Since the regulatory framework Basel II was implemented in 2007, banks have been allowed to develop internal risk models for quantifying the capital requirement. By using data on retail non-performing loans from Hoist Finance, the thesis assesses the Advanced Internal Ratings-Based approach. In particular, it focuses on how banks active in the non-performing loan industry, can risk-classify their loans despite limited data availability of the debtors. Moreover, the thesis analyses the effect of the maximum-recovery period on the capital requirement. In short, a comparison of five different mathematical models based on prior research in the field, revealed that the loans may be modelled by a two-step tree model with binary logistic regression and zero-inflated beta-regression, resulting in a maximum-recovery period of eight years. Still it is necessary to recognize the difficulty in distinguishing between low- and high-risk customers by primarily assessing rudimentary data about the borrowers. Recommended future amendments to the analysis in further research would be to include macroeconomic variables to better capture the effect of economic downturns. / Sedan det regulatoriska ramverket Basel II implementerades 2007, har banker tillåtits utveckla interna riskmodeller för att beräkna kapitalkravet. Genom att använda data på fallerade konsumentlån från Hoist Finance, utvärderar uppsatsen den avancerade interna riskklassificeringsmodellen. I synnerhet fokuserar arbetet på hur banker aktiva inom sektorn för fallerade lån, kan riskklassificera sina lån trots begränsad datatillgång om låntagarna. Dessutom analyseras effekten av maximala inkassoperioden på kapitalkravet. I sammandrag visade en jämförelse av fem modeller, baserade på tidigare forskning inom området, att lånen kan modelleras genom en tvåstegs trädmodell med logistisk regression samt s.k. zero-inflated beta regression, resulterande i en maximal inkassoperiod om åtta år. Samtidigt är det värt att notera svårigheten i att skilja mellan låg- och högriskslåntagare genom att huvudsakligen analysera elementär data om låntagarna. Rekommenderade tillägg till analysen i fortsatt forskning är att inkludera makroekonomiska variabler för att bättre inkorporera effekten av ekonomiska nedgångar.

This thesis evaluates the regulation of credit institutions. Its aim is to answer the question of how the regulation of credit institutions evolved and how this development influenced current regulation. This thesis examines the potential of credit institution regulation to prevent further financial crises. At first the author deals with the development of the market of financial services and subsequently with the development of regulation of credit institutions. In the first part the author analyses the positive and negative aspects of each piece of legislation, reasons for their adoption, changes or their further use. This thesis deals particularly with capital adequacy requirements. It analyses their gradual development and reason for their amendments, especially in the context of the recent financial crisis. The author concludes that that current se-up of the credit institution regulation and its expected development puts too much emphasis in increasing of the capital adequacy requirements. The author sees this aspect especially in the directive on capital requirements from 2013 which presents new buffers that the credit institutions are required to hold and in the resolution directive from 2014 which adds new, yet similar requirements. The author particularly disagrees with the assessment of...

<p>Vid tidpunkten för disputationen var följande delarbete opublicerat: delarbete 3 accepterat.</p><p>At the time of the doctoral defence the following paper was unpublished: paper 3 accepted.</p>

Relations of Central bank to Commercial banks The purpose of my thesis is to analyse relations among central bank and commercial banks in current view with emphasising on situation in the Czech Republic. This analysis is a critical appraisal of issues in relation to current legislation, and last but not least also the planned changes, which are currently under discussion. The thesis is divided into five chapters with introduction and abstract. Chapter One is introductory and defines basic terminology used in the thesis like banking system, central bank and commercial banks. This chapter is subdivided into four parts. Part One describes central bank and banking system. Part Two describes central bank, its position, activity and tools. Part Third is focused on commercial banks. Final part deals with trends in the development of the banking sector. Chapter Two characterises subjects of banking system in the Czech Republic and is divided into two parts. Part One outlines organizational structure of the CNB and its main functions. Part Two outlines organizational structure of commercials banks in the Czech Republic. Chapter Three concentrates on banking regulation and supervision and its division. Part One analyzes arguments for and against bank regulation. Part Two is focused on banking regulation and...

The importance of sound financial risk management has become increasingly emphasised in recent years, especially with the financial crisis of 2007-08. The Basel Committee sets the international standards and regulations for banks and financial institutions, and in particular under market risk, they prescribe the internal application of the measure Value-at-Risk. However, the most established non-parametric Value-at-Risk model, historical simulation, has been criticised for some of its unrealistic assumptions. This thesis investigates alternative approaches for estimating non-parametric Value-at-Risk, by examining and comparing the capability of three counterbalancing weighting methodologies for historical simulation: an exponentially decreasing time weighting approach, a volatility updating method and, lastly, a more general weighting approach that enables the specification of central moments of a return distribution. With real financial data, the models are evaluated from a performance based perspective, in terms of accuracy and capital efficiency, but also in terms of their regulatory suitability, with a particular focus on the Swedish market. The empirical study shows that the capability of historical simulation is improved significantly, from both performance perspectives, by the implementation of a weighting methodology. Furthermore, the results predominantly indicate that the volatility updating model with a 500-day historical observation window is the most adequate weighting methodology, in all incorporated aspects. The findings of this paper offer significant input both to existing research on Value-at-Risk as well as to the quality of the internal market risk management of banks and financial institutions. / Betydelsen av sund finansiell riskhantering har blivit alltmer betonad på senare år, i synnerhet i och med finanskrisen 2007-08. Baselkommittén fastställer internationella normer och regler för banker och finansiella institutioner, och särskilt under marknadsrisk föreskriver de intern tillämpning av måttet Value-at-Risk. Däremot har den mest etablerade icke-parametriska Value-at-Risk-modellen, historisk simulering, kritiserats för några av dess orealistiska antaganden. Denna avhandling undersöker alternativa metoder för att beräkna icke-parametrisk Value-at‑Risk, genom att granska och jämföra prestationsförmågan hos tre motverkande viktningsmetoder för historisk simulering: en exponentiellt avtagande tidsviktningsteknik, en volatilitetsuppdateringsmetod, och slutligen ett mer generellt tillvägagångssätt för viktning som möjliggör specifikation av en avkastningsfördelnings centralmoment. Modellerna utvärderas med verklig finansiell data ur ett prestationsbaserat perspektiv, utifrån precision och kapitaleffektivitet, men också med avseende på deras lämplighet i förhållande till existerande regelverk, med särskilt fokus på den svenska marknaden. Den empiriska studien visar att prestandan hos historisk simulering förbättras avsevärt, från båda prestationsperspektiven, genom införandet av en viktningsmetod. Dessutom pekar resultaten i huvudsak på att volatilitetsuppdateringsmodellen med ett 500 dagars observationsfönster är den mest användbara viktningsmetoden i alla berörda aspekter. Slutsatserna i denna uppsats bidrar i väsentlig grad både till befintlig forskning om Value-at-Risk, liksom till kvaliteten på bankers och finansiella institutioners interna hantering av marknadsrisk.

This thesis investigates three different techniques for estimating loss given default of non-performing consumer loans. This is a contribution to a credit risk evaluation model compliant with the regulations stipulated by the Basel Accords, regulating the capital requirements of European financial institutions. First, multiple linear regression is applied, and thereafter, zero-and-one inflated beta regression is implemented in two versions, with and without Bayesian inference. The model performances confirm that modeling loss given default data is challenging, however, the result shows that the zero-and-one inflated beta regression is superior to the other models in predicting LGD. Although, it shall be recognized that all models had difficulties in distinguishing low-risk loans, while the prediction accuracy of riskier loans, resulting in larger losses, were higher. It is further recommended, in future research, to include macroeconomic variables in the models to capture economic downturn conditions as well as adopting decision trees, for example by applying machine learning. / Detta examensarbete undersöker tre olika metoder för att estimera förlusten vid fallissemang för icke-presterande konsumentlån. Detta som ett bidrag till en kreditrisksmodell i enlighet med bestämmelserna i Baselregelverken, som bland annat reglerar kapitalkraven för europeiska finansiella institut. Inledningsvis tillämpas multipel linjär regression, därefter implementeras två versioner av utvidgad betaregression, med och utan bayesiansk inferens. Resultatet bekräftar att modellering data för förlust givet fallissemang är utmanande, men visar även att den utvidgade betaregressionen utan bayesiansk inferens är bättre de andra modellerna. Det ska dock tilläggas att alla modeller visade svårigheter att estimera lån med låg risk, medan tillförlitligheten hos lån med hög risk, vilka generellt sett medför större förluster, var högre. Vidare rekommenderas det för framtida forskning att inkludera makroekonomiska variabler i modellerna för att fånga ekonomiska nedgångar samt att implementera beslutsträd, exempelvis genom applicering av maskininlärning.