Since the 2008 financial crisis, the interest for the subject area of modelling non-maturity deposits has been growing quickly. The area has been widely analysed from the perspective of a traditional bank where customers foremost have transactional and salary deposits. However, in recent year the Swedish banking sector has become more digitized. This has opened up opportunities for more niche banking actors to establish themselves on the market. Therefore, this study aims to examine how the theories developed and previously used in modelling liquidity volumes at traditional banks can be used at a niche bank focused on savings and investments. In this study the topics covered are short-rate modelling using Vasicek's model, liquidity volume modelling using SARIMA and SARIMAX modelling as well as liquidity risk modelling using an approach developed by Kalkbrener and Willing. When modelling the liquidity volumes the data set was divided depending on account and customer type into six groups, for four out of these the models had lower in and out of set prediction errors using SARIMA models for only two of the six models were there improvements made to the in and out of set prediction error using SARIMAX models. Finally, the resulting minimization of liquidity volume forecasting 5 years in the future gave reasonable and satisfactory results. / Sedan finanskrisen 2008 har intresset kring ämnesområdet gällande modellering av inlåningsvolymer utan en kontrakterad förfallodag ökat snabbt. Området har analyserats i stor utsträckning från perspektivet av en traditionell bank där kunder har framförallt transaktions- och lönekonton. De senaste åren har den Svenska banksektorn blivit mer digitaliserad. Detta har öppnat upp möjligheter för nischbanker att etablera sig på marknaden. Därför ämnar denna studie att undersöka hur teorier som har utvecklats och tidigare använts på traditionella banker för att modellera likviditetsvolymer kan användas på en nischbank som är fokuserad på sparande och investeringar. I denna studie modelleras korträntor med Vasicek's modell, likviditetsvolymer med SARIMA och SARIMAX modeller och likviditetsrisk med en modell utvecklad av Kalkbrener och Willing. För modelleringen av likviditetsvolymer delades likviditetsdatan upp i sex grupper baserat på konto- och kund typ. För fyra av dessa data set gav SARIMA-modeller lägre prediktionsfel och endast för två av de sex grupperna gav SARIMAX-modeller bättre resultat. Slutligen så gav den resulterande minimeringen av nödvändiga likviditetsvolymer på en 5 årig horisont rimliga och tillfredsställande resultat.

Data governance frameworks are critical to reducing operational costs and risks in the financial industry. Corporate data managers face challenges when implementing data governance frameworks. The purpose of this multiple case study was to explore the strategies that successful corporate data managers in some banks in the United States used to implement data governance frameworks to reduce operational costs and risks. The participants were 7 corporate data managers from 3 banks in North Carolina and New York. Servant leadership theory provided the conceptual framework for the study. Methodological triangulation involved assessment of nonconfidential bank documentation on the data governance framework, Basel Committee on Banking Supervision's standard 239 compliance documents, and semistructured interview transcripts. Data were analyzed using Yin's 5-step thematic data analysis technique. Five major themes emerged: leadership role in data governance frameworks to reduce risk and cost, data governance strategies and procedures, accuracy and security of data, establishment of a data office, and leadership commitment at the organizational level. The results of the study may lead to positive social change by supporting approaches to help banks maintain reliable and accurate data as well as reduce data breaches and misuse of consumer data. The availability of accurate data may enable corporate bank managers to make informed lending decisions to benefit consumers.

This dissertation presents a liquidity stress-testing model for evaluating liquidity and systemic risk in banks from developed and emerging economies respectively. The model further relies on simulations to generate liquidity buffer losses for both a non-crisis and crisis period as well. The emerging economy is represented by South Africa (SA) and the developed economy by the United Kingdom (henceforth UK). The Liquidity Stress Tester model (LST) has been successfully applied to both the Dutch and UK markets in previous research. The model's flexibility and adaptability allows it to assess different banking systems and different reactions (buffer restoration and leverage targeting) of participants within these milieus. The LST considers feedback effects arising from bank reactions and allows for the assessment of severely stressed haircuts and systemic risk increases caused by reputation degradation and increased contagion from other banks. Losses stemming from the second round effects of a liquidity event are explored through the reactions conducted by banks in the banking system. The study conducts a review of liquidity risk models utilised in previous research. Characteristics of these models and the data they used are highlighted, shedding light on the advantages and shortcomings of these models. Possible restrictions in liquidity risk management are also explored. The study discusses the relevance of the South African/UK economies' comparison, as well as the selected periods chosen for investigation. To assist further research with the LST, the study illustrates and discusses how it is modelled and developed in Microsoft Office Excel. The results obtained illustrate the potential severity of second round feedback effects of a liquidity event on liquidity positions in banks. The effects of mitigating actions conducted by banking institutions reacting to initial liquidity stress shocks are explored, as well as the way these actions could potentially affect second round effects on banks. The analysis and discussion of simulated results attempts to isolate and identify characteristics of economies and periods used that may have contributed to specific liquidity events. The study concludes with a summary of the research and suggestions for possible future work and development using the LST. / MCom (Risk Management), North-West University, Potchefstroom Campus, 2013

This dissertation presents a liquidity stress-testing model for evaluating liquidity and systemic risk in banks from developed and emerging economies respectively. The model further relies on simulations to generate liquidity buffer losses for both a non-crisis and crisis period as well. The emerging economy is represented by South Africa (SA) and the developed economy by the United Kingdom (henceforth UK). The Liquidity Stress Tester model (LST) has been successfully applied to both the Dutch and UK markets in previous research. The model's flexibility and adaptability allows it to assess different banking systems and different reactions (buffer restoration and leverage targeting) of participants within these milieus. The LST considers feedback effects arising from bank reactions and allows for the assessment of severely stressed haircuts and systemic risk increases caused by reputation degradation and increased contagion from other banks. Losses stemming from the second round effects of a liquidity event are explored through the reactions conducted by banks in the banking system. The study conducts a review of liquidity risk models utilised in previous research. Characteristics of these models and the data they used are highlighted, shedding light on the advantages and shortcomings of these models. Possible restrictions in liquidity risk management are also explored. The study discusses the relevance of the South African/UK economies' comparison, as well as the selected periods chosen for investigation. To assist further research with the LST, the study illustrates and discusses how it is modelled and developed in Microsoft Office Excel. The results obtained illustrate the potential severity of second round feedback effects of a liquidity event on liquidity positions in banks. The effects of mitigating actions conducted by banking institutions reacting to initial liquidity stress shocks are explored, as well as the way these actions could potentially affect second round effects on banks. The analysis and discussion of simulated results attempts to isolate and identify characteristics of economies and periods used that may have contributed to specific liquidity events. The study concludes with a summary of the research and suggestions for possible future work and development using the LST. / MCom (Risk Management), North-West University, Potchefstroom Campus, 2013

The interest in modeling non-maturing deposits has skyrocketed ever since thefinancial crisis 2008. Not only from a regulatory and legislative perspective,but also from an investment and funding perspective.Modeling of non-maturing deposits is a very broad subject. In this thesis someof the topics within the subject are investigated, where the greatest focus inon the modeling of the deposit volumes. The main objective is to providethe bank with an analysis of the majority of the topics that needs to be cov-ered when modeling non-maturing deposits. This includes short-rate model-ing using Vasicek’s model, deposit rate modeling using a regression approachand a method proposed by Jarrow and Van Deventer, volume modeling usingSARIMA, SARIMAX and a general additive model, a static replicating port-folio based on Maes and Timmerman’s to model the behaviour of the depositaccounts and finally a liquidity risk model that was suggested by Kalkbrenerand Willing. All of these models have been applied on three different accounttypes: private transaction accounts, savings accounts and corporate savingsaccounts.The results are that, due to the current market, the static replicating portfoliodoes not achieve the desired results. Furthermore, the best volume model forthe data provided is a SARIMA model, meaning the effect of the exogenousvariables are seemingly already embedded in the lagged volume. Finally, theliquidity risk results are plausible and thus deemed satisfactory. / Intresset för att modellera inlåningsvolymer utan en kontrakterad förfallodaghar ökat markant sedan finanskrisen 2008. Inte bara sett utifrån ett perspek-tiv att uppfylla krav som ställs av tillsynsmyndigheter, men också sett utifrånbankens investerings-och finansieringsperspektiv.Målet med det här arbetet är att förse banken med en analys av majoritetenav de olika områdena som man behöver ta hänsyn till när man ska model-lera inlåningar utan förfallodatum, men med ett fokus på volymmodellering.I den här rapporten modelleras räntor (kortränta och kontoränta), kontovoly-merna, kontobeteendet samt likviditetsrisken. Detta görs med hjälp av Vasicekför korträntan, en regressionsmetod samt en metod som föreslagits av Jarrowoch Van Deventer för kontoräntan, SARIMA, SARIMAX och en generell ad-ditiv regressionsmetod för volymerna, en statisk replikeringsportfölj baseradpå Maes och Timmermans modell för att imitera kontona och slutligen så mo-delleras likviditetsrisken med ett ramverk som föreslagits av Kalkbrener ochWilling. Alla dessa nämnda modeller appliceras, där det är möjligt, på de treolika kontotyperna: privatkonton, sparkonton samt företagssparkonto.Resultatet är att räntemodelleringen samt replikeringsportföljen inte ger ade-kvata resultat på grund av den rådande marknaden. Vidare så ger en SARIMA-modell den bästa prediktionen, vilket gör att slutsatsen är att andra exogenavariabler redan är inneslutna i den fördröjda volymvariabeln. Avslutningsvisså ger likviditetsmodellen tillfredsställande resultat och antas vara rimlig.