The protracted period of stability in the banking sector since the Great Recession, accompanied by the evolving time path of interest rates, makes understanding the causes and timing of the next economic downturn particularly acute for regulatory agencies. The development and implementation of supervisory ratings models is critical in providing a first response by regulatory agencies to shift examination resources to those institutions that pose the greatest risk to bank solvency or financial stability. In alignment with the Economic Growth, Regulatory Relief, and Consumer Protection Act of 2018, examiners could enhance prudential regulation standards through data-enhanced activities to monitor inherent and emerging risk, especially at small depository institutions and holding companies where reduced reporting requirements and extended examination cycles have been implemented under the Act. The results of this paper show that robust forward-looking statistical models are superior to backward-looking assessments of supervisory compliance, which could lead to less regulatory burden when integrated into the examination process, particularly at smaller institutions.


中文翻译：

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监管银行风险预警建模：审查员的第一道防线

自大衰退以来银行业长期保持稳定，伴随着利率时间路径的演变，使得监管机构对下一次经济衰退的原因和时机的理解尤为紧迫。监管评级模型的开发和实施对于监管机构将审查资源转移到对银行偿付能力或金融稳定性构成最大风险的机构做出第一反应至关重要。根据 2018 年的《经济增长、监管救济和消费者保护法》，审查员可以通过数据增强活动来提高审慎监管标准，以监测固有风险和新兴风险，特别是在小型存款机构和控股公司，根据该法案已实施了减少报告要求和延长审查周期的措施。本文的结果表明，稳健的前瞻性统计模型优于对监管合规性的回顾性评估，当整合到审查过程中时，这可能会减少监管负担，尤其是在较小的机构中。