model of information technology of risk
assessment start-ups relating to safety of their financing, using fuzzy math.
Development of technologies of this type will enable us to consider the projects
adequately, to increase the validity of investments decisions, and to increase
economic and management security. This will allow to evaluate projects that are
registered on the platform. Investors will be able to make informed investment
decisions.
Increasing of platform security is possible with the help of its accreditation and
rating system that will be displayed on the website, and assess of start-ups and their
risk related to security funding level.
The disadvantages described in chapter 2 points 2-3 can be solved as follows.
The platform should enable an investor to resell its investment in secondary trading.
If there is a need to send back their investments before the launch of the project, or
on the contrary to maximize profits at the peak of popularity of the project, it should
be possible to sell the investment share in secondary trading. Therefore, the
successful sale of investment shares allows to make an additional profit. The
platform should be able to refund. In case the investment project did not assemble
the declared amount of money, the investments should be sent back into investor's
account without platform commissions.
Point 4 should be solved systematically developing legislation for a new type
of IT maintenance business that has great prospects. Laws should be simple, clear
and start-ups and investors supporting. Investors should not be afraid to be unable
to bring their investments into projects during the successful launch phase. And
“the start-uppers” have to be sure that in case of successful project launch the
investors will not get their business. There should be a clear law that governs
modern business and prevents fraud.
If disadvantages described in points 1-4 are solved systematically, the
unprofitability of platforms is automatically reduced.

Volodymyr Polishchuk, Miroslav Kelemen, Jarosław Kozuba
318
5.2. Mathematical model of risk start-up assessment concerning the
funding safety level
Let us develop a two-level mathematical model of information technology
enabling each start-up on the platform to establish a start-up risk assessment of the
project realization, on which the safety level of its future funding depends.
Let us offer our last experience based on the previous work [12] and for
example [1] the next set of start-up risk assessment criteria on which the platform
can assess risks of start-ups. There are four groups of criteria:
O
K
– «operational
risk»;
I
K
– «investment risks»;
F
K
– «financial risks»;
S
K
– «risks of innovation».
Let us present each group of criteria as a set parameters. For instance, a «risks
of innovation» criteria -
S
K
is expressed using indicators:
1
S
K
– risk of inefficient
innovative investments;
2
S
K
– risk of inefficient innovation promotion;
3
S
K
– risks
of terms disruption of innovation design;
4
S
K
– risks of technology innovation;
5
S
K
–
the risk of resource deficiency in innovation design.
Each risk criteria is evaluated by experts with one of the terms of the following
term-set of linguistic variables
{ }
; ;; ;LН НС С ВС В=
, where: Н – «low
risk level»; НС – «risk level below average»; С – «average risk level»; ВС – «risk
level above average»; В – «high risk level».
Also, an expert puts the number of «authenticity» for each assessment of risk
level
()
L
µ
of his consideration concerning the interval [0; 1]. Thus, the input data
for risk assessment projects of different origins can be presented in tables by the
following criteria risk groups (tab. 1).
Table 1
The input data by the criteria risk groups
Group criteria’s Linguistics variable Accuracy of expert considerations
1
K
α
1
L
α
1
()L
α
µ
2
K
α
2
L
α
2
()L
α
µ
…
…
…
m
K
α
m
L
α
()
m
L
α
µ
Where
{ }
;; ;OIFS
α
=
– one of the risk criteria group,
, 1,
i
Ki m
α
=
– і-indicator
of risk group criteria,
i
L
α
– indicator of term-set
L
for і-indicator of the group
α
,

Technology improving safety of crowdfunding platforms...
319
()
i
L
α
µ
– the accuracy of expert considerations concerning appropriation of variable
i
L
α
corresponding value.
Let us describe two-level mathematical model of projects risk assessment
based on the input of linguistic variables. It’s necessary to make up rules of the
knowledge base belonging to get the resulting term-evaluation
L
α
for each risk
criteria group on the first level. On the basis of the resultant term assessment
L
α
let
us define the aggregated estimate of reliability
()L
α
µ
. At the second level on the
basis of the estimates
L
α
and
()L
α
µ
let us make a project risk assessment for each
group of criteria
α
.
Consider the first level – building of association rules of resulting term
assessment by risk criteria group.
Level Н – «low risk level». The minimum amount of criteria with low risk level
term should not be less than 60% and the remaining 40% of the criteria should not
have terms lower than «risk level below average».
Level НС – «risk level below average». The project should have the minimal
amount of criteria with the term «risk level below average» not less than 60%, and
the other 40% of criteria should have terms not lower than the «average risk level».
Level С – «average risk level». The minimal amount of criteria with the term
«average risk level» not less than 60%, and the other 40% of criteria should have
terms not lower than the «risk level above average».
Level ВС – «risk level above average». The minimal amount of criteria with the
term «risk level above average» not less than 60%, and the other 40% of criteria
should have terms not lower than the «high risk level».
Level В – «high risk level». The project gets the resulting term-evaluation «В»
in case the amount of criteria with the term «high risk level» compiles 60% and
more.
A know ledge base is built based on accessory rules of the resulting term-
evaluation due to the risk criteria groups.
Since the expert gives every
i
L
α
variable the authenticity he considers –
()
i
L
α
µ
from interval [0; 1], than linguistic variables can be presented as triangular
membership functions according to Kofman, A. 1983. In this case every linguistic
L
variable can be replaced with the next
*
L
with authenticity
*
()1 ()LL
µµ
= −
.
That makes it possible to draw out all the possible variants of the expert risk
assessment with the help of the membership rules of the resulting term-evaluation.
The aggregated authenticity estimation
()L
α
µ
,
{ }
;; ;OIFS
α
=
is calculated
with the following formula:

Volodymyr Polishchuk, Miroslav Kelemen, Jarosław Kozuba
320
1
1
() (),
m
i
i
LL
n
αα
µµ
=
=
∑
{ }
;; ;OIFS
α
=
, (1)
Where
()
i
L
α
µ
– is the authenticity estimation of the linguistic variables which
match the resulting term-evaluation for і-criterion of
α
risk criteria group;
n
– is
their amount.
Thereby, the resulting term-evaluation for every risk criteria group of a project
based on membership rules and the aggregated authenticity estimation is obtained
on the first level (1).
The aggregated risk estimation and its linguistic interpretation concerning the
safety of investing in start-ups is obtained on the second level.
Since the resulting term-evaluation
L
α
contents risk level, its terms can be
adequately determined on the percentage scale (0-100%), where each one is given
the value on the interval
[;]ab
. For instance, ”Н” – [0; 20], ”НС” – [20; 40], ”С”
–[40; 60], ”ВС” – [60; 80], ”В” – [80; 100]. The risk of 90% is interpreted as
«high risk level».
The relation between the resulting
L
α
term-evaluation and its authenticity
()L
α
µ
will be seen as a S-shaped membership function. As the membership
function values (the aggregated risk estimation) and the intervals of numerical
values for
L
are defined, for every criteria group
α
,
x
α
is deduced from the general
formula of the S-shaped membership function:
()
( ) , 0 ( ) 0.5;
2
1 ()
( ), 0.5 ( ) 1.
2
Lba a L
x
L
b ba L
αα
α
αα
µµ
µµ
−+ ≤ ≤


=−
− − <≤


(2)
To get the generalized risk evaluation of the start-up project for the criteria
group
α
the following formula is used:
100
x
z
α
α
=
(3)
The evaluation
z
α
is normalized. It presents the aggregated risk estimation of
the start-up concerning the resulting term-evaluation and its authenticity for every
criteria group
α
.
Let us calculate the aggregated risk estimation for all criteria groups
α
:

Technology improving safety of crowdfunding platforms...
321
1(1 )
4
R
Oz
α
α
= −
∑
(4)
The gained estimation
R
O
is normalized. To compare it with the output
variable
R
the following scale is suggested:
1
r
= «negligible risk level of start-up and high level of its funding safety»;
2
r
= «low risk level of start-up and the level of its funding safety above average»;
3
r
= «average risk level of start-up and average level of its funding safety»;
4
r
= «high risk level of start-up and low level of its funding safety»;
5
r
= «extreme risk level of start-up and extremely low level of its funding safety».
The linguistic interpretation of the aggregated risk estimation
12345
{,,,,}R rrrrr=
is defined by the following scale:
R
O∈
(0,77; 1] –
1
r
;
R
O∈
(0,57;
0,77] –
2
r
;
R
O∈
(0,36; 0,57] –
3
r
;
R
O∈
(0,21; 0,36] –
4
r
;
R
O∈
[0; 0,21] –
5
r
.
The model of creating the aggregated risk estimation of a start-up uses the
expert consideration and considerations, based on the result, are aggregated in the
final estimation by the criteria groups.
5.3. The model of crowdfunding platform rating estimation
For the rating appropriation system of the unified estimation to work it is
necessary to develop a mathematical model of its calculating on the website of the
crowdfunding platform. Such rating model should be standardized for
crowdfunding platforms at least within the state. Investors and start-uppers should
have the complete analytical and rating information about the platform.
The model of the task is formulated as follows:
1234
(, , , )EK PR PR PR PR PR=
(5)
where:
1
PR
– aggregated estimation of the platform wrens,
2
PR
– in targeted risk estimation concerning the project’s funding safety level,
3
PR
– aggregated estimation of investors who worked on the platform,
4
PR
– success estimation of the realized projects,
EK
– output rating and linguistic estimation of the crowdfunding platform,
P
R
– operator that makes the output
EK
variable corresponding to input
estimations
1234
,,,PR PR PR PR
.

Volodymyr Polishchuk, Miroslav Kelemen, Jarosław Kozuba
322
A set of criteria in the form of expert questions is suggested to get platform
owners aggregated evaluation. Also appropriate tonal estimates range is described.
Platform owners answer the questions and choose the most appropriate option.
1
P
K
– Platform holders comprehensive income in the last 12 months?:
1. $0 - $24 999 (5 points);
2. $25 000 - $99 999 (20 points);
3. $100 000 - $249 999 (25 points);
4. $250 000 or more (30 points).
2
P
K
– Platform owners business experience level is achieved due to?:
1. lack of business keeping knowledge (5 points);
2. successful small business launch (15 points);
3. working as co-founders or co-workers in a successful high-tech
company (20 points);
4. there is the founder of several successful companies among the
owners (30 points).
3
P
K
– The owners are experienced in IT or investment market occupying
executive positions in the branch?:
1. none of the owners is (5 points);
2. less than 2 years (15 points);
3. 2-5 years (20 points);
4. has an experience for over 5 years (30 points).
4
P
K
– The number of scientists working on a platform development full time
for at least three months?:
1. none (5 points);
2. a group of 1-3 (15 points);
3. a group of 3-5 (20 points);
4. more than 5 (30 points).
5
P
K
– The number of sales / marketing development / business experts working
to promote the platform full-time for at least three months?:
1. none (5 points);
2. a group of 1-3 (15 points);
3. a group of 3-5 (20 points);
4. more than 5 (30 points).
6
P
K
– The authorized capital of crowdfunding platform is?:
1. $0 - $24 999 (5 points);
2. $25 000 - $99 999 (20 points);
3. $100 000 - $249 999 (25 points);
4. $250 000 or more (30 points).

Technology improving safety of crowdfunding platforms...
323
7
P
K
– Corporate attorney of platform is:
1. the lawyer with only a law degree (5 points);
2. a small local firm (10 points);
3. a medium sized company, which operates in the investment area
(20 points);
4. a nationally recognized corporate law firm with a lot of connections
in the venture community (30 points).
The following scale for the answers scores is heuristic and characterizes the
level of the platform owners. The more points there are, the more trust the platform
and its owners have. For each criterion the platform and its owners correspond to
one of the answers to which the corresponding scores assigned. Let us define the
assessments convolution, such as the amount of tonal range answers points divided
into the amount of maximum points:
7
1
17
max
1
,
i
i
i
i
b
PR
b
=
=
=∑
∑
(6)
where:
i
b
- scoring by the i-criterion,
max
i
b
- maximum scoring by the i-criterion,
1
PR
- normalized aggregate assessment of the platform owners.
To get an integrated risk assessment regarding the project funding security
level let us use the following formula:
2
R
O
PR d
=∑
(7)
where:
R
O
– start-up risk assessment (described in the previous point),
d
– a number of start-ups on a platform.
The next step is building of an aggregated assessment of investors working
with a platform –
3
PR
.Thus, let us sum up the assessment of the presence of the
following subject son the platform:
1. Venture fund which is a part of the top 20 global investors (0,4points).

Volodymyr Polishchuk, Miroslav Kelemen, Jarosław Kozuba
324
2. Worldwide-known business angels (0,3 points).
3. Large national investment firms (0,2 points).
4. National-known business angels (0,1 points).
3
PR
assessment obtained by summing the number of points will be
normalized. Of course, such concepts as "top 20" or "known business angels" are
fuzzy. A knowledge base, which is based on the world rankings, should be created
to build up a computer information technology based on the proposed model. It has
to be updated every time when new rankings are published.
To get
4
PR
‒ the assessment of accomplished project success the following
formula is suggested:
44
4
4
, 1,
1, 1.
RR
PR R
<

=≥

(8)
where:
*
4
0
k
Rn
=
,
*
k
– the amount of projects on the platform which raised the start-up
budget and got the investments,
0
n
– the amount of projects which didn’t raise the start-up budget.
At this point, let us build about going rating and linguistic assessment of
crowdfunding platform
EK
. If an expert defines weight coefficient
{ }
1234
,,,wwww
of an interval. Normalized weight coefficients should be defined as follows:
4
1
1, 4, 1.
i
ii
i
i
i
w, i
w
αα
=
= = =
∑
∑
(9)
Let us use the following formula to rate the scoring:
4
1
.
ii
i
PR PR
α
=
= ⋅
∑
(10)
The obtained
PR
assessment is set from the interval [0;1], the following scale
is suggested to compare it with its outgoing variable
EK
:
1
ek
= «very high platform
rating»;
2
ek
=«high platform rating»;
3
ek
=«sufficient platform rating»;
4
ek
=«speculative platform rating»;
5
ek
=«very low platform rating».

Technology improving safety of crowdfunding platforms...
325
The linguistic explanation of the aggregated risk assessment
12345
{,,,,}EK ek ek ek ek ek=
is defined as follows:
PR ∈
(0,87; 1] –
1
ek
;
PR ∈
(0,67; 0,87] –
2
ek
;
PR ∈
(0,36; 0,67] –
3
ek
;
PR ∈
(0,21; 0,36] –
4
ek
;
PR ∈
[0;
0,21] –
5
ek
.
How did we select criteria for experts? Are criteria we suggest somehow
related to good/bad practices of crowdfunding? Based on analysis and practical
experience, the set of criteria for obtaining the unified rating assessment of
crowdfunding platforms was given and the set of criteria for startup projects risk
assessment was suggested. The sets of criteria are heuristic and they can be
supplemented when needed. Information technology models do not depend on the
number of criteria. Therefore, the number of criteria does not affect the work of
developed models and increase in their number during the technology
implementation leads to more accurate estimates.
Thus, the building model of the crowdfunding rating assessment is given. The
program realization of the models hold gets the information from the platform and
should be its inseparable addition. It gives the opportunity to assign the platform
rating based on the dynamic indicators in real time.
6. Criminal law protection of investors against the financial
fraud
The authors of start-up projects may commit the unlawful actions, such as the
fraud that intentionally causes the damage. The damage under the Criminal Code
means the damage to property or actual loss of property or the rights of the victim
or other harm that is related to a criminal offense, whether damage to property or
rights.
The damage may be caused to an investor who may be a natural person or a
legal entity. In the case of drawing funds from different funds, it may also be a
grant, subsidy or start-up project contribution, and so on. Subsidiary fraud can be
committed at the national level, or the offender may commit a crime of damaging
the interests of the European Union, and so on. Such actions are primarily among
the crimes against the property.
The criminal law protection of property rights is regulated primarily in the
Fourth chapter of the Special part of the Criminal Code, but also on the basis of
Art. 20 sec. 1 of the Constitution of the Slovak Republic no. 460/1992 Coll.,
According to which everyone has the right to own property. The property rights
and interests are also protected in some other headings of the specific part of the

Volodymyr Polishchuk, Miroslav Kelemen, Jarosław Kozuba
326
Criminal Code, such as the economic, generally dangerous and environmental
crimes. The laws protect not only tangible property but also intangible property.
The Criminal Law Theory classifies crimes against property (§ 212 - § 249a)
into three groups:
1. Crimes that are associated with the unauthorized enrichment,
2. Crimes related to damage to the foreign property and property rights,
3. Crimes in which the booty from crimes are involved.
The group object of the fourth chapter of the Special part of the Criminal Code
is property rights, but also some other property rights and undisturbed possession
of the thing. The subject of the attack is usually an alien thing.
The factual nature of the crime of fraud is defined in the provisions of § 221
par. 1 of the Criminal Code:
"Whoever enriches himself or herself by causing anyone to mislead or mislead a
person to cause damage to another's property, causing minor damage to foreign
property, shall be punished by imprisonment for up to two years ... Deprivation of
liberty for ten to fifteen years The offender shall be punished if he commits the
offense referred to in paragraph 1 as a member of a dangerous group." [3].
An assessment of whether, in a particular case, all the constituent elements of
the offense are met by the law enforcement and, ultimately, the court.
§ 261 - § 263 of the Criminal Law "The Damage to the European Union's
Financial Interests" provides protection of the financial interests of the European
Union in the territory of the Slovak Republic in accordance with the European
Association Agreement concluded between the European Communities and their
Member States and the Slovak Republic dated 4.10.1993, Which entered into force
on 1.2.1995. Another important document in this area is the Convention on the
Protection of the European Communities' Financial Interests of 26.7.1995, the
Protocol to that Convention of 27.9.1996 and the Second Protocol to the
Convention of 19.6.1997.
The object of these crimes is to protect the financial interests of the European
Union and to harm the financial interests of the European Union “Core crimes”,
which by their very nature are most jeopardizing the interests of the European
Union and its citizens in relation to the threat to the four freedoms on which the
European Union is built.
The perpetrator of the crimes under § 261 and 263 may be anyone. The
perpetrator under § 262 may be only a managerial or controlling officer.
The subjective aspect of crimes under § 261 and 262 presupposes the
culpability in the form of intent and the crime in the form of negligence for a crime
under § 263.

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7. Results and discussion
The result of scientific research is the designed models of fraud risks reducing
in the start-ups and crowdfunding platforms. Altogether they build a safety
improving technology of the crowdfunding.
Is our model similar to existing one? Crowdfunding has a range of commonly
known disadvantages and their reducing can improve and develop new type of
business activity. The information technology models is a new ideological
approach that does not have analogue. The system solves the problem of safety of
crowdfunding platform functioning based on developed models: rating assignment
system of unified assessment crowdfunding platforms; startup projects assessment;
startup projects risk assessment concerning their financing safety level and criminal
law protection of investors against the financial fraud. The models are based on the
correct usage of fuzzy logic and fuzzy set device to reveal the uncertainty of
experts’ consideration that insures authenticity of scientific results.
Given recommendations of the weaknesses elimination in conjunction with the
developed technology are aimed at the encouraging of the crowdfunding business
promotion and development.
What formulations are valid now, what amendments are suggested?
Crowdfunding is a kind of very risky innovative business which needs development
and implementation of new assessment technology and fraud detection. Therefore,
let us suggest the following:
The disadvantages solving should be implemented carefully in order not to harm
the development of new business:
1. Laws must be simple (it means they should not be ambiguous), laws must be
clear and aimed at the start-ups support but protected the investors against the
financial fraud as much as possible too;
2. Accreditation of the crowdfunding platform should take place when it is
registered with the relevant authorities;
3. Platform rating should be assigned automatically, updated in real time and
displayed on platform site;
4. Start-ups evaluation and fraud risk assessment should be promulgated while
choosing the project.
Thus, the proposed improving safety crowdfunding platform technology has
many advantages, namely: mathematical information technology model of the
reducing the start-up project fraud risk increases objective expert estimates of
project risk assessment using the input linguistic variables and reliability of the
expert considerations concerning their assignment; makes it possible to change the
decision-making level in the knowledge base; brings together opinions by criteria

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328
groups in the final evaluation and risk degree of the project, based on the two-level
fuzzy mathematical model; the rating system of crowdfunding platform model can
evaluate the platform and give the linguistic interpretation of such evaluation using
a system approach of the platform owners, start-ups risks, investors and successful
projects.
The disadvantages of this approach include the use of different membership
functions models and convolution that leads to ambiguous results.
Platform owners can select the perspective projects for their customers, avoiding
the scams. Startups and entities, which wish to invest in them, will be able to choose
a platform on the rating level. This agenda can help ensure the security and
sustainability of the society's development, which is the subject of research by other
scientists for example [6, 15] etc.
8. Conclusions
The research of a crowdfunding platform functioning is conducted and the
technology of improving the security of investing in start-ups on the platform is
proposed. The following results were obtained:
– the recommendations on the elimination of five known crowdfunding
disadvantages are given, namely: fraud risks, legal risks, platform and
project unprofitability, non-investment of the required amount of money to
run the project;
– there is a developed mathematical model of information technology for
fraud risks reducing in start-up using expert arguments on assessments by
different risk criteria, reliability of its reasoning and based on the opinion
aggregation of criteria groups in the final evaluation;
– there is a created model of the crowdfunding platform rating system to
reduce the fraud risk. This model allows evaluating the platform and giving
a linguistic interpretation of such evaluation, aggregating considerations on
expert estimates: the platform owners; the project financing safety risk; the
investors working with a platform; the projects successfulness.
Thus, the technology of crowdfunding safety improving based on the model of
fraud risks reducing in the start-ups and platforms, as well as recommendations on
elimination of existing disadvantages, will be a useful tool for promotion of the
crowdfunding platforms activities and within the support tools against the financial
fraud in the financial and transport sectors too.

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