Abstract

Due to the birth of the age of Big Data and the development of Internet finance, electronic banking has been booming. With the application of descriptive statistics, KMV model, panel data regression and robustness testing, this paper examines the validity of KMV model as a measurement of the credit risk of financial institutions, and reveals the impact of electronic banking on the credit risk of commercial banks. The findings are as follows: First, the default distance based on the KMV model can well reflect the credit risk of banks; Second, the growing electronic banking may increase the credit risk, considering the lack of governmental and industrial regulation; At last, the credit risk of banks under different systems have their unique characteristics, so that a clearly defined division of responsibilities for risk control and supervision is needed.

Highlights

  • In recent years, Internet finance has been growing rapidly, and electronic banking has taken a larger share of banking services in commercial banks

  • Electronic Banking Transactions (EBT) of commercial banks is determined as a core variable, with non-performing loan ratio (NPR), return on assets (ROA), asset-liability ratio (LEV), loan-deposit ratio (LDR), the stock holding ratio of major shareholders (TOP1) and capital adequacy ratio (CAR) as explanatory variables

  • These results indicate that banks under different systems have varied standards concerning the management of credit risk

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Summary

Introduction

Internet finance has been growing rapidly, and electronic banking has taken a larger share of banking services in commercial banks. This new form of banking, which is free of the need for counters, increases market risks, and has a great impact on the risk measurement of commercial banks. By the end of 2014, the non-performing loans of commercial banks added up to 842.6 billion yuan, with an increasing number of 250.5 billion yuan in 2014, compared with 99.2 billion yuan in 2013. The credit standing of all levels in China still needs to be improved. Under such environment, it is significant to adopt proper measurement and management of credit risk, so as to manage the capital effectively, preventing the negative influence of the growing Internet finance

Literature Review
Default Distance in KMV Model
The Construction of Econometric Models
Data Selection and Description
Descriptive Analysis
Regression Analysis
Robust Test
Conclusions
Suggestions
Full Text
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