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APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION

December 2018
International Journal of New Economics and Social Sciences 8(2):12-14

DOI:10.5604/01.3001.0012.9925

Authors:

Sylwia Gwoździewicz

The Jacob of Paradies University, Gorzow Wielkopolski, Poland

Dariusz Prokopowicz

Cardinal Stefan Wyszynski University in Warsaw 🏛️

Jan Grzegorek

University of Warsaw

Martin Dahl

Uczelnia Łazarskiego

Currently, business analytics uses computerized platforms containing ready-made reporting formulas in the field of Business Intelligence. In recent years, software companies supporting enterprise management offer advanced applications of information-analytical Business Intelligence class systems consisting of modular development of these systems and combining business intelligence software with platforms that use data warehouse technology, multi-dimensional analytical processing software and data mining and processing applications. This article describes an example of this type of computerized analytical platform for business entities, which is included in analytical applications that allow quick access to necessary, aggregated and multi-criteria processed information. The software allows entrepreneurs and corporate managers as well as entities from the SME sector on the one hand to use embedded patterns of reports or analyzes, and on the other hand to self-develop and configure analyzes carried out, tailored to the specifics of a specific entity. Such analytical applications make it possible to build integrated risk management systems in the organization.

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International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

Sylwia Gwoździewicz 1)

Dariusz Prokopowicz 2)

Jan Grzegorek 3)

Martin Dahl 4)

1) PhD, Assistant Professor at the Department of Management

and Marketing, Lazarski University

(Warsaw, Poland)

* Corresponding author: e-mail: sylwiagwozdziewicz@gmail.com

ORCID: https://orcid.org/0000-0003-3034-2880

2) PhD Department of Journalism, Information and Bibliography,

University of Warsaw

(Warsaw, Poland)

* Corresponding author: e-mail: darprokop@poczta.onet.pl

ORCID: https://orcid.org/0000-0001-6383-916X

3) PhD, Department of Journalism, Information and Bibliography

University of Warsaw

(Warsaw, Poland)

* Corresponding author: e-mail: jan.grzegorek@o2.pl

ORCID: https://orcid.org/0000-0003-1106-6518

4) PhD, Assistant Professor at the Faculty of Economics and

Management, Lazarski University

(Warsaw, Poland)

* Corresponding author: e-mail: augwaw@gmail.com

ORCID: https://orcid.org/0000-0003-1978-7045

APPLICATION OF DATA BASE SYSTEMS BIG DATA

AND BUSINESS INTELLIGENCE SOFTWARE

IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION

ZASTOSOWANIE SYSTEMÓW BAZODANOWYCH BIG DATA

I APLIKACJI ANALITYKI BIZNESOWEJ W PROCESACH

ZINTEGROWANEGO ZARZĄDZANIA RYZYKIEM

W ORGANIZACJI

ПРИМЕНЕНИЕ СИСТЕМ БАЗ ДАННЫХ BIG DATA

И ПРИЛОЖЕНИЙ ДЛЯ АНАЛИЗА БИЗНЕС-ДАННЫХ

В ИНТЕГРИРОВАННОМ УПРАВЛЕНИИ РИСКАМИ

В ОРГАНИЗАЦИИ

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

Abstract

Currently, business analytics uses computerized platforms containing ready-made re-

porting formulas in the field of Business Intelligence. In recent years, software companies

supporting enterprise management offer advanced applications of information-analytical

Business Intelligence class systems consisting of modular development of these systems

and combining business intelligence software with platforms that use data warehouse

technology, multi-dimensional analytical processing software and data mining and pro-

cessing applications. This article describes an example of this type of computerized ana-

lytical platform for business entities, which is included in analytical applications that

allow quick access to necessary, aggregated and multi-criteria processed information.

The software allows entrepreneurs and corporate managers as well as entities from the

SME sector on the one hand to use embedded patterns of reports or analyzes, and on the

other hand to self-develop and configure analyzes carried out, tailored to the specifics of

a specific entity. Such analytical applications make it possible to build integrated risk

management systems in the organization.

Keywords: risk management, digitization of business processes, computerization of eco-

nomic analyzes, corporate finance, Big Data, Business Intelligence, Internet, integrated

risk management system

Streszczenie

Obecnie w analityce biznesowej wykorzystywane są zinformatyzowane platformy zawie-

rające gotowe formuły raportowania w zakresie Business Intelligence. W ostatnich latach

producenci oprogramowania wspomagającego zarządzanie przedsiębiorstwem oferują

zawansowane zastosowania informacyjno-analitycznych systemów klasy Business Intel-

ligence polegające na modułowej rozbudowie tych systemów i łączeniu oprogramowania

analityki biznesowej z platformami wykorzystującymi technologię hurtowni danych,

oprogramowaniem wielowymiarowego przetwarzania analitycznego oraz aplikacjami

eksploracji i przetwarzania danych. W niniejszym artykule opisano przykład tego typu

zinformatyzowanej platformy analitycznej dla podmiotów gospodarczych, która zalicza

się do aplikacji analitycznych umożliwiających szybki dostęp do niezbędnych, zagrego-

wanych i wielokryterialnie przetwarzanych informacji. Oprogramowanie to pozwala

przedsiębiorcom i menadżerom korporacji jak również podmiotów z sektora MSP z jednej

strony na korzystanie z wbudowanych wzorców raportów czy analiz, a z drugiej na sa-

modzielne opracowywanie i konfigurowanie przeprowadzanych analiz, dostosowanych

do specyfiki konkretnego podmiotu. Tego typu aplikacje analityczne umożliwiają zbudo-

wanie w organizacji systemów zintegrowanego zarządzania ryzykiem

Słowa kluczowe: zarządzanie ryzykiem, cyfryzacja procesów biznesowych, informatyza-

cja analiz ekonomicznych, finanse przedsiębiorstw, Big Data, Business Intelligence, In-

ternet, zintegrowany system zarządzania ryzykiem

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

Аннотация

В настоящее время в бизнес-аналитике используются компьютеризированные

платформы, содержащие готовые формулы отчетности. В последние годы

компании-разработчики программного обеспечения, поддерживающие управление

предприятием, предлагают передовые приложения информационно-

аналитических систем класса Business Intelligence, состоящие из модульной

разработки этих систем и объединения программного обеспечения для бизнес-

аналитики с платформами, использующими технологию хранилища данных,

многомерным программным обеспечением для аналитической обработки и

приложениями для анализа и обработки данных. В этой статье описан пример

компьютеризированной аналитической платформы этого типа для бизнес-

субъектов, которая включена в аналитические приложения, которые

обеспечивают быстрый доступ к необходимой, агрегированной и

многокритериальной обработанной информации. Программное обеспечение

позволяет предпринимателям и корпоративным менеджерам, а также

организациям из сектора МСП, с одной стороны, использовать встроенные

шаблоны отчетов или анализов, а с другой стороны, самостоятельно

разрабатывать и конфигурировать выполняемые анализы с учетом специфики

конкретной организации. Аналитические приложения такого типа позволяют

строить интегрированные системы управления рисками в организации.

Ключевые слова: управление рисками, оцифровка бизнес-процессов,

компьютеризация экономических анализов, корпоративные финансы, Интернет,

интегрированная система управления рисками

______________________________________________________________________

Article history: Received: 18.09.2018 / Accepted: 15.12.2018 / Published: 30.12.2018

JEL Classification: O 3, O 30, O 32

________________________________________________________________________________________

Statement of the problem in general outlook and its connection with important

scientific and practical tasks.

Rapid progress has been made in the field

of the use of computerized analytical Busi-

ness Intelligence platforms supporting

business management processes in recent

years. To the area of the fastest growing

fields of ICT, which support business man-

agement processes, belongs dissemination

of standards for the transfer of information

and carrying out financial operations in the

cloud as well as using the large data sets

located in the Big Data platforms. Current

Big Data technology solutions are not only

large databases, but data warehouses al-

lowing for multi-aspect analysis of huge

sets of quantitative data made for the pur-

poses of reports submitted periodically to

the managerial staff (Gwoździewicz S.,

Prokopowicz D., 2016a, p. 229-230).

Enterprises striving for market and busi-

ness success try to build their competitive

advantage by implementing new IT solu-

tions for their operations. One of the areas

of activity of companies and institutions

significantly affecting the efficiency of

their functioning is the issue of efficient

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

risk management in the context of the or-

ganization's management process. The is-

sue of improving the risk management pro-

cess has gained a new meaning in the con-

text of the global financial crisis that ap-

peared in autumn 2008. The specificity of

this crisis was its systemic char-acter and

the huge potential scale of bankruptcy of

many entities, including banks, insurance

companies and enter-prises (Domańska-

Szaruga B., Prokopowicz D., 2015, p. 37-

48). In the context of the discussed issue,

the issue of risk management is particularly

important, including the improvement of

integrated risk management systems using

currently available IT solutions.

Many studies show that the efficient use of

information technology and information

resources of an organization affects the

quality of decision making in the business

management process. Risk management

should be based on a prior analysis of reli-

able and up-to-date information about

counterparties, market data and business

activities (Prokopowicz D., 2014, p. 148 -

149). More and more companies and finan-

cial institutions use for this purpose busi-

ness analyzes conducted on IT platforms

offering Business Intelligence solutions

(Gendron M. S., 2014, p. 157).

It is assumed that the analyzes carried out

with the use of computerized Business In-

telligence applications make it easier for

managers to conduct real-time analyzes of

large data sets related to the company's op-

erations. Therefore, the dominant opinion

is that Business Intelligence solutions (An-

alizy BI, 2017) are becoming more and

more use-ful in organizational manage-

ment processes. Considering the analytical

and technological abilities of these appli-

cations, they are also well suited for build-

ing integrated risk management systems in

the organization. Integrated risk manage-

ment systems are also built in business or-

ganizations operating in Poland, mainly in

corporations and financial institutions

(Dmowski A., Prokopowicz D., 2010, p.

335). The process of building and gradu-

ally improv-ing these systems in Poland

began in the second half of the 90s.

The downside of the analytical processes in

enterprises is their time-consumption. In

addition, the scope of this time-consuming,

e.g. calculated by the number of analysts

and managers' work hours, may addition-

ally increase along with the increasing in-

formation resources collected on the Inter-

net. Experts in the global network issue es-

timate that the Internet information re-

source doubles in approximately every two

years. On the other hand, global-ly operat-

ing Internet companies such as Google or

Facebook in their Big Data bases (Mayer-

Schonberger V., 2015, p. 34) collect data

about Internet users in such a wide range

that they are not able to precisely predict to

what this collected information will be

used in 5 years. The Internet is not a static

medium, because online libraries and other

knowledge bases are rapidly changing and

increasing. Therefore, enterprises actively

using the opportunities offered by the In-

ternet in their activities should effectively

use the information resources contained in

the global network, taking into account the

dynamic nature of the variability of data

collected on the Internet (Surma J., 2016,

p. 57). The scope of the use of information

and technological possibilities of the Inter-

net by economic entities is constantly

growing and currently it is impossible to

determine the limits of this development.

More and more enterprises, financial and

public institutions define the Internet (in

the context of their business) as a medium

that can not be ignored. More and more or-

ganizations are observing the need to up-

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

date and process information on the Inter-

net and want to improve the Internet mar-

keting techniques (Wehbe B., Decker J.,

Alexander M., 2015, p. 62-63). Organiza-

tions use the information and technological

abilities of the global network in the con-

text of analyti-cal processes carried out in

the Business Intelligence formula, manag-

ers are making decisions on a base of these

processes (Radziszewski P., 2016, p. 43).

IT systems containing embedded analytical

applications that integrate most or all of the

business entity's activities have been built

since the 1990s in financial institutions, in-

cluding large commercial banks operating

in Poland. These systems, usually referred

to as integrated IT systems, combine many

activities of institutions, thus replacing

several independent applications operating

in different departments. As a result, insti-

tutions of the market financial system from

the end of the last century usually set key

trends in the development of ICT and the

construction of integrated IT systems.

However, in recent years, the issue of elec-

tronic transfer and processing of large data

sets is also increasingly applicable to other

types of entities, including non-financial

enterprises and public institutions, due to

the ongoing digitization of enterprises and

public institutions (Gwoździewicz S.,

2014, p. 74). The most dynamically devel-

oping fields of ICT technology (which de-

termine the successive stages of progress in

the field of internet data transmission) in-

clude the dissemination of data pro-cessing

standards in the cloud computing as well as

using the large data sets located in the Big

Data platforms (Libuda Ł., 2016, p. 17). In

connection with the above, a technological

revolution is currently underway, which

will allow for computerized integration of

many areas of analytical activity conducted

in organizations, including enterprises, fi-

nancial and public institutions. In recent

years, computerized analytical Business

Intelligence plat-forms and Big Data data-

base systems are used to improve processes

of business analysis and risk quantification

instruments.

Analysis of latest research where the solution of the problem was initiated.

The issues of the use of computerized Busi-

ness Intelligence analytics platforms and

data processing in Big Data database sys-

tems in integrated risk management pro-

cesses in economic entities described in the

present study were discussed in numerous

scientific publications by scientists operat-

ing in various scientific environments and

originating from various countries; these

issues have global character. The increase

in the interest of scientists in these issues

results from its timeliness and high level of

significance and from the growing im-

portance of Business Intelligence analytics

and data processing in Big Data database

systems. Through verification of opinions,

considerations, conclusions and research

theses contained in the cited publications

the main research aspects and the outline of

of supporting business entities manage-

ment processes with the use of information

processing in Big Data database systems

and computerized Business Intelligence

analytics platforms were formulated. Main

research aspects and the outline of the ana-

lyzed topic were used as the basis for de-

termining the objectives and research

methods used in this study. The aims of pa-

per and research methods are presented in

the next section of this article. The basis for

these main components of the research pro-

cess that was carried out in this study was

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

to define a synthetic image of the problem

of management support in business entities

by using information processing in Big

Data database systems and computerized

Business Intelligence analytics platforms

after collecting analytical data and verify-

ing the conclusions contained in the quoted

publications. Prior to the research, collect-

ing and developing research results on var-

ious aspects of the issues of supporting

business entity management processes

through the use of computerized Business

Intelligence analytics platforms and infor-

mation processing in Big Data database

systems, the authors of this study have re-

viewed the literature on the above-men-

tioned issues. Determining and specifying

the research problem, which was then char-

acterized and analyzed in this article, was

preceded by a review of the publications in

which key issues were Business Intelli-

gence and Big Data. The review of the lit-

erature shows that the topic of Business In-

telligence and Big Data applications in the

company management process described

in various publications were examined

only on selected issues, while no attempt

was made to synthetically capture the prob-

lem, and to consider all key aspects of the

Business Intelligence analytics and big

data technologies; considerations does not

have an interdisciplinary attribute and the

conclusions from the research was not a de-

rivative of a fully synthetic approach. Syn-

thetic research approach has been used in

this study. One of the key methodological

premises of the present study of the use of

computerized Business Intelligence analyt-

ics platforms and data processing in Big

Data database systems in integrated risk

management processes in business entities

was the application of a synthetic research

approach to achieve interdisciplinary com-

bination of various aspects of the described

and researched issues of Business Analyt-

ics applications Intelligence and Big Data

technology in the business management

process. The key conclusions that were for-

mulated in the summary part are a deriva-

tive of the synthetic research approach

used. Based on the content of the studied

source materials and expert publications, it

has been demonstrated that in recent years

the problem of supporting risk manage-

ment processes in business entities through

the use of information processing in Big

Data technology and Business Intelligence

platforms is among the most developmen-

tal areas in the field of practical applica-

tions of the process organization manage-

ment as well as scientific research of this

issue. This article describes the issues of

the applications of Business Intelligence

analytics and Big Data technology in the

enterprise management process with the

use of a synthetic approach to research and

considerations undertaken by authors in

earlier publications: A. Dmowski

(Dmowski A., Prokopowicz D., 2010); D.

Prokopowicz (Prokopowicz D., 2003, Pro-

kopowicz D., 2013, Prokopowicz D., 2014,

Prokopowicz D., 2015), S. Gwoździewicz

(Gwoździewicz S., 2014; Gwoździewicz

S., Prokopowicz D., 2016a, b ), J. Grze-

gorek (Grzegorek J., Prokopowicz D.,

2017), B. Domańska-Szaruga (Domańska-

Szaruga B., Prokopowicz D., 2015) and

other authors of the cited publications.

Aims of paper. Methods.

Before writing this article, a literature re-

view of the issues of supporting risk man-

agement processes in business entities

through the use of information processing

in Big Data technology and in Business In-

telligence platforms has been made. The

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

literature review was also preceded by

specifying the key issues, which were ana-

lyzed, the objectives of the research under-

taken and the formulation of key questions

and research thesis. The subject of this

work initially defined conceptually and ax-

iomatically was also clarified after the re-

view of publications of other researchers

regarding the application of Big Data data-

base systems and business analytics appli-

cations in the pro-cesses of integrated risk

management in the organization. In view of

the above, the article presents an analysis

of the application of Business Intelligence

analytics and Big Data technology in the

business management process in a syn-

thetic approach.

The analysis of source materials shows that

the studied issues of the topic of the use of

computerized Business Intelligence analyt-

ics platforms and data processing in Big

Data database systems in integrated risk

man-agement processes in enterprises have

been described and considered in the cur-

rent scientific literature only in selected as-

pects. No attempts have been made to carry

out research that would consist in develop-

ing a synthetic approach to this problem. A

full synthetic approach would integrate

various key aspects of supporting risk man-

agement processes in business entities

through the use of information processing

in Big Data database systems and comput-

erized Business Intelligence platforms, the

considerations would have an interdiscipli-

nary attribute and the conclusions from the

research would also have a synthetic ap-

proach. This type of research approach has

been used in this study. One of the key

methodological premises of the analysis of

Business Intelligence and Big Data in the

business management process was the use

of a fully objective description of all prem-

ises, conditions, components of the ana-

lyzed topic and factors affecting particular

aspects of Business Intelligence analytics

and Big Data tech-nology. While analyzing

the problem of the use of computerized

Business Intelligence analytics platforms

and data processing in Big Data database

systems in integrated risk management

processes in business entities, the authors

of this study have verified the theses and

conclusions formulated by the authors of

the cited publications. Verified theses and

conclusions that repeatedly represented a

diverse view, heterogeneous evaluation of

key as-pects of the topic in terms of their

level of significance and identified correla-

tions were used to formulate key questions

and research theses for this study. Based on

the verification, conclusions were formu-

lated, which were included in the summary

part. While formulating these conclusions,

the research carried out was guided by the

principle of scientific objectivity, impar-

tiality and synthetic of the research ap-

proach.

During the research, various research

methods were used, which were listed be-

low: descriptive and com-parative meth-

ods, inductive reasoning, deductive reason-

ing, descriptive-vector method, media ob-

servation meth-od. The choice of methods

was determined by the type of research ma-

terials in which various aspects of the prob-

lem of supporting risk management pro-

cesses in business entities through the use

of information processing in Big Data da-

tabase systems and computerized Business

Intelligence analytics platforms were de-

scribed. The purpose of presenting key is-

sues of the subject, explaining particularly

important relationships, correlations be-

tween the components of the application of

computerized Business Intelligence plat-

forms and data processing in Big Data da-

tabase systems in integrated risk manage-

ment processes in business entities mainly

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

uses a descriptive method. The compara-

tive method was used primarily in the com-

parisons of selected aspects of the studied

issues of appli-cations of Business Intelli-

gence analytics and Big Data technology in

the process of managing various business

entities. Inductive reasoning was used to

select unambiguous facts and aspects of the

problem of supporting busi-ness entity

management processes through the use of

Business Intelligence analytics and infor-

mation processing in Big Data technology

meeting the requirement of indisputability

in their experimental verification.

In connection with the above, guided by the

principle of scientific objectivity, impar-

tiality and synthetics of the research based

on the verification of the content of the

cited publications for the purpose of this

study, the following main research thesis

was formulated: In recent years, the im-

portance of supporting management pro-

cesses, including risk management in busi-

ness entities information processing in Big

Data database systems and computerized

Business Intelligence analytics platforms is

increasing. The final part of this study con-

tains a reference to the verifying the re-

search thesis.

Exposition of main material of research with complete substantiation

of obtained scientific results. Discussion.

Determinants of the implementation of in-

tegrated risk management in corporations

and financial institutions

The development of computer science, the

increase in the importance of derivatives on

capital markets, new distribution channels

for products, services, factors of produc-

tion and information, deregulation of fi-

nancial markets, the development of over-

national corporations are factors that deter-

mined the processes of economic globali-

zation since the 1970s (Gwoździewicz S.,

Prokopowicz D., 2016b, p. 65-66). One of

the important factors of these processes

was the growing level of risk of financial

markets and risk related to entities operat-

ing on these markets. The problem of the

growing level of risk appeared periodically

and grew during periods of global economy

downturn and usually also large discounts

of the market valuation of assets of busi-

ness entities. The escalation of these cycli-

cally emerging processes took place in au-

tumn 2008 and led to a global financial cri-

sis (Domańska-Szaruga B., Prokopowicz

D., 2015, p. 41-42).

Many years before 2008, individual identi-

fication tools, individual quantification

methods, and econometric models have al-

ready been improved, but this has not saved

the financial systems and entire national

economies from the crisis. The source of

the crisis was the lack of a full correlation

of the process of improving financial risk

management conducted in individual fi-

nancial entities and macroeconomic risk

management of the entire system, con-

ducted monetary policy, ignoring signals

suggesting growing financial problems and

deteriorating economic conditions in the

real economy. Some entities tried to hide

these problems in the initial stage of their

occurrence, using creative accounting,

however over time when the risk of bank-

ruptcy of the entire institution was already

very high and still grew strongly the only

solution that could protect an institution

from bankruptcy were low-interest govern-

ment loans.

The approach to risk management has

changed over the last years. Currently, the

management of individual types of banking

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

risks gives way to integrated risk manage-

ment systems and risk management of the

active operations. Changes taking place on

the financial markets, which are above all:

progress in the field of information tech-

nology and in the field of electronic ser-

vices,

widespread application of statistical econ-

ometric and credit scoring models in the

credit departments of financial institutions,

banks' expansion towards new areas of in-

vestment banking, including active partici-

pation in derivatives markets (Świderska

J., 2013, p. 84),

Banks leaving the traditional area of de-

posit and credit banking,

mutual overlap between sources of partic-

ular types of banking risks,

led to the modification of the overall con-

cept of risk management with an emphasis

on increasing the importance of integration

and systemic risk management as well as

the risk of active operations (e.g. all loans

and pseudo loans granted by a given bank).

Integrated risk management is a process in

which activities of individual departments

of institutions should be aimed at achieving

the same goals. The integration of various

activities requires the existence of a cen-

tralized information system that would

cover all aspects of the organization's func-

tioning. Such a system should also (Pro-

kopowicz D., 2015, p. 86-87):

provide all units and departments author-

ized to make decisions with relevant infor-

mation,

enable making decisions at operational lev-

els consistent with the organization's stra-

tegic objectives,

support decision-making at all levels of the

organizational structure by providing up-

to-date information reflecting the operation

of the entire entity as well as its individual

departments.

Constant development of IT makes possi-

ble construction of a centralized infor-

mation system that meets the above crite-

ria. Integrated risk management organized

on the basis of such system is currently the

most frequently discussed issue in the con-

text of maintaining or increasing the com-

petitiveness of an organization in the sector

(Żabińska J., ed. 2011, p. 147).

Integrated risk management in corpora-

tions and financial institutions is based on

(Butler C., 2002, p. 44):

identification and quantification of all

types of risk resulting from the conducted

activity,

assessing the significance of particular

risks, both individually and in comprehen-

sive terms,

development and implementation of a risk

management strategy covering areas with

which all of the examined risks are related.

Integrated risk management enables:

focusing of the management on those types

of risk that are most important for the busi-

ness,

application of various methods of compre-

hensive risk reduction and securing assets

methods.

The process of improving systems and

models of risk management in financial in-

stitutions can also be implemented actively

through the exchange of experiences of in-

dividual financial institutions or passively,

in a situation where the bank focuses only

on the experience of its own operations. In

the event of the detection of unforeseen ef-

fects of market, operational or credit risk in

one of the financial institutions, the source

of the event is identified and is fully ana-

lyzed also in the supervisory and advisory

institutions. The conclusions from the ana-

lyzes are the basis for the amendment of le-

gal regulations developed by supervisory

bodies and for the improvement of risk

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

management systems implemented in indi-

vidual entities (Prokopowicz D., 2015, p.

85). Increasing importance of integrated

risk management in corporations and fi-

nancial institutions

Improvement of integrated risk manage-

ment in corporations should combine the

methodology of modeling of individual

risk categories using advanced mathemati-

cal and statistical methods and active shap-

ing of revenues from sales through specific

financial instruments with traditional

methods based on, the limits of exposures

and concentration (Koleśnik J., 2012, p.

67). In connection with the above, taking

into account mainly the quantitative nature

of both the risk measurement models and

the data subject to the study, Business In-

telligence applications are perfectly suited

to building integrated risk management

systems in the organization. The process of

building and successive improvement of

these systems in Poland began in the sec-

ond half of the 90s and was determined

mainly by the technological progress of

quantitative methods of individual catego-

ries of risks embedded in computerized an-

alytical platforms as well as adaptation of

applied research methods to standards of

European Union. An example of this deter-

minant of adaptation processes to the re-

quirements of the European Union is the

banking sector in Poland. For a dozen

years, new risk management standards

have been implemented in commercial

banks operating in Poland as part of the

process of adjusting the applied procedures

and models for estimating individual finan-

cial and operational risk categories to the

Basel Committee's guidelines on financial

supervision (Prokopowicz D ., 2003, p. 97-

98). Commercial banks operating in Po-

land that use advanced methods in the

credit risk management process, based on

the Value at Risk method (Prokopowicz D.,

2013, p. 18-19), have the opportunity to

significantly reduce their credit activity

costs. The Value at Risk method is the ba-

sis of advanced mathematical and statisti-

cal risk measurement methods. The most

well-known system of internal models for

measuring and aggregating risk is the sys-

tem RiskMetricsTM (RiskMetricsTM –

Technical Document, Fourth Edition, De-

cember 1996), developed by the American

investment bank J. P. Morgan (Świderska

J., 2013, p. 96). The Value at Risk method

allows (for the assumed probability) to de-

fine a situation of exceeding the level of a

potential loss value. In general, the value of

this probability is taken to be 0.05 or 0.01.

The Value at Risk value is a summary and

statistical measure of potential losses

shown in the balance sheet under condi-

tions of an effective, i.e. "normal" func-

tioning of the

market.

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

Chart 1. Normal distribution model of VaR value estimation of active products at

the 99% confidence level.

Source: A. Kulik, Dlaczego Value at Risk jest standardem w zarządzaniu ryzykiem? Zastosowania metody

Cash Flow at Risk, Konferencja Polskiego Stowarzyszenia Ryzyka Finansowego PRMIA, 10.01.2003, p. 19.

Since the mid-1990s, the number of banks

in Poland applying new models based on

Value at Risk. This trend is in line with the

globally dominant tendencies because at

present almost all capital banks operating

in highly developed countries use ad-

vanced risk quantification methods with

the new standards resulting from the provi-

sions of the New Capital Accord (Żabińska

J., ed., 2011, p. 39) .

Banks use different econometric models in

relation to risk analysis. For the risk analy-

sis processes in unitary terms, i.e. in rela-

tion to a single credit or pseudo credit

transaction, the most commonly used

method currently applied in financial insti-

tutions is scoring method based on the for-

mula of granting a specific number of

points for each factor under investigation

(Prokopowicz D., 2014, p. 151-152). This

method is also based mainly on quantita-

tive data describing a potential counter-

party or the transaction under review be-

fore its finalization. The main premise for

using this method is to strive for maximum

objectivity, standardization and reduction

of operational costs of the analytical pro-

cess. All the research methods listed above,

are important factors subject to the perma-

nent process of improving the integrated

risk management process (Matuszyk A.,

2008, p. 57). Due to the clearly prevailing

quantitative nature of research methods,

identification and quantification of individ-

ual risk categories, the continuation of the

process of risk management improvement

can be carried out by implementing Busi-

ness Intelligence platforms that are cur-

rently under development.

Poland in this matter fits the global trends.

In connection with the above, as a conse-

quence of the adaptation of national regu-

lations to the guidelines and recommenda-

tions of the Basel Committee on Financial

Supervision, the security of the financial

system in Poland should gradually in-

crease. On the other hand, the implement-

ing of Business Intelligence platforms in

enterprises and financial institutions (Grze-

gorek J., Prokopowicz D., 2017, p. 223-

1 percent of event

Probability distribution

International Journal of New Economics and Social Sciences № 2(8)2018

ISSN 2450-2146 / E-ISSN 2451-1064

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/)

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data

And Business Intelligence Software In Integrated Risk Management In Organization

International Journal of New Economics and Social Sciences, 2(8)2018: 43-56

DOI 10.5604/01.3001.0012.9925

234) should contribute to the organiza-

tional and technological improvement of

already built integrated risk management

systems.

Conclusions.

The public sector, often called the govern-

ment sector, is the section of economy

which concerns transactions performed by

the government. Using the income ob-

tained from taxes and other sources of in-

come, the government finances its ex-

penses, affecting the economy and invest-

ment decisions (Pas Ch., Lowes B., Da-

vies., 2000, p.439-440). The above defini-

tion, however, has become a little outdated.

More and more expenditure on healthcare

or education is being financed on commer-

cial terms, following the growing scope of

privatization of entities operating in these

areas (Karpiński A., Paradysz S., 2005,

p.59-60).

An important issue which appears in dis-

cussions concerning the purposefulness

and rationality of the amounts spent is the

concept of their effective spending and ac-

counting.

The degree of development, the role of the

public sector and its efficiency can be

measured by means of various measures,

including (Karpiński A., Paradysz S.,

2005, p.62-63):

1) the share of public sector in the whole

employment in the country economy

(OECD) ,

2) the share of expenditure on the public

sector in the Gross Domestic Product

(GDP),

3) the share of the public sector in fixed as-

sets of the economy,

4) the level of satisfying the needs for pub-

lic services in particular categories of

service users (for example the unem-

ployed, the retired, children),

5) the share of public funds in financing

particular types of services (healthcare, ed-

ucation, cultural activity),

6) the results of the public opinion survey

evaluating the degree of satisfying the

needs for public services,

7) the efficiency of funds spent on public

services,

8) qualitative indicators evaluating the

public sector operations.

The above indicators and their cognitive

values are, however, commonly criticized.

Therefore we should consider developing

and adopting uniform criteria for evaluat-

ing the ways of spending public funds. This

is by no means an easy task, since the pub-

lic sector is not homogenous, whereas tasks

performed by public sector units are nu-

merous and varied.

The development of uniform sector indica-

tors in the context of groups of entities (for

example healthcare units, education units,

etc.) could become a tool for rationalizing

the expended funds as well as the criterion

of evaluating not only the correctness of

their expenditure but also evaluating the

achieved effects. Uniform indicators would

also ensure comparability, needed so much

when evaluating planning resources allo-

cated for tasks performed by the public sec-

tor.

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Dec 2022

Dariusz Prokopowicz

The economic crisis, which in 2020 was caused by the SARS-CoV-2 (Covid-19) coronavirus pandemic, was mainly a downturn and recession of non-financial sectors of the economy, mainly resulting from the recession of service sectors covered by lockdowns. The previous mainly financial crisis occurred in 2007-2009. These crises had a different character and other anti-crisis interventionist actions were launched as part of monetary policy and/or fiscal, budgetary, social policy, etc. In 2021, the global economy began to recover efficiently from the economic crisis of 2020. On the other hand, in 2021 there was an increase in inflation as a result of excessively interventionist, monetarist anti-economic measures implemented as part of public financial aid offered during the pandemic to commercially operating economic entities. In 2022, the increase in inflation accelerated and there may be another significant slowdown in economic growth caused by economic sanctions imposed on Russia in connection with the war in Ukraine. The aforementioned war caused an increase in fossil fuel prices, energy prices, food prices and became another pro-inflationary factor. Central banks raise interest rates as part of anti-inflationary measures. However, inflation remains elevated. As a result, there were symptoms of a decrease in consumption and production, and enterprises resigned from the implementation of previously planned business ventures and reduced the level of investments. The result may be the emergence of a deep economic downturn in 2023. In connection with the above, the following research questions arise: what were the original sources of inflation growth and what anti-crisis socio-economic policy should be applied by the governments of individual countries to avoid stagflation in 2023?

Gospodarcze skutki wojny w Ukrainie

Chapter

Full-text available

Mar 2023

Dariusz Prokopowicz

W rozdziale pt. Gospodarcze skutki wojny w Ukrainie opisano kluczowe aspekty wpływu toczącej się od 24 lutego 2022 roku wojny w Ukrainie na polską gospodarkę ze szczególnym uwzględnieniem wywołanego tą wojna kryzysu energetycznego w Europie oraz także w polskiej gospodarce. Gdy w 2021 roku gospodarki wielu krajów zaczęły wychodzić z covidowej recesji gospodarki 2020 roku to również ceny różnych kategorii surowców przemysłowych i energetycznych zaczęły rosnąć. Następnie zaraz po tym gdy 24 lutego 2022 roku wojska sowieckie najechały Ukrainę ceny paliw kopalnych zaczęły dodatkowo szybko rosnąć na giełdach surowców energetycznych. Również cena energii elektrycznej w ofertach firm energetycznych zaczęła szybko rosnąć. Wzrosty cen paliw i energii stały się kolejnymi czynnikami wzrostu cen produktów spożywczych, co finalnie spowodowało także przyspieszenie wzrostu inflacji. W związku z tym już w połowie 2022 roku pojawiły się prognozy sugerujące, że w okresie grzewczym jesień-zima 2022/2023 wystąpi poważny kryzys energetyczny w wielu krajach. Poza tym w 2022 roku inflacja kontynuowała swój wzrost i sukcesywnie wyczerpywały się rządowe instrumenty antyinflacyjnej polityki gospodarczej. Skutkiem było spadające tempo wzrostu gospodarczego odnotowane już niemal od początku 2022 roku. Skutkiem znacznego wzrostu inflacji jest spadek poziomu realnych dochodów obywateli oraz skutkiem może być także wzrost bezrobocia i skali ubóstwa w społeczeństwie. W sytuacji sukcesywnie pogłębiającej się dekoniunktury gospodarki w 2023 roku może pojawić się nawet stagflacja i recesja gospodarki w 1 i/lub 2 kwartale 2023 roku. Niektóre gospodarki nie wyszły jeszcze w pełni ze skutków globalnego kryzysu finansowego 2008-2009 oraz z pandemicznego kryzysu gospodarczego 2020 a teraz pojawiają się symptomy kolejnego, poważnego kryzysu energetycznego i gospodarczego, który może się pojawić w 2023 roku. Rozwijające się kryzysy związane ze wzrostem inflacji, wzrostem kosztu pieniądza, rozwijającym się kryzysem energetycznym wcześniej już się rozwijały, ale nie były do tej pory w takim stopniu widoczne i zauważalne jak to jest obecnie. Nie były także tak bolesne kosztowo i egzystencjalnie dla obywateli jak obecnie. Wojna w Ukrainie spowodowała przyśpieszenie i zwiększenie skali określonych procesów gospodarczych w Polsce, które od lat już się wcześniej rozwijały ale nie były do tej pory w takim stopniu widoczne i zauważalne jak to jest obecnie. Poza tym poziom inflacji zdeterminowany jest także tym jak jest prowadzona w Polsce zaostrzana od października 2021 roku polityka monetarna i nadal łagodna polityka fiskalna. Otóż szybkie i zastosowane z dużym zakresem podniesienie stóp proc. przez bank centralny spowodowałoby krótkotrwałą recesję ale również szybko rozwiązałoby problem inflacji. Natomiast powolne podnoszenie stóp proc. przez bank centralny i stosowanie łagodnej polityki fiskalnej polegającej na dodatkowych dotacjach, dopłatach i zasiłkach socjalnych powoduje, że powoli zaostrzana polityka monetarna nie działa antyinflacyjnie i inflacja może utrzymywać się latami. Długotrwała, wieloletnia inflacja jest dla obywateli najbardziej kosztowna i może wygenerować kolejne kryzysy od 2023 roku. Do tych kolejnych kryzysów, które mogą pojawić się od 2023 roku to jest kryzys zadłużeniowy w systemie finansów publicznych państwa oraz ewentualna stagflacja w sytuacji znacznego wzrostu bezrobocia.

Społeczno-ekonomiczne determinanty rozwoju zastosowań technologii generatywnej sztucznej inteligencji (Socio-economic determinants of the development of generative artificial intelligence technology applications)

Preprint

Full-text available

Dec 2024

Dariusz Prokopowicz

Rozwój generatywnej sztucznej inteligencji (GAI), tworzącej treści takie jak teksty, obrazy, muzyka czy symulacje, zależy od czynników społeczno-ekonomicznych, które kształtują jej potencjał wdrożeniowy. Wzrost produktywności, popyt na automatyzację oraz dostępność kapitału sprawiają, że duże firmy inwestują w GAI, by obniżać koszty i przyspieszać procesy. Jednakże, automatyzacja ta może zagrozić miejscom pracy w sektorach niskokwalifikowanych, szacując ryzyko likwidacji do 15% stanowisk do 2030 r. Wysokie koszty technologii ograniczają dostęp mniejszych firm, co może zwiększać nierówności. Regulacje, jak przygotowywany w Unii Europejskiej AI Act, wspierają odpowiedzialne stosowanie GAI, ale różnice prawne między państwami mogą prowadzić do nierówności technologicznych. Adaptacja społeczna rośnie, mimo obaw o dezinformację, a rozwój infrastruktury, np. chmury obliczeniowej, przyspiesza rozwój GAI, choć podnosi kwestie ekologiczne. Przyszłość GAI będzie zależeć od uwarunkowań społeczno-ekonomicznych, międzynarodowej konkurencyjności oraz współpracy na poziomie prawnym i etycznym. Model akceptacji technologii Davisa wskazuje, że społeczna akceptacja jest kluczowa, a teorie Schumpetera podkreślają rolę przedsiębiorców w napędzaniu innowacji, wymagając współpracy sektora prywatnego i publicznego. Słowa kluczowe: generatywna sztuczna inteligencja, GAI, determinanty rozwoju AI, rozwój zastosowań AI, automatyzacja, rynek pracy, dezinformacja, regulacje prawne, etyka AI - The development of generative artificial intelligence (GAI), which creates content such as text, images, music or simulations, depends on socioeconomic factors that shape its deployment potential. Productivity gains, demand for automation and the availability of capital are driving large companies to invest in GAI to cut costs and speed up processes. However, this automation could threaten jobs in low-skilled sectors, estimating the risk of eliminating up to 15% of positions by 2030. The high cost of the technology limits access for smaller companies, which could increase inequality. Regulations, such as the AI Act being drafted in the European Union, support responsible use of GAI, but legal differences between countries can lead to technological inequality. Social adaptation is growing, despite concerns about disinformation, and infrastructure development, such as cloud computing, is accelerating GAI development, although it raises environmental issues. The future of GAI will depend on socioeconomic conditions, international competitiveness, and cooperation at the legal and ethical levels. Davis' technology acceptance model indicates that social acceptance is key, and Schumpeter's theories emphasize the role of entrepreneurs in driving innovation, requiring private and public sector cooperation. Keywords: generative artificial intelligence, GAI, determinants of AI development, AI application development, automation, labor market, disinformation, regulation, AI ethics

Zarządzanie informacją w sytuacji kryzysowej

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Full-text available

Jul 2023

In recent years, there have been a number of different crises such as the dotcom crisis at the end of the 1990s, the global financial crisis of 2007-2009, the pandemic economic crisis and the global economic recession of 2020, the increase in commodity prices and the rise in inflation from 2021, the outbreak of war in Ukraine, the energy and food crisis that occurred in 2022 in many countries. In addition to this, a climate crisis is increasingly developing, which is primarily generated by the still high level of civilisation's greenhouse gas emissions and the increasingly rapid process of global warming. Some of these crises were caused by objective, external factors, independent of the economic policies pursued. On the other hand, however, economic and other crises are also caused by erroneous fiscal and budgetary policies pursued by the government and errors in monetary policies pursued by central banks. According to the long-term forecasting models of climatologists, geophysicists, ecologists, etc., the climate crisis already underway will intensify in the coming decades. As a result, the levels of various risks may increase and the conditions for doing business and managing an economic entity may become even more difficult in the future. As the scale and frequency of various crises increase, more and more economic actors and public institutions are taking various anti-crisis measures, creating and improving risk management systems, early warning systems and contingency plans, carrying out restorative and developmental restructuring processes, creating innovative solutions in order to flexibly adapt to the changing environment. As the climate crisis is likely to develop for many years to come, the importance of pursuing sustainable development goals and urgently carrying out a green transformation of the economy is growing. In the context of the issues outlined above, the importance of efficient organisational management, information management and crisis management is growing. The improvement of the processes of business entity, information and crisis management has been realised in recent years thanks to the implementation into information systems of new ICT information technologies and technologies typical of the current fourth technological revolution, Industry 4.0. Besides, within the improvement of computerised information systems, new Internet media are increasingly used as both a source of data and information and as a medium for the development of Internet channels of marketing communication conducted with customers and potential consumers. Key words: Information management, information systems, crisis management, crisis, economic crisis, financial crisis, climate crisis, new media, information security, Industry 4.0

Business Intelligence System Based on Big Data Technology

Conference Paper

Oct 2022

Gospodarcze skutki wojny w Ukrainie

Preprint

Full-text available

Jan 2023

Dariusz Prokopowicz

Globalization and the process of the systemic and normative adaptation of the financial system in Poland to the European Union standards

Article

Full-text available

Apr 2016

The publication describes the system and normative determinants of contemporary processes of economic globalization, which take place during the last decades and are linked in Europe with progressive integration of market structures of the European Union. Making the integration of market structures in Europe in 2004 also included Poland. In this way, Poland has significantly increased the scope of the openness of its economy for the development of trade. Therefore, the Polish accession to the European Union is considered to be an important factor in the continuation of the processes of globalization and economic growth. In the context of these processes since the 90s of the last century in Poland functioning economic systems and regulations specifying the functioning of the various branches, sectors and institutions are gradually adapted to EU standards. One of the sectors of the economy, which is relatively more has been adapted institutionally and normatively to the requirements of the EU financial system is in Poland.

Credit scoring w kontekście doskonalenia procesu zarządzania ryzykiem kredytowym

Article

Full-text available

Dec 2014

Dariusz Prokopowicz

Regulacje Komitetu Bazylejskiego a modyfikacje systemów zarządzania ryzykiem kredytowym

Article

Full-text available

Oct 2003

Dariusz Prokopowicz

Zarządzanie bankowym ryzykiem kredytowym realizowane jest w różnych obszarach działalności kredytowej banku. W procesie tym działalność kredytowa i jej weryfikacja w coraz większym stopniu zintegrowana zostaje z analizą ryzyka i sprzedaży pozostałych produktów banku oraz systemem zinformatyzowanego pozyskiwania, gromadzenia i przetwarzania danych. Z drugiej strony jest to proces koordynowany przez zewnętrzne instytucje tj. organy krajowego nadzoru bankowego oraz instytucje działające w skali międzynarodowej. Kryzys naftowy, deregulacja rynków walutowych, pojawienie się derywatów, globalizacja rynków kapitałowych to tylko niektóre aspekty wzrostu ryzyka w latach 70-tych ubiegłego wieku. Potrzeba stworzenia specjalnych regulacji ostrożnościowych dla sektora bankowego w skali globalnej była podstawą powołania w tym okresie Komitetu Bazylejskiego. Główne kierunki zmian w polskim systemie bankowym wyznaczane były przez pryzmat integracji Polski ze strukturami europejskiego systemu finansowego. Proces dostosowywania systemu bankowego, poszczególnych procedur działalności bankowej oraz jakości świadczonych usług do standardów międzynarodowych tj. przede wszystkim Unii Europejskiej oraz OECD, jest wynikiem z jednej strony odgórnych wymogów przystąpienia Polski do Wspólnoty Europejskiej, natomiast z drugiej strony, w ujęciu oddolnym, naturalnego procesu dostosowywania jakości produktów finansowych do analogicznych usług oferty banków zagranicznych, z których część już funkcjonuje w Polsce. Wstąpienie Polski do Unii Europejskiej warunkowane było spełnieniem szeregu modyfikacji na płaszczyźnie formalno-prawnej i instytucjonalnej również w sektorze usług finansowych, głównie poprzez stosowne zmiany w przepisach prawa bankowego oraz innych regulacjach prawnych rynku kredytowego w Polsce. Ostatnie nowelizacje regulacji bankowych doprowadziły do wysokiego stopnia zgodności polskich nadzorczych norm ostrożnościowych z dyrektywami Unii Europejskiej.

Business Intelligence and the Cloud: Strategic Implementation Guide

Book

Full-text available

Mar 2014

Michael S Gendron

Organizational managers are called upon to understand big data, BI, mobile and cloud computing, and to craft business and information technology (IT) strategies based on these technologies. The entire IT ecosystem is being disrupted with new offerings and lower technology prices that affect virtually every business decision. Managers are required to justify their projects based on total cost of ownership, return on investment, and capital expense versus operational expense. Books, trade journals, web sites, and consultants abound that will tell you how to use these technologies, and these are a great resource. However, it is helpful to have a book that provides explanations in an easily digestible way so that C-suite members, managers, and staff can obtain the background necessary to deploy the technologies that will bring the greatest competitive return. This book is just such a resource.

Bezpieczeństwo systemu bankowego. Teoria i praktyka

Book

Jan 2012

Jan Koleśnik

Bezpieczeństwo systemu bankowego nie jest dobrem danym raz na zawsze. Wymaga systematycznej i kompleksowej analizy otoczenia – zagranicznego i krajowego. Autor niniejszej książki właściwe formułuje wnioski, pisząc, że w świetle doświadczeń ostatniego światowego kryzysu finansowego konieczne jest dokonanie rekonstrukcji nie tylko podejścia teoretycznego, ale także praktycznego do kwestii bezpieczeństwa systemu bankowego. Słusznie zauważa przy tym, iż istotny wpływ na bezpieczeństwo zarówno pojedynczego banku, jak i całego systemu bankowego może mieć nadmierna skłonność do ryzyka osób zarządzających bankami. Zwraca on uwagę, że to właśnie człowiek podejmuje decyzje finansowe obarczone ryzykiem i że decyzje te mają różne podłoże. Autor swoją książką wnosi istotny i nowatorski wkład do teorii ekonomii behawioralnej.

THE IMPLEMENTATION OF AN INTEGRATED CREDIT RISK MANAGEMENT IN OPERATING IN POLAND COMMERCIAL BANKS

Article

Dec 2015

Dariusz Prokopowicz

Since the late 90-th the value of an integrated credit risk management in commercial banks operating in Poland has become very actual. In classical terms, the integrated risk management is the identification and valuation of certain categories of bank risks associated with their activities. The using of modern information systems helpes to improve the integration of the various business segments in the banks and develope a model for risk management portfolio. The implementation of integrated risk management in relation to the loan portfolio improved process control assets of banks. Thus, a comprehensive risk management in terms of loan portfolio significantly adds risk analysis model, each credit transaction.

Business intelligence in cloud

Article

Jan 2014

Celina M. Olszak

The paper reviews and critiques current research on Business Intelligence (BI) in cloud. This review highlights that organizations face various challenges using BI cloud. The research objectives for this study are a conceptualization of the BI cloud issue, as well as an investigation of some benefits and risks from BI cloud. The study was based mainly on a critical analysis of literature and some reports on BI cloud using. The results of this research can be used by IT and business leaders as they plan and develop BI cloud in their organizations. © 2014, Czestochowa University of Technology. All Rights reserved.

Witryna internetowa "cdnpartner.pl

Jan 2017

B I Analizy

Analizy BI (w:) Witryna internetowa "cdnpartner.pl", marzec 2017, (https://cdnpartner.pl/oferta/rozwiazania-comarch/comarch-erp-optima/analizy-bi).

Application Of Data Base Systems Big Data And Business Intelligence Software In Integrated Risk Management In Organization

Jan 2018
43-56

D Gwoździewicz
D Prokopowicz
J Grzegorek
M Dahl

Gwoździewicz D., Prokopowicz D., Grzegorek J., Dahl M., (2018) Application Of Data Base Systems Big Data And Business Intelligence Software In Integrated Risk Management In Organization. International Journal of New Economics and Social Sciences,2(8)2018: 43-56 DOI 10.5604/01.3001.0012.9925

Tajniki Value at Risk. Praktyczny podręcznik zastosowań metody VaR. Wydawnictwo Liber, s. 44

Jan 2002

C Butler

Butler C. (2002). Tajniki Value at Risk. Praktyczny podręcznik zastosowań metody VaR. Wydawnictwo Liber, s. 44.

APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION

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