This paper examines the effects of managerial overconfidence on bank risk taking and investigates whether improvements in governance can help to mitigate the adverse effects of managerial overconfidence on bank risk taking by using ordinary least squares method. The sample consists of the financial institutions in G20 and Taiwan over the period of 2005-2012. The executive overconfidence is meas...

expert systems can help to build banks customers' credit scoring models. here, selection of key features of the credit scoring is important. also, it is possible to express the features values as fuzzy. the problem is how to improve features selection by genetic algorithm, in way that these features can be employed as input in fuzzy expert system. this paper presents a hybrid credit scorin...

Bank plays the central role for the economic development world-wide. The failure and success of the banking sector depends upon the ability to proper evaluation of credit risk. Credit risk evaluation of any potential credit application has remained a challenge for banks all over the world till today. Artificial neural network plays a tremendous role in the field of finance for making critical, ...

Over the last two decades, bank lending has been closely correlated with property prices in both industrialised and developing countries. From previous empirical studies it is not clear whether these cycles were driven by property prices or lending. In this study I analyse the direction of causality between bank lending and property prices in 16 industrialised countries over the last two decade...

It is typically less profitable for an opportunistic borrower to divert inputs than to divert cash. Therefore, suppliers may lend more liberally than banks. This simple argument is at the core of our contract theoretic model of trade credit in competitive markets. The model implies that trade credit and bank credit can be either complements or substitutes. Among other things, the model explains...

Currently, in Iran's banking system, non-repayment of facilities has become one of the biggest issues, and due to the lack of a proper system for proper allocation of facilities, they face a number of problems, including the problem of allocation of loans, the problem of failure to repay loans Of the central bank, or the amount of facilities increased from the amount of reimbursement. The solut...

This paper develops a decision support tool using an A2 method and data envelopment analysis (DEA) approach (A2-DEA). This new method is applied for the bank credit customer selection problem and credit scoring as a pilot survey at Export Development Bank of Iran. The proposed method has led to fewer calculations, faster and more accurate decision making, less complexity, and ability to ana...

We analyze conventional and unconventional monetary policies in a dynamic small open-economy model with financial frictions. In the model, financial intermediaries or banks borrow from the world market and lend to domestic households. Banks can borrow abroad up to a multiple of their equity; in turn, there is a limit to how much bank equity households can hold. An economy-wide credit constraint...

Data science and machine-learning techniques help banks to optimize enterprise operations, enhance risk analyses gain competitive advantage. There is a vast amount of research in credit risk, but our knowledge, none them uses registry as data source model the probability default for individual clients. The goal this paper evaluate different models create accurate assessment using from real data...