Dissertations / Theses on the topic 'Bank loans Data processing'

This study consists of two essays. The first essay investigates whether non-CEO inside director reputation matters in bank loan contracting. Reputable inside directors (RIDs) can improve borrowers’ financial reporting quality and reduce agency risk in loan contracting. Based on regression analysis of 5,104 loan facilities during 1999-2007 in the U.S., I find that borrowers with reputable inside directors enjoy lower loan interest rate and a smaller number of restrictive covenants, and are less likely to have the loans secured by collateral, compared with borrowers without RIDs. The results still hold after I control for CEO reputation, and address the endogeneity of RIDs and the joint determination of various loan contracting terms. These findings shed new light on the impact of director-level reputation in the context of bank loan market. The second essay investigates whether non-CEO inside directors with reputation incentives affect the effectiveness of a firm’s internal control over financial reporting. Internal control effectiveness is an important indicator of financial reporting quality. Using a large sample of 7,352 firm-year observations from 2004 to 2012, I find that firms with RIDs are less likely to have reported internal control weaknesses (ICWs). I also find that RIDs have a more pervasive impact on account-level ICWs than company-level ICWs. Empirical results also demonstrate that the association between RIDs and ICWs is more pronounced for firms with lower audit quality, higher CEO entrenchment, and higher cost of misreporting. Further test shows that RIDs can help to improve earnings quality through mitigating ICWs. The study results still hold after I control for CEO reputation, employing alternative proxies and estimation methods, and address the potential endogeneity problems of RIDs. The study findings add to the few empirical studies examining the determinants of ICWs and have corporate governance policy implications for regulators by supporting the desirable role of inside directors in terms of efficient contracting.

Thesis (M.S.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Electrical and Computer Engineering, 2009.
Includes bibliographical references.

This study is about whether the money supply in South Africa under a monetary policy regime of inflation‐targeting is exogenously or endogenously determined. The proposition of an exogenous money supply has been offered by monetarists, where the Central Bank determines the quantity of money supplied to the economy and this has a causal influence on income and credit extension. The endogenous money theory is a post‐Keynesian proposition whereby the money creation is determined by banks adjusting their responses to demands for credit‐money from economic agents. The data analysis is from 2000Q1 to 2010Q4 and entails the use of the variables monetary base (MB), domestic credit extension (DCE), M3, and gross national product (GDP). All variables are logged. The empirical tests conducted start with the Augmented Dickey‐Fuller unit root test to determine the variables order of integration. Johansen cointegration tests are done followed by Vector Error‐Correction Models (VECMs) and Granger causality tests to determine whether there is unidirectional or bidirectional causality between variables over the long and short‐run. Based on the results of the testing it was discovered that over the inflation‐targeting regime money supply in South Africa was endogenously determined. Furthermore, the data best supports the Accommodationist analysis of endogenous money as opposed to that of Structuralism and Liquidity Preference
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First part of this thesis presents the design, validation, and implementation of an Orthogonal Frequency Division Multiplexing (OFDM) transmitter and receiver on a Cyclone II FPGA chip using DSP builder and Quartus II high level design tools. The resources in terms of logical elements (LE) including combinational functions and logic registers allocated by the model have been investigated and addressed. The result shows that implementing the basic OFDM transceiver allocates about 14% (equivalent to 6% at transmitter and 8% at receiver) of the available LE resources on an Altera Cyclone II EP2C35F672C6 FPGA chip, largely taken up by the FFT, IFFT and soft decision encoder. Secondly, a new wavelet-based OFDM system based on FDPP-DA based channel estimation is proposed as a reliable ECG Patient Monitoring System, a Personal Wireless telemedicine application. The system performance for different wavelet mothers has been investigated. The effects of AWGN and multipath Rayleigh fading channels have also been studied in the analysis. The performances of FDPP-DA and HDPP-DA-based channel estimations are compared based on both DFT-based OFDM and wavelet-based OFDM systems. The system model was studied using MATLAB software in which the average BER was addressed for randomized data. The main error differences that reflect the quality of the received ECG signals between the reconstructed and original ECG signals are established. Finally a DA-based architecture for 1-D iDWT/DWT based on an OFDM model is implemented for an ECG-PMS wireless telemedicine application. In the portable wireless body transmitter unit at the patient site, a fully Serial-DA-based scheme for iDWT is realized to support higher hardware utilization and lower power consumption; whereas a fully Parallel-DA-based scheme for DWT is applied at the base unit of the hospital site to support a higher throughput. It should be noted that the behavioural level of HDL models of the proposed system was developed and implemented to confirm its correctness in simulation. Then, after the simulation process the design models were synthesised and implemented for the target FPGA to confirm their validation.

First part of this thesis presents the design, validation, and implementation of an Orthogonal Frequency Division Multiplexing (OFDM) transmitter and receiver on a Cyclone II FPGA chip using DSP builder and Quartus II high level design tools. The resources in terms of logical elements (LE) including combinational functions and logic registers allocated by the model have been investigated and addressed. The result shows that implementing the basic OFDM transceiver allocates about 14% (equivalent to 6% at transmitter and 8% at receiver) of the available LE resources on an Altera Cyclone II EP2C35F672C6 FPGA chip, largely taken up by the FFT, IFFT and soft decision encoder. Secondly, a new wavelet-based OFDM system based on FDPP-DA based channel estimation is proposed as a reliable ECG Patient Monitoring System, a Personal Wireless telemedicine application. The system performance for different wavelet mothers has been investigated. The effects of AWGN and multipath Rayleigh fading channels have also been studied in the analysis. The performances of FDPP-DA and HDPP-DA-based channel estimations are compared based on both DFT-based OFDM and wavelet-based OFDM systems. The system model was studied using MATLAB software in which the average BER was addressed for randomized data. The main error differences that reflect the quality of the received ECG signals between the reconstructed and original ECG signals are established. Finally a DA-based architecture for 1-D iDWT/DWT based on an OFDM model is implemented for an ECG-PMS wireless telemedicine application. In the portable wireless body transmitter unit at the patient site, a fully Serial-DA-based scheme for iDWT is realized to support higher hardware utilization and lower power consumption; whereas a fully Parallel-DA-based scheme for DWT is applied at the base unit of the hospital site to support a higher throughput. It should be noted that the behavioural level of HDL models of the proposed system was developed and implemented to confirm its correctness in simulation. Then, after the simulation process the design models were synthesised and implemented for the target FPGA to confirm their validation.

Bibliografia: p. 48-51
TCC (especialização em Web Intelligence & Data Analytics) - Centro de Referência em Inteligência Empresarial (Universidade Federal do Rio de Janeiro), Rio de Janeiro, 2015.
O Banco Nacional de Desenvolvimento Econômico e Social (BNDES) é hoje o principal instrumento de financiamento de longo prazo para realização de investimentos em todos os segmentos econômicos no Brasil. Buscando atender a uma parcela crescente do empresariado nacional, nos últimos anos o BNDES tem aumentado a quantidade de operações com micro, pequenas e médias empresas, através dos agentes financeiros parceiros, que analisam e encaminham a solicitação de projeto ao banco. Essa estrutura não permite que o BNDES tenha um contato maior com o cliente final, o que levou o banco a estabelecer vários canais de comunicação de forma a atender as demandas desse público, como Serviço de Informação ao Cidadão (SIC), Central de atendimento, Ouvidoria, portal institucional e etc. A grande quantidade de informações gerada através desses canais está dispersa na organização, o que implica na falta de um repositório central que disponibilize essas informações, fazendo com que o banco não conheça de forma estruturada o seu próprio capital de relacionamento. Neste trabalho, buscou-se relacionar o big data, o capital de relacionamento e a gestão desse capital através da ferramenta tecnológica denominada CRM. O objetivo principal do projeto é integrar as bases com os dados de relacionamento do Banco, através da aplicação do modelo de ecossistema big data, para obter uma visão global de todas as ações de relacionamento realizadas com os clientes e clientes potenciais, com o fim de orientar as ações futuras da instituição. Com a implementação do projeto pretende-se conhecer as interações do cliente com o BNDES, independentemente do canal de comunicação utilizado; oferecer produtos e serviços que se adequem às necessidades do cliente; acompanhar mudanças no perfil e identificar oportunidades de atuação junto aos clientes. Pretende-se também, a partir da base de dados, gerar produtos, tanto internos como externos, e ações inovadoras junto ao cliente. O projeto será implantado por fases, visto que todos os canais de comunicação com o cliente serão integrados ao sistema. Apresentam-se também indicadores para o projeto, uma proposta de governança e uma breve explicação do que será realizado em cada fase do processo de implementação do ecossistema de big data no BNDES.
The National Bank of Development (BNDES) is currently the main long-term financing instrument for investments in all economic sectors in Brazil. Seeking to meet a growing share of the national business, in recent years BNDES has increased the amount of lending to micro, small and medium enterprises through partner financial agents, which analyze and send the financial resource request to the bank. This structure does not allow the BNDES has greater contact with the end customer, which led the bank to establish multiple communication channels to meet the demands of the public, as the Information Service to Citizens (SIC), Call Center, Ombudsman, institutional portal and etc. The large amount of information generated through these channels is dispersed in the organization, which implies the lack of a central repository where this information could be provided, causing the bank does not know their own relationship capital in a structured way. In this study, we relate the big date, the relationship capital and the management of the relationship capital through technological tool called CRM. The main objective of the project is to integrate the bases with relationship data from the Bank, through the application of big data ecosystem model to get an overview of all relationship activities carried out with customers and potential customers, in order to guide future actions of the institution. The implementation of the project aims to meet customer interactions with BNDES, regardless of the communication channel used; offer products and services to answer the customer's needs; monitor changes in the profile and identify performance opportunities with customers. It is also intended, from the database, generate products, both internal and external, and innovative actions with the client. The project will be implemented in stages, as all channels of communication with the client will be integrated into the system. Are also presented indicators for the project, a proposal for governance and a brief explanation of what will be done in each phase of the implementation process of the big data ecosystem in BNDES.

碩士
大葉大學
國際企業管理學系碩士在職專班
95
This research penetration questionnaire survey and the statistical analysis obtain the following conclusion: 1st, the bank gives the letter verification with to exceed the time limit loans, two presents the negative direction relations; The processing not good creditor's rights mechanism with exceeds the time limit loans, two presents the negative direction rela-tions; Exceeds the time limit loans with the bank management achievements, two pre-sents the negative direction relations. 2nd, the bank gives the letter verification and the bank management achievements, two assumes right now to the relations; The processing not good creditor's rights mechanism and the bank management achievements, two assume right now to the rela-tions. According to analyzes the result, proposed suggested: The strengthening gives the letter verification unit to the bank the risk control mechanism, relaxes the control in ad-dition on the governmental agency regarding the policy, the promotion property nego-tiable securities market development and so on, and constructs the early warning mechanism by the risk management technology, promotes the bank the management achievements.

by Simon Leung Tak-wing, Elmen Li Pak-kee.
Thesis (M.B.A.)--Chinese University of Hong Kong, 1991.
Bibliography: leaves 36-38.
ABSTRACT --- p.ii
TABLE OF CONTENTS --- p.iii
CHAPTER
Chapter I --- INTRODUCTION --- p.1
Chapter II --- IMPORTANCE OF RISK MANAGEMENT IN BANK MANAGEMENT --- p.4
Chapter III --- RESEARCH METHODOLOGY OF THE STUDY --- p.7
Chapter IV --- MANAGEMENT INFORMATION SYSTEM AND TREASURY MANAGEMENT --- p.12
Chapter V --- IMPLICATIONS OF ADOPTING MANAGEMENT INFORMATION SYSTEM --- p.16
Chapter VI --- FINDINGS WITH A FEW SELECTED BANKS IN HONG KONG --- p.21
Chapter VII --- CONCLUSIONS AND OUTLOOK OF MIS IN TREASURY MANAGEMENT --- p.30
BIBLIOGRAPHY --- p.36

JEL Classification: C23, G18, G21, G28, G32
This study analyzes the impact of non-performing loans (NPLs) on credit granted by banks and, consequently, on their management lending policies. An historical review of recent developments in national economies in terms of credit granting and credit quality is presented in this document, along with an analysis of the macroeconomic determinants of NPLs in order to understand the impact of its dynamics in banks’ lending policies and profitability. Furthermore, a perspective of the evolution of regulation on NPLs and the development of the NPLs definition overtime, with the enlargement of the dimensions considered, is also given. Finally, we analyze the measures undertaken by banks to tackle NPLs, in order to evaluate their current situation and the adjustment needed that should be taken regarding the paradigm of banks’ management and the respective business models. Using an unbalanced panel data of quarterly information of 111 banks of the Euro Area, covering the period from 2010 to 2015, and applying a fixed effects model estimated with the Driscoll-Kraay robust approach, we conclude that NPLs show different lagged effects on credit granting. Only after some time of coexistence of simultaneous increase in credit granting and in NPLs, a change in the credit policy occurs. Thus suggesting the existence of rigidity when setting credit policy. Dividing the data into two different groups - countries of Central and Eastern Europe and Peripheral countries (that suffered from financial stress in the period under analysis) – and applying the same approach, we observe significant differences in results between countries.
Este estudo analisa o nível de impacto dos créditos não produtivos na concessão de crédito e, consequentemente, na gestão das políticas de concessão de crédito dos Bancos. É apresentada uma perspetiva histórica dos desenvolvimentos económicos relacionados com a concessão e a qualidade do crédito, acompanhada por uma análise dos fatores determinantes dos créditos não produtivos, de forma a apurar a sua dinâmica nas políticas de crédito e na rendibilidade dos Bancos. Adicionalmente, é apresentada a evolução da regulamentação relativa a créditos não produtivos e do conceito ao longo do tempo, tendo em conta o alargamento das dimensões consideradas. Finalmente, é também realizada uma análise das medidas endereçadas pelos Bancos para lidar com os créditos não produtivos, de forma a aferir o estado atual dos Bancos e a necessidade de ajustamentos relativamente ao paradigma da gestão e dos modelos de negócio dos Bancos. Através da utilização de dados de painel não balanceados e de um modelo de efeitos fixos juntamente com o estimador robusto Driscoll-Kraay, é analisada informação trimestral relativa a 111 Bancos da Área do Euro no período entre 2010 e 2015, concluindo-se que a variável relativa aos créditos não produtivos demonstra um comportamento diferenciado entre os intervalos temporais, o que sugere a existência de uma rigidez na definição da política de crédito. Apenas depois de algum tempo, em que o aumento do crédito coincide com o aumento de créditos não produtivos, existe uma alteração da política de crédito. Dividindo a informação em dois grupos – Países da Europa Central e de Leste e Países Periféricos (que estiveram sob pressão financeira no período em análise) – e aplicando a mesma abordagem permite-nos observar diferenças significativas de resultados entre os países considerados.

The Iberia Margin is an excellent example of a passive rift. Multi-Channel Seismic (MCS) data consisting of the Line 14 reflection profile from the 1997 Iberia Seismic Experiment were processed and interpreted. Enhanced processing attenuated pervasive water-bottom multiple noise. MCS data image an extensional terrain that includes the Ocean-Continent Transition (OCT). The Moho is imaged locally. Extended crust was restored to an unextended state to quantify deformation. Horizontal strain tends to increase seaward along dip; the average strain is 46%. Crustal-thickness data indicate an average crustal thickness of 9.9 km. With certain assumptions regarding the observability of extension, the presence of 'pure shear' exclusively, and initial crustal thickness, there is a major discrepancy between the observed average crustal thickness and the average crustal thickness predicted by observed strain. The only satisfactory explanation is that crust has been removed by asymmetrical extension (simple shear).

This thesis explores the use of unstructured data, and specifically textual data, in providing consumer insights and improving business decisions. The thesis consists of two essays. In essay I, I examine how the linguistic similarity between the language used by reviewers of a product and a prospective customer’s own writing style can be leveraged to assess the match between customers and products. Applying tools from machine learning, Bayesian statistics, and computational linguistics to a large-scale dataset from Yelp, I find that the closer the writing style of a restaurant’s past reviews are to a prospective customer’s writing style, the more likely that customer is to write a review for that restaurant. This effect holds across restaurant types and is driven by the linguistic similarity between the customer’s own reviews and positive past reviews for the restaurant. Further, I find that similarity with respect to words related to leisure (e.g., family, wine, beer, weekend), biology (e.g., eat, life, love), as well as swear words are most influential in creating a match between customers and restaurants. In essay II, I examine whether borrowers consciously or not, leave traces of their intentions, circumstances, and personality traits in the text they write when applying for a loan. I find that this textual information has a substantial and significant ability to predict whether borrowers will pay back the loan above and beyond the financial and demographic variables commonly used in models predicting default. Using text-mining and machine-learning tools to automatically process and analyze the raw text in over 120 thousand loan requests from Prosper.com, an online crowdfunding platform, I find that including the textual information in the loan significantly helps predict loan default and can have substantial financial implications. I find that loan requests written by defaulting borrowers are more likely to include words related to their family, mentions of God, the borrower’s financial and general hardship, pleading lenders for help, and short-term focused words. I further observe that defaulting loan requests are written in a manner consistent with the writing style of extroverts and liars.