Risk Management is one of the challenging tasks in financial industries. In banking system risk occurs due to internal and external factors, like government intervention with fiscal policies. To measure the efficiency of banks we need to identify the risk factors in banks. Impact of this risk factors is disentangle from overall efficiency. Stochastic Frontier Analysis (SFA) and (Data Envelopment Analysis)are two major techniques used to measure the efficiency of organizational units where multiple inputs and outputs makes comparison difficult. This thesis explains about the DEA analysis, how to assess and disentangle the risk factors effect from overall efficiency in different stages. DEAP,EMS and QSB are some of the computer oriented programmes useful in calculating efficiency. SAS is also one of the major high level programming language useful to solve linear and non-linear programming techniques. The ultimate objective is to identify which banks were seriously affecting with this risk factors.
This book provides a model of bankruptcy prediction conditional on financial ratios being evaluated for banks when they need funds. Credit risk is of great concern for most banks as credit risk is that risk that can easily and most likely prompts banks failure. Adequately managing credit risk in financial institutes is critical for survival and growth of the banking industry. Addressing these concerns for enhanced financial decision making in this analysis Artificial Neural Network (ANN) has been used for prediction and estimation of ratios. The sample size selected is a few major players both in the government and private sector of Indian Banking Industry. The analysis incorporates various ratios and then relates them to examine the explanatory capabilities of the financial ratios to suggest the position of the bank. Construction of the basic ratios into ratio pillars is a vital ingredient of the basic work done prior to deployment of neural network.
In 2003, the new banking law No. 88/2003 was promulgated. This law was meant to foster the consolidation of the sector through mergers and acquisitions, and abolished the distinction between commercial, business and specialized banks. Interested by this new development, we analyzed the Egyptian banking sector’s efficiency and productivity over the period 2004-2009 through the non-parametric technique DEA, to measure banks’ efficiency, and the Malmquist Productivity Indexes to estimate productivity changes. Finally we examined, through a GLS regression, possible correlates or determinants of efficiency, such as stability, ownership & control, size, market power, risk, and other bank characteristics. Finally we give policy recommendations to foster the consolidation and the liberalization of the sector.
Indian banking system has well developed organization in the country. Entrepreneurs and creative thinker were established the most of the banks in India. In the pre –independence era, they provided financial support to the farmers, business community, traders and industrialists in India. At present, largest commercial bank in the country is State Bank of India. . Banking sector in India has seen lots of positive developments in the last decade. The policy makers in India have made lot of efforts to improve the regulation in the banking sector. The banking sector evaluates positive results in growth, profitability, non- performing assets, credit risk and funds management. In this scenario, some of the banks have recognized innovation and growth aspects. Banking industry in India has to strengthen them to support to the Indian economy.
'Analysis on credit concentration risk and NPA in Bank's Portfolio' analyzes the credit portfolio composition of a large and medium sized commercial bank in India to understand the nature and dimensions of industry –wise credit concentration risk and also evaluates its influence on Non-Performing Assets of the banks. The required data for this study was collected from industry-wise loan exposures of Indian Overseas Bank and yearly NPAs of the bank. The industry-wise credit concentration risk for each year is calculated by using Herfindahl-Hirschman Index (HHI index). Multiple Linear Regression Analysis was run on SPSS 19.0 to quantify the relationship between the credit concentration risk and Non-Performing Assets of the commercial bank. The results indicate that there exists a strong positive relationship between the industry-wise concentration risk and NPA of the commercial bank. Hence it is highly desirable for the commercial banks to have a diversified portfolio in order to reduce their Non –Performing Assets.
Commitment to prudent lending is an important and current issue of discussion in the global banking system today. Banking prudence and efficiency to manage their risks in different business cycle and environment would help to alleviate crises and losses. The objectives of the study were to examine the credit risk management techniques applied by micro-finance institutions in Kenya; to find out how micro-finance institutions analyze the credit worthiness of their customers and to determine the credit risk management process utilized by micro-finance institutions (MFIs). From 35 MFIs sampled, this study found out that credit criteria, the six c’s of credit (character, capacity, capital, condition, collateral and common sense), diversification of loan services, credit reminder, training and development of staff, collateralizations as well as guidelines for credit approval process are important techniques to manage credit risk. The completion of this study is of great significance as it helps micro-finance institutions reduce the costs associated with managing credit risks. Good risk management techniques enable companies to seize opportunities as well as prevent disasters.
The current situation of the financial sector clearly shows us that the ways of predicting the future losses, along with their monitoring and management, are rather underdeveloped or being taken as separate mathematical models, thus using only quantitative analysis without the qualitative one. The role of the risk-management system cannot be underestimated, especially after (and during) the world economy crisis. The current problem of the Russian risk-management system is the low power given to the risk-management personnel. That’s why one of the key points to the better risk evaluation is the possibility of the risk-management department to report directly to the board of directors, not to the management of the bank, as it is the shareholders’ money to lose. The goal is to find the proper balance between the risk and the profit while presenting the transparency of the business. It should be done in a clear way, better an algorythm, which can be applied in many organisations by the starting employees. This book presents a sample of such an algorythm.
The aim of this book is in the first place to show how to deal with a credit risk, and which tools the Czech banking sector uses to minimize it (based on the adequate literature and own experience). In the second place, the aim is to find out the reliable logit model estimating the probability of default during the short period based on available data (in the time of economic crisis in the Czech environment). In the first part of the book I am describing the development of Non-performing loans before and during the current financial crisis together with the results of the CNB''s stress tests. Next chapter describes the credit risk with the emphasis on the credit monitoring, including the most frequently used monitoring tools. Final part turns us to the most important EWM model. The strictly confidential banking data (credit account turnovers, credit contract), together with data from the financial statements and CRU registry are the inputs to the Model. The Model should work as an early warning signal detection thanks to the estimate of probability of default (more specifically the watch loan classification or worse) during the next three months.
Banking sector is suffering a huge chunk of non-performing loan in Pakistan, Due to this profitability and survivals of banks are at risk in Pakistan. “A large number of banks in economies like Thailand, Indonesia, Japan and Mexico experienced a high level of non-performing loan and has faced a significant increase in credit risk during the financial and banking crisis. Due to these financial and economic crises many banks closed down their operations in Indonesia and Thailand (Ahmad & Arif, 2007)”. Keeping in consideration to increase in non-performing in Pakistan, study will explore the relationship between Credit Risk and performance of banking sector.By providing reliable data and evidences about the credit risk and its consequences on banks performance in Pakistan, it is clear that how this important factor non- performing loans (NPLs) is influencing the performance of the banks in Pakistan. It also contributes in addressing the problem and finding a research based solution to the problem of non-performing loans in Pakistani banking context. It also contributes efforts toward the financial risk management strategies and techniques.
The improvement of the overall fund of the banking system depends profoundly on the efficiency and performance of the banking sector. With the advent of more banks into the banking foray, it has become mandatory for Indian banking structure to adopt several norms and practices of those prevalent in developed economies. This ultimately leads to the bankruptcy or merger of banks and knows light and several hidden information. Hence, the book evaluates the Fund management of Banking Sector in Indian Scenario. Even though the banks have achieved tremendous growth in various fields, it also confronted with the problem of high operational costs. Hence, the financial system needs some more improvement through meticulous attention to restore the problems.
This is an academic article that contains the real life day to day working experience of different tasks in Credit Department of Dhaka Bank Limited, KDA Avenue Branch. Provided detailed information about the organization with its company profile, Corporate Vision and Mission, product & service and resources.Discussed about the overall credit risk grading processes of DBL which starts with the branch and done fully under head office’s credit department.The whole system has been described elaborately keeping in mind the most important segments. In addition the diagrams Credit Risk Grading score sheet add a clear understanding of the system.
This book provides a model of Z Score prediction conditional on internal parameters of Z Score. Z Score is being evaluated for banks when they need funds. Credit risk is of great concern for most banks as credit risk is that risk that can easily and most likely prompts banks failure. Adequately managing credit risk in financial institutes is critical for survival and growth of the banking industry. Addressing these concerns for enhanced financial decision making in this analysis Artificial Neural Network (ANN) has been used for prediction and estimation of internal ratios for Z score. The sample size selected is a few major players both in the government and private sector of Indian Banking Industry. The analysis incorporates Z Score values to estimate the terms, viability and period for credit.
This book discusses on the ‘Corporate Credit Risk of Indian Manufacturing Companies: Towards an Early Warning System’. Devised for the analysis of financial health of the Indian manufacturing firms, it aims to pave a path towards designing a EWS by identifying the essential variables and hence assess the credit worthiness of the firms and avert a default. Most of the research on bankruptcy or default is done for the developed nations whereas it’s meagre in India due to lack of data and proper bankruptcy laws. In the present study the popular and robust Z score model is developed for the listed manufacturing firms in India and then DEA is used to assess their technical efficiencies. The rating agencies can incorporate these technical efficiencies in their ratings methodologies. Finally the study looks into the impact of macroeconomic factors on the firms’ financial health. This book is meant for those who are interested in learning about the financial health of listed firms i.e. Banks, Financial Institutions and Investors, for those undertaking research in Credit risk, CRAs and for the policy makers.
Co-operative banks are an integral part of the Indian financial system. They comprise urban co-operative banks and rural co-operative credit institutions. Co-operative banks in India are more than 100 years old. UCBs also referred to as primary co-operative banks, play an important role in meeting the growing credit needs of urban and semi-urban areas of the country. UCBs mobilize savings from the middle and lower income groups and purvey credit to small borrowers, including weaker sections of the society. Scheduled UCBs are under closer regulatory and supervisory framework of the RBI. Though much smaller as compared to scheduled commercial banks, co-operative banks constitute an important segment of the Indian banking system. They have traditionally played an important role in creating banking habits among the lower and middle-income groups in urban areas and also in strengthening the rural credit delivery system. This book – focusing on management of UCBs – in India, including recent reforms. Besides, it includes a case study of financial efficiency and the working of UCBs in the Indian state of Andhra Pradesh of Chittoor District.
The concept of cost efficiency was introduced by Farrell (1957) as the ratio of factor minimal cost to the actual cost. Unlike technical efficiency, the cost efficiency measure takes into consideration changes in input mix also. The Farrell cost efficiency measure was extended by Fare et.al (1984) for the case of multiple inputs and outputs. Solving one linear programming problem for one production unit, the factor minimal cost can be calculated which is called in this study as ‘Farrell Cost Efficiency’. This is a very restrictive measure since it requires the knowledge of input prices and these prices are assumed to be constant.This book describes the concepts of various types of market efficiencies of decision making units (DMU’s) such as price efficiency, Farrell cost efficiency, Economic efficiency, Input technical efficiency and Input Associative efficiencies. The study aims at evaluating the cost efficiencies of 77 Indian commercial Banks employing a wide variety of inputs in order to produce a spectrum of outputs.