The aim of this thesis is to evaluate creditworthiness (credibility) of a client and assessment of loan granting decision. The work highlights the importance of financial analysis, which constitutes a basis for risk assessment of a client and is a deciding factor in the final decision of granting a loan. Theoretical and methodological part deals with definitions, explanation of terms and methods related to credit processing and financial analysis. The second part assesses financial stability of the company "Firma, a.s." through financial analysis and subsequently evaluates its credibility by applying a selected credit rating model. As a result, final loan granting decision is made.

Consumer credit Abstract This diploma thesis deals with the topic of consumer credit, focusing on a systematic and comprehensive analysis of the development of consumer credit legislation not only in the Czech Republic, but also with a focus on essential legislation of the European Community and the European Union. The thesis is also focused on answering the theses set out in the introduction, which focus mainly on the issue of assessing the creditworthiness of consumers and the issue of regulation of providers and intermediaries and their impact on the activities of these entities in practice. For this purpose, the thesis is structured into seven parts, in which the legal regulation of consumer credit is systematically described, and certain essential or problematic passages are analysed in more detail. The first part of the thesis defines the basic concepts that are used in all aspects of consumer credit legislation and simultaneously in this thesis. The second part follows, which deals with the historical development of consumer credit from its very beginnings, through the development of consumer credit legislation in Community law, to the development of consumer credit legislation in our legal system. In the third part of this thesis, I analyse the general legal regulation of consumer credit and related...

The main aim of my diploma thesis is to choose the most sutaible option of loan financing of business activities of individual in simulated conditions. The first part is followed to summary of theoretical knowledges about loans issues which are loan analysis specifically interest, loan application, repayment, protection, risks and types of loans, then loan markets, loan unions and central bank and loans. The second part is aimed to analysis of specific cases of getting loans, morgages and leasing for entrepreneurs and citizens and it´s following evaluation. Then there is comparison of the best options. In conclusion of this part there are analysis and all the results of current situation of getting loans for entrepreneurs in Czech republic.

This master thesis focuses on checking the status of performance measurement and management of ThyssenKrupp Výtahy, s.r.o. and on implementation of financial analysis for years 2007-2012. The first part is concentrated mainly on the current state of performance measurement and management and introduction of IT background including introduction of the reporting system and their use in performance management. The second part is dedicated to the financial analysis to find the weaknesses in performance management using vertical and horizontal analysis of financial statements, ratio indicators, credibility and bankruptcy models, EVA indicator and a comparison with the sector average, and to summarize the results and to provide recommendations.

As the use of AI in society is developing, the requirement of explainable algorithms has increased. A challenge with many modern machine learning algorithms is that they, due to their often complex structures, lack the ability to produce human-interpretable explanations. Research within explainable AI has resulted in methods that can be applied on top of non- interpretable models to motivate their decision bases. The aim of this thesis is to compare an unexplained machine learning model used in combination with an explanatory method, and a model that is explainable through its inherent structure. Random forest was the unexplained model in question and the explanatory method was SHAP. The explainable model was logistic regression, which is explanatory through its feature weights. The comparison was conducted within the area of creditworthiness and was based on predictive performance and explainability. Furthermore, the thesis intends to use these models to investigate what characterizes loan applicants who are likely to default. The comparison showed that no model performed significantly better than the other in terms of predictive performance. Characteristics of bad loan applicants differed between the two algorithms. Three important aspects were the applicant’s age, where they lived and whether they had a residential phone. Regarding explainability, several advantages with SHAP were observed. With SHAP, explanations on both a local and a global level can be produced. Also, SHAP offers a way to take advantage of the high performance in many modern machine learning algorithms, and at the same time fulfil today’s increased requirement of transparency. / I takt med att AI används allt oftare för att fatta beslut i samhället, har kravet på förklarbarhet ökat. En utmaning med flera moderna maskininlärningsmodeller är att de, på grund av sina komplexa strukturer, sällan ger tillgång till mänskligt förståeliga motiveringar. Forskning inom förklarar AI har lett fram till metoder som kan appliceras ovanpå icke- förklarbara modeller för att tolka deras beslutsgrunder. Det här arbetet syftar till att jämföra en icke- förklarbar maskininlärningsmodell i kombination med en förklaringsmetod, och en modell som är förklarbar genom sin struktur. Den icke- förklarbara modellen var random forest och förklaringsmetoden som användes var SHAP. Den förklarbara modellen var logistisk regression, som är förklarande genom sina vikter. Jämförelsen utfördes inom området kreditvärdighet och grundades i prediktiv prestanda och förklarbarhet. Vidare användes dessa modeller för att undersöka vilka egenskaper som var kännetecknande för låntagare som inte förväntades kunna betala tillbaka sitt lån. Jämförelsen visade att ingen av de båda metoderna presterande signifikant mycket bättre än den andra sett till prediktiv prestanda. Kännetecknande särdrag för dåliga låntagare skiljde sig åt mellan metoderna. Tre viktiga aspekter var låntagarens °ålder, vart denna bodde och huruvida personen ägde en hemtelefon. Gällande förklarbarheten framträdde flera fördelar med SHAP, däribland möjligheten att kunna producera både lokala och globala förklaringar. Vidare konstaterades att SHAP gör det möjligt att dra fördel av den höga prestandan som många moderna maskininlärningsmetoder uppvisar och samtidigt uppfylla dagens ökade krav på transparens.

Der Trend zur Auswertung aller nur möglichen Datenbestände für kommerzielle Zwecke ist eine nicht mehr aufzuhaltende Entwicklung. Auch für die Kreditwürdigkeitsprüfung wird überlegt, Daten aus Sozialen Netzwerken einzusetzen. Die Forschungsfrage entsteht, wie die Nutzer dieser Netzwerke reagieren, wenn Banken ihre privaten Profile durchsuchen. Mit Hilfe einer Befragung von 271 Probanden wurde dieses Problem erforscht. Die Ergebnisse sind wie folgt: Die betroffenen Bürger sehen die Entwicklung mit Sorge. Sie begreifen ganz rational die neuen Geschäftsmodelle und ihre Logik und erkennen die Vorteile. Sie stehen dem Big-Data-Ansatz nicht vollkommen ablehnend gegenüber. Abgelehnt wird es aber, wenn sich Daten aus sozialen Medien negativ für eine Person auswirken. Wenn man schon sein Facebook-Profil einer Bank öffnet, dann will man einen Vorteil davon haben, keinen Nachteil. Ein Teil der Gesellschaft lehnt das Schnüffeln in privaten Daten strikt ab. Insgesamt sind die Antworten deutlich linksschief verteilt mit einem sehr dicken Ende im ablehnenden Bereich. Das Schnüffeln in privaten Daten wird als unethisch und unfair empfunden. Die Menschen fühlen sich im Gegenzug berechtigt, ihre Facebook-Daten zu manipulieren. Eine wie-Du-mir-so-ich-Dir-Mentalität ist festzustellen. Wer kommerziell ausgeschnüffelt wird, der antwortet kommerziell mit Manipulationen seiner Daten. Insgesamt ist Banken zu raten, nicht Vorreiter der Entwicklung zu sein, sondern abzuwarten, welche Erfahrungen Fintechs machen. Banken haben zu hohe Opportunitätskosten in Form des Verlustes von Kundenvertrauen. / The trend to analyze all conceivable data sets for commercial purposes is unstoppable. Banks and fintechs try to use social media data to assess the creditworthiness of potential customers. The research question is how social media users react when they realize that their bank evaluates personal social media profiles. An inquiry among 271 test persons has been performed to analyze this problem. The results are as follows: The persons are able to rationally reflect the reasons for the development and the logic behind big data analyses. They realize the advantages, but also see risks. Opening social media profiles to banks should not lead to individual disadvantages. Instead, people expect an advantage from opening their profiles voluntarily. This is a moral attitude. An important minority of 20 to 30 % argues strictly against the commercial use of social media data. When people realize that they cannot prevent the commercial use of private data, they start to manipulate them. Manipulation becomes more extensive when test persons learn about critical details of big data analyses. Those who realize that their private data are used commercially think it would be fair to answer in the same style. So the whole society moves into a commercial direction. To sum up, banks should be reluctant and careful in analyzing private client big data. Instead, banks should give the lead to fintechs as they have fewer opportunity costs, because they do not depend on good customer relations for related products.

Der Trend zur Auswertung aller nur möglichen Datenbestände für kommerzielle Zwecke ist eine nicht mehr aufzuhaltende Entwicklung. Auch für die Kreditwürdigkeitsprüfung wird überlegt, Daten aus Sozialen Netzwerken einzusetzen. Die Forschungsfrage entsteht, wie die Nutzer dieser Netzwerke reagieren, wenn Banken ihre privaten Profile durchsuchen. Mit Hilfe einer Befragung von 271 Probanden wurde dieses Problem erforscht. Die Ergebnisse sind wie folgt: Die betroffenen Bürger sehen die Entwicklung mit Sorge. Sie begreifen ganz rational die neuen Geschäftsmodelle und ihre Logik und erkennen die Vorteile. Sie stehen dem Big-Data-Ansatz nicht vollkommen ablehnend gegenüber. Abgelehnt wird es aber, wenn sich Daten aus sozialen Medien negativ für eine Person auswirken. Wenn man schon sein Facebook-Profil einer Bank öffnet, dann will man einen Vorteil davon haben, keinen Nachteil. Ein Teil der Gesellschaft lehnt das Schnüffeln in privaten Daten strikt ab. Insgesamt sind die Antworten deutlich linksschief verteilt mit einem sehr dicken Ende im ablehnenden Bereich. Das Schnüffeln in privaten Daten wird als unethisch und unfair empfunden. Die Menschen fühlen sich im Gegenzug berechtigt, ihre Facebook-Daten zu manipulieren. Eine wie-Du-mir-so-ich-Dir-Mentalität ist festzustellen. Wer kommerziell ausgeschnüffelt wird, der antwortet kommerziell mit Manipulationen seiner Daten. Insgesamt ist Banken zu raten, nicht Vorreiter der Entwicklung zu sein, sondern abzuwarten, welche Erfahrungen Fintechs machen. Banken haben zu hohe Opportunitätskosten in Form des Verlustes von Kundenvertrauen. / The trend to analyze all conceivable data sets for commercial purposes is unstoppable. Banks and fintechs try to use social media data to assess the creditworthiness of potential customers. The research question is how social media users react when they realize that their bank evaluates personal social media profiles. An inquiry among 271 test persons has been performed to analyze this problem. The results are as follows: The persons are able to rationally reflect the reasons for the development and the logic behind big data analyses. They realize the advantages, but also see risks. Opening social media profiles to banks should not lead to individual disadvantages. Instead, people expect an advantage from opening their profiles voluntarily. This is a moral attitude. An important minority of 20 to 30 % argues strictly against the commercial use of social media data. When people realize that they cannot prevent the commercial use of private data, they start to manipulate them. Manipulation becomes more extensive when test persons learn about critical details of big data analyses. Those who realize that their private data are used commercially think it would be fair to answer in the same style. So the whole society moves into a commercial direction. To sum up, banks should be reluctant and careful in analyzing private client big data. Instead, banks should give the lead to fintechs as they have fewer opportunity costs, because they do not depend on good customer relations for related products.

This dissertation work deals with the subject of a company in the area of e-commerce, which represents short-term or long-term plans in controlling the financial relationship toward the outer environment but also inside the company. The problem of possible abuse of credit cards is briefly analysed as well. The impulse for choosing this topic was increasing number of falsification and abusing of credit cards. When this subject is analysed in detail, the problem connected with lack of information on this particular area of crime inevitably appears. Clients of individual banking institutions often do not have even the basic knowledge about the ways their cards could be abused or misused. This is why the question of certain, at least minimal, basic information campaign done by the banks, which are supposed to protect the financial means of their clients. This dissertation work sets its goal in creating the methods of investigation of credit cards abuse not only in the Czech Republic but in the growing system of countries of Schengen Treaty and European Union. The benefit of the work can be seen in the level of theory as well of practice. The theoretical part of the work contains the analysis of the current situation of scientific knowledge in the area of information and communication technology of companies, which is implemented into information systems. Then the advantages and disadvantages connected with this kind of e-commerce are assessed and the specific opportunities for abuse of these media of payment are characterised. The problem sees mainly in writing a specialised publication, which would deal with the problem of abuse and falsification of credit cards and its possible use would be at police academies. Its main part should be the characteristics of particular forms of cards forging and also possible identification of these forgeries. This book could also help in prevention and inform clients of financial institutions about the ways of credit cards abuse. In the practical part, which concentrates on the Czech and foreign market, the author sets the basic premises for realisation of safe business of companies in the Czech Republic and its procedures. Furthermore the reasons of e-commerce abuse in the Czech Republic are analysed and results of quantification research presented. This was concentrated on ascertainment of reason of low interest in information among the public. In the conclusive part of the work the whole problem is summarised and there are also outlined perspectives and possibilities of further development

Положения научной новизны, изложенные в диссертации: - расширено содержание понятия «кредитоспособность» коммерческой организации, акцентируя внимание на необходимости периодической оценки менеджментом финансовых возможностей компании; - определена тенденция в формировании информационной базы оценки кредитоспособности в современных условиях и предложено дополнительное решение в подготовке наиболее полных данных о бизнесе; - разработан порядок определения долговой нагрузки по ключевым показателям, позволяющий оперативно представлять информацию для управления компанией. Практическая значимость работы заключается в разработке рекомендаций по совершенствованию управления привлечением и использованием заемного капитала, которые могут использоваться значительной частью коммерческих организаций. / The provisions of scientific novelty set out in the dissertation: - the content of the concept of "creditworthiness" of a commercial organization has been expanded, focusing on the need for management to periodically assess the company's financial capabilities; - a tendency in the formation of an information base for assessing creditworthiness in modern conditions was determined and an additional solution was proposed in the preparation of the most complete data on business; - a procedure for determining the debt burden by key indicators has been developed, which makes it possible to promptly provide information for the management of the company. The practical significance of the work lies in the development of recommendations for improving the management of attracting and using debt capital, which can be used by a significant part of commercial organizations.

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