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.