Effective analysis for identifying structural weaknesses in banks
A recent FSI Insights paper from the Financial Stability Institute considers supervisory practices for assessing the sustainability of banks’ business models. “Banks rarely become weak overnight, and flaws in business models and strategies are often the root causes of banks’ vulnerabilities and failures,” it asserts. Business model analysis (BMA) is therefore crucial in allowing supervisors to identify banks’ vulnerabilities at an early stage and intervene to ensure their safety and soundness.
“Granular and good-quality data, adequate data aggregation capabilities, suitable analytical tools, regular dialogue with the bank and expert judgment are indispensable elements of an effective BMA framework,” says the paper. Functional BMA is predicated on banks’ ability to produce and aggregate financial data, and supervisors’ ability to analyse it. We would explicitly add that this should be structured data. The use of XBRL enhances the consistency and comparability of data, while validation processes help ensure its quality. Machine-readability means that complex analyses can be carried out in an automated and timely fashion, with minimal delay in the identification of any emerging weakness.
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