The FSA published the English version of "FSA Analytical Notes (2025.1) vol.2". 
full text
As financial institutions’ business environments and profit structures change, it is important to understand economic and market trends based on data, and to accurately grasp the business conditions of individual financial institutions and also the resilience and vulnerabilities of the financial system as a whole. From this perspective, the FSA has been focusing on the utilization of granular data, such as transaction-level bank loan data and financial data on individual corporations. Some case examples of data analyses using such granular data are published as a series of reports titled “FSA Analytical Notes.”
This issue contains two analyses on: 1) borrower classifications assigned to shared borrowers, and 2) attributes of housing loans by regional banks. It is notable in that it uses granular loan data to understand borrower classifications and attributes of housing loans.
This paper analyzes the borrower classifications (internal ratings) of shared borrowers, to which two or more banks extend loans, using granular loan-by-loan level data collected by the Common Data Platform. The results of the analysis suggest that loans extended to the shared borrowers outside the home region of banks (prefecture-wise cross-border loans) and loans which include major bank(s) in their creditors, are more likely to be rated as "normal" even after controlling the effects of the financial conditions of the borrowers.
This paper compiles a detail picture of the housing loans extended by regional banks, using granular loan data collected by the Common Data Platform. It is confirmed that there are regional differences in interest rate types and levels. In addition, it is observed that transaction volumes and lending periods per loan are growing, which may lead to higher risks.
Enhancing the use of data in financial supervision and policy-making is a medium- to long-term agenda. The FSA will continue to build its data analysis capabilities and data infrastructure.
* Unless otherwise noted, the figures and tables in this report were prepared by the FSA.
- Contact
