Parsing the content of bank supervision
Beverly Hirtle and
No 770, Staff Reports from Federal Reserve Bank of New York
We measure bank supervision using the database of supervisory issues, known as matters requiring attention or immediate attention, raised by Federal Reserve examiners to banking organizations. The volume of supervisory issues increases with banks? asset size, especially for the largest and most complex banks, and decreases with profitability and the quality of the loan portfolio. Stressed banks are faster at resolving issues, but all else equal, resolving new issues takes longer the more issues a bank faces, which may suggest capacity constraints in addressing multiple supervisory issues. Using computational linguistic methods on the text of the issue description, we define five categorical issue topics. The subset of issues related to capital levels and loan portfolio are the most consequential in terms of regulatory rating downgrades and are directly related to changes in banks? balance sheet characteristics and profitability. Other issues appear to reflect soft information and are less correlated with bank observables. By categorizing questions asked by analysts at banks? quarterly earnings calls using the same linguistic approach, we find that market monitors raise issues similar to those of supervisors when the issues are related to hard information (such as loan quality or capital) and public supervisory assessment programs.
Keywords: bank supervision; bank regulation; market monitoring; text classification; Latent Dirichlet Allocation (search for similar items in EconPapers)
JEL-codes: G21 G28 (search for similar items in EconPapers)
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