The development and complexity of the e-commerce sector has increased the demand forcompanies to grasp and develop their business models, as well their credit risk managementfunctions, in order be profitable and create value. This thesis examines how credit riskmanagement can be integrated in a business model, in terms of a customer value proposition,profit formula, key processes and key resources. Theories about business models state that abusiness model should give a holistic view of the company and how it operates. Features for asuccessful model should include functions that create value and increase competitiveness, as wellas generating valuable cost and risk structures to ensure the company’s profitability. The empiricaldata was collected through interviews and secondary data at Klarna, a company that operates withpayment solutions in the e-commerce, a market where the risk of credit losses is high and to haveproper credit risk functions is a necessity. The result revealed that credit risk management is afundamental part of a business model in the e-commerce, since effective credit risk managementfunctions ensure that the elements of a business model are functional and complement each other.The study further found that there are certain prominent functions in each one of the four elementsthat enable the integration of credit risk management in the business model.

Magistro baigiamajame darbe nagrinėjamas Lietuvos bankinio sektoriaus kredito rizikos valdymas 2008-2011 m. laikotarpiu: teorinėje dalyje pateikiama bendroji kredito rizikos esmė, išskiriami galimi kreditų rizikos valdymo modeliai, metodai ir priemonės, lyginami skirtingų užsienio mokslininkų kredito rizikos valdymo empiriniai tyrimai. Empirinėje dalyje atliekama Lietuvos bankų sektoriaus suteiktų kreditų dinaminė analizė 2008-2011 m., sąryšiu su pagrindiniais kredito ir bankinės veiklos kokybės rodikliais, kreditų palūkanų normomis ir aptariama Lietuvos ūkinė situacija finansinės krizės metu. Konstruktyvioje dalyje pateikiamas galimas kredito rizikos valdymo modelis Lietuvos bankiniame sektoriuje. / In the final thesis of the Master‘s degree there are analyzed the credit risk management in Lithuanian banking sector in year 2008-2011: in the theoretical part there are described the general credit risk definition, highlighted models, approaches and tool for credit risk management, compared the interpretation aspects of credit risk management researches by different scientists. In the empirical part there are represented the dynamics of given credits in year 2008-2011, and its’ relationship with the main measures of the quality of credit portfolio and commercial banks‘ activity. In the last part there is represented the model for credit risk management in Lithuanian banking sector.

The diploma thesis is focused on predictive modeling in credit risk management. Banks and financial institutions are mainly interested in it to estimate the probability of client's default in order to make a decision about which client will be accepted and which client will be rejected. The theoretical part includes an introduction of credit scoring and a description of discrete choice models. The linear probability model, the probit model and the logit model are described in detail. The logit model is afterwards used for the prediction of client's default. The practical part is focused on a statistical description of the dataset and a description of how to work with it before we start with the development of the credit scoring model. After that follows the estimation of the model on testing sample, its testing and the estimation of the model on full sample with a description of individual steps of calculation and outputs of the program SPSS.

Diplomová práce se zabývá aplikací fuzzy logiky na proces automatické detekce úpadkového klienta z pohledu řízení úvěrového rizika banky. Na základě analýzy stávajícího informačního systému Credit Risk Monitoring autor navrhuje změnu přístupu v hodnocení úvěrového klienta.

iv Abstract This diploma thesis examines the impact of the COVID-19 crisis on the bank credit risk in the European Union. The analysis is performed using two sets of panel data. The first set contains data at the bank-level between 2012 and 2018 and is obtained from BankFocus batabase and the second set of data is obtained from the EBA Risk dashboard and contains data at the country-level between 2014 and 2020. Both datasets contain bank-specific variables and macroeconomic variables. We use the variables Cost of risk, Total capital ratio, Tier 1 ratio and NPE ratio as dependent variables. As representatives of the COVID-19 shock, we use the number of people infected with this disease, the number of deaths from this disease and the Stringency Index. We employ the GMM system for our analysis and test 5 hypotheses. We did not reject 3 hypotheses, namely that Cost of risk is a key determinant of credit risk and that the crisis caused by COVID-19 affects the variables Capitalo ratio and NPE ratio. We further concluded that the variables representing COVID-19 do not have a negative effect on credit risk, mainly due to the interventions of the ECB and the IASB. JEL Classification C12, C33, G01, G21 Keywords bank, COVID-19 crisis, credit risk management, Stringency index Title Author's e-mail Supervisor's e-mail...

Current regulation governing acquisition financing Abstract The thesis deals with financing of share deal acquisition operations. The first chapter points out idiosyncrasies of acquisition operations, providing context for the rest of the thesis. The second chapter deals with loan financing, one of the two financing methods described. The chapter starts off with Czech Civil Code's rules governing loans and goes on to provide an overview of stipulations used in corporate banking practice, including the usual arrangement of rights and obligations of lenders and borrower in case of syndicated loans. A subchapter about credit risk rounds off the second chapter. Not restricted to public law regulation, it describes derivatives used to hedge against credit risk and touches upon the influence of regulation on cost of loan financing. The third chapter is about bond financing. It offers a robust overview of Czech rules governing bonds as nominate debt securities and their issue. The consequent subchapter on placement of bonds handled by an investment firm serves as an equivalent of the banking practice- focused subchapter. Subjects that perform various tasks after placement in order to simplify the administration of a given issue are a topic which completes the third chapter. The conclusion of the thesis sets out...

E-commerce has grown significantly the last decade, and made a considerable leap during Covid19. The final step in e-commerce is payments, and as a result of this, credit risk management in real-time has become increasingly important. An imperative function in credit risk management is underwriting, in which it is decided which purchases to accept and which not to. However, events can occur that cause increases or decreases in for instance acceptance rates, and these must be detected in order to for instance maintain good stakeholder relationships. Thus, KPI:s are monitored with the aim of detecting outliers as soon as possible.  The purpose of this study is to explore the business value and obstacles of automating outlier detection for credit risk KPI time series in e-commerce. In addition, aspects to think about on implementation are investigated. The research is a case study and is founded in thematic analysis of qualitative data collected at an e-commerce company.  The results of the study show that automation can contribute to significant business value due to for instance a decrease in monetary and alternative costs of manual monitoring, as well as a potential for better quality in the monitoring, and thus also enhanced stakeholder relationships. However, results also imply that there are several obstacles to actually implementing full automation such as a lack of trust in the automation, along with opinions that automation will impair knowledge and communication, and that the implementation is complex. / Under det senaste årtiondet har e-handel signifikant växt, och under Covid19 eskalerade utvecklingen ännu mer. Det sista steget i e-handel är betalningar, och till följd av detta har kreditriskhantering blivit allt viktigare. En signifikant funktion i kreditriskhantering är underwriting, där det bestäms vilka köp som skall accepteras och inte. Dock kan händelser ske som ökar eller minskar till exempel andelen köp som accepteras, och dessa händelser måste identifieras bland annat för att kunna upprätthålla goda relationer med företagets intressenter. Således monitoreras KPI:er med syftet att upptäcka anomalier så tidigt som möjligt. Syftet med denna studie är att undersöka affärsvärdet, samt barriärer, av implementation av automatiserad outlier detection för kreditrisk KPI tidsserier i e-handel. Denna forskning är en fallstudie som grundas i tematisk analys av kvalitativ data som samlas in på ett e-handelsföretag.  Vidare visar resultaten av studien att automatisering kan bidra till betydande affärsvärde bland annat till följd av minskade monetära såväl som alternativa kostnader från manuell monitorering, samt potential till bättre kvalitet i monitoreringen och således förbättrade intressentrelationer. Dock tyder resultaten även på att det finns ett flertal hinder för att faktiskt implementera full automatisering såsom brist på tillit till automatisering, tillsammans med åsikter såsom att automatisering kommer bidra till minskad kunskap och kommunikation, och att en implementation skulle vara både tekniskt och logiskt utmanande.

Thesis (MSc)--Stellenbosch University, 2015 / ENGLISH ABSTRACT : In recent years, the use of Lévy processes as a modelling tool has come to be viewed more favourably than the use of the classical Brownian motion setup. The reason for this is that these processes provide more flexibility and also capture more of the ’real world’ dynamics of the model. Hence the use of Lévy processes for financial modelling is a motivating factor behind this research presentation. As a starting point a framework for the LIBOR market model with dynamics driven by a Lévy process instead of the classical Brownian motion setup is presented. When modelling LIBOR rates the use of a more realistic driving process is important since these rates are the most realistic interest rates used in the market of financial trading on a daily basis. Since the financial crisis there has been an increasing demand and need for efficient modelling and management of risk within the market. This has further led to the motivation of the use of Lévy based models for the modelling of credit risky financial instruments. The motivation stems from the basic properties of stationary and independent increments of Lévy processes. With these properties, the model is able to better account for any unexpected behaviour within the market, usually referred to as "jumps". Taking both of these factors into account, there is much motivation for the construction of a model driven by Lévy processes which is able to model credit risk and credit risky instruments. The model for LIBOR rates driven by these processes was first introduced by Eberlein and Özkan (2005) and is known as the Lévy-LIBOR model. In order to account for the credit risk in the market, the Lévy-LIBOR model with default risk was constructed. This was initially done by Kluge (2005) and then formally introduced in the paper by Eberlein et al. (2006). This thesis aims to present the theoretical construction of the model as done in the above mentioned references. The construction includes the consideration of recovery rates associated to the default event as well as a pricing formula for some popular credit derivatives. / AFRIKAANSE OPSOMMING : In onlangse jare, is die gebruik van Lévy-prosesse as ’n modellerings instrument baie meer gunstig gevind as die gebruik van die klassieke Brownse bewegingsproses opstel. Die rede hiervoor is dat hierdie prosesse meer buigsaamheid verskaf en die dinamiek van die model wat die praktyk beskryf, beter hierin vervat word. Dus is die gebruik van Lévy-prosesse vir finansiële modellering ’n motiverende faktor vir hierdie navorsingsaanbieding. As beginput word ’n raamwerk vir die LIBOR mark model met dinamika, gedryf deur ’n Lévy-proses in plaas van die klassieke Brownse bewegings opstel, aangebied. Wanneer LIBOR-koerse gemodelleer word is die gebruik van ’n meer realistiese proses belangriker aangesien hierdie koerse die mees realistiese koerse is wat in die finansiële mark op ’n daaglikse basis gebruik word. Sedert die finansiële krisis was daar ’n toenemende aanvraag en behoefte aan doeltreffende modellering en die bestaan van risiko binne die mark. Dit het verder gelei tot die motivering van Lévy-gebaseerde modelle vir die modellering van finansiële instrumente wat in die besonder aan kridietrisiko onderhewig is. Die motivering spruit uit die basiese eienskappe van stasionêre en onafhanklike inkremente van Lévy-prosesse. Met hierdie eienskappe is die model in staat om enige onverwagte gedrag (bekend as spronge) vas te vang. Deur hierdie faktore in ag te neem, is daar genoeg motivering vir die bou van ’n model gedryf deur Lévy-prosesse wat in staat is om kredietrisiko en instrumente onderhewig hieraan te modelleer. Die model vir LIBOR-koerse gedryf deur hierdie prosesse was oorspronklik bekendgestel deur Eberlein and Özkan (2005) en staan beken as die Lévy-LIBOR model. Om die kredietrisiko in die mark te akkommodeer word die Lévy-LIBOR model met "default risk" gekonstrueer. Dit was aanvanklik deur Kluge (2005) gedoen en formeel in die artikel bekendgestel deur Eberlein et al. (2006). Die doel van hierdie tesis is om die teoretiese konstruksie van die model aan te bied soos gedoen in die bogenoemde verwysings. Die konstruksie sluit ondermeer in die terugkrygingskoers wat met die wanbetaling geassosieer word, sowel as ’n prysingsformule vir ’n paar bekende krediet afgeleide instrumente.

Föränderlig, ofullständig eller osäkerhet kring informationen från företagslåntagare kan skapa betydande utmaningar med kreditrisker för bankerna. På grund av detta ser banker de små och medelstora företagen (SMF) som högre risk. Tidigare forskning tyder på att följder av informationsasymmetri är att banker försvårar företagens tillgång till finansiering. Utifrån detta är syftet med denna studie att beskriva och analysera hur de svenska storbankerna hanterar kreditriskerna vid utlåning till SMF, samt vilka likheter och skillnader det finns mellan bankerna. Med användningen av en kvalitativ datainsamlingsmetod genomfördes semistrukturerade intervjuer med relevanta bankanställda på SEB, Handelsbanken och Swedbank från vilket en tydlig empiri kunde sammanställas. Detta analyserades sedan utifrån teorin om negativt urval och minskad kapitalkostnad samt signaleringsteorin.  Studien fann att de svenska storbankernas strategier för kreditriskhanteringen vid utlåning till SMF utgår från liknande delar. Detta för att både kunna identifiera, förebygga och åtgärda eller minska påverkan från kreditrisker. Skillnaderna mellan bankernas strategier i kreditriskhantering ses i hur de genomför vissa processer och vad de främst fokuserar på vid utlåningen till SMF. Dessa skillnader ses inom vilka externa källor storbankerna använder för informationsinsamling, vilka som har ansvaret för beslutet om kreditvärdighet och om banken använder standardiserade lånevillkor eller inte. / Changing, incomplete or uncertain information from corporate borrowers can create significant credit risk challenges for banks. Because of this, banks see the small and medium-sized enterprises (SMEs) as higher risk. Previous research suggests that consequences of information asymmetry are that banks make it more difficult for companies to access financing. Based on this, the purpose of this study is to describe and analyze how the major Swedish banks manage credit risks when lending to SMEs, as well as what similarities and differences exist between the banks. Using a qualitative data collection method, semi-structured interviews were conducted with relevant bank employees at SEB, Handelsbanken and Swedbank from which a clear empirical record could be compiled. This was analyzed based on the theory of adverse selection and reduced cost of capital, as well as the signalling theory.  The study found that the major Swedish banks strategies for credit risk management when lending to SMEs are based on similar elements. This is to be able to both identify, prevent and remedy or reduce the impact from credit risks. The differences between the banks strategies in credit risk management are seen in how they carry out certain processes and what they mainly focus on when lending to SMEs. These differences are seen in which external sources the big banks are using for information gathering, who is responsible for the decision on creditworthiness and whether the bank uses standardized loan terms or not.

Made available in DSpace on 2016-03-15T19:32:31Z (GMT). No. of bitstreams: 1 Sergio de Jesus.pdf: 1304758 bytes, checksum: d93f4a2c0b7a9f80ad1636906381440d (MD5) Previous issue date: 2011-02-14 / Fundo Mackenzie de Pesquisa / The process of credit risk management of banks is an extremely important activity for the correct identification of the risks inherent in banking to lend funds to third parties. Thus, bank s managers should be alert to best market practices and efficient processes for the timely and accurate identification of credit risks in its loan portfolio and act appropriately to minimize their potential losses. Worldwide, the process of credit risk management has changed to improve the measurement of risks by banks through the new agreement of Capitals - Basel II. Through this new agreement the banks can build and use their own models of credit risk management, with the inclusion of financial and nonfinancial information. Currently, studies demonstrate the importance of intangible assets of enterprises, including those related to intellectual capital, for its ability to generate value and future cash flows for companies. However, due to the difficult identification and measurement of these assets, the current processes for credit risk management still do not include these assets (Intellectual Capital) into their risk analysis. Thus, this study investigates the structure of current models of credit risk management of Brazilian banks, from the Basel II s perspective, to see the possibility to contemplate the intangible assets related to intellectual capital in these models. It was also a scope of the research, a proposal for improving the process of Banco Titânio (unreal name), through the identification, measurement and inclusion of such assets in the process of credit risk management of the bank. The research is exploratory and descriptive and it was conducted in two phases: Initially, the data collection was conducted through an electronic research sent to eight Brazilian banks, and the data were processed by descriptive analysis and content analysis. In the second phase, the research was conducted like a case analysis with the Banco Titânio, and the data were processed through the verification in loco of the current processes of the bank. The results showed that intangible assets related to Intellectual Capital are viewed by managers of banks as important informations to the process of managing credit risk, but because there is no systematic way for its inclusion in the models, these assets still are not included in the processes of credit risk management of Banks that formed the sample; therefore, we proposed a systematic way to improve the management models of banks' credit risk with the inclusion of these assets. / O processo de gerenciamento de risco de crédito dos bancos é uma atividade de extrema importância para a correta identificação dos riscos inerentes à atividade bancária de emprestar recursos financeiros a terceiros. Dessa forma, os gestores dos bancos precisam estar atentos às melhores práticas de mercado e ter em mãos processos eficientes para a tempestiva e correta identificação dos riscos de crédito de sua carteira de empréstimos e agir de maneira adequada para minimizar suas possíveis perdas. Mundialmente, o processo de gerenciamento de risco de crédito passa por significativas mudanças de forma a melhorar a mensuração de riscos por parte dos bancos, devido ao novo acordo de capitais da Basileia II. Segundo este novo acordo, os bancos podem construir e utilizar modelos próprios de gerenciamento de riscos de crédito com a inclusão de informações financeiras e não financeiras. Atualmente, estudos demonstram a importância dos ativos intangíveis das empresas, inclusive os relacionados ao Capital Intelectual, por sua capacidade de geração de valor e de fluxos de caixas futuros para as empresas. Porém, em função da difícil identificação e mensuração desses ativos, os processos atuais de gerenciamento de risco de crédito não incluem esses ativos em suas análises. Sendo assim, esse estudo buscou conhecer a estrutura atual dos modelos de gerenciamento de risco de crédito de bancos brasileiros, pela ótica do novo acordo de capitais da Basileia II, de forma a se verificar a possibilidade de se contemplar os ativos intangíveis relacionados ao Capital Intelectual nesses modelos. Também foi escopo do trabalho sugerir uma proposta de aperfeiçoamento do processo do Banco Titânio (nome fictício), com a identificação, mensuração e inclusão desses ativos no processo de gerenciamento de risco de crédito do banco. A pesquisa é descritiva e exploratória e foi conduzida em duas fases: Na primeira fase, a coleta de dados foi efetuada por meio de questionário eletrônico enviado para oito bancos brasileiros, sendo que os dados foram tratados por análises descritivas e análises de conteúdo. Na segunda fase da pesquisa, foi efetuada uma análise de caso com o Banco Titânio, sendo que os dados foram tratados por meio da verificação in loco dos processos atuais do banco. Os resultados demonstraram que os ativos intangíveis relacionados ao Capital Intelectual são vistos pelos gestores dos bancos como informações importantes para o processo de gerenciamento de risco de crédito, porém por não existir uma forma sistematizada para sua inclusão nos modelos, esses ativos ainda não são contemplados nos processos de gerenciamento de risco de crédito dos bancos que compuseram a amostra; sendo assim, foi proposta uma sistemática para o aperfeiçoamento dos modelos de gerenciamento de risco de crédito dos bancos com a inclusão desses ativos.