The key to good model risk governance is establishing an efficient model lifecycle management process. In the banking industry, small and medium sized firms may not have the infrastructure and…

It is well known that mortgage rates are tied to the basic rules of supply and demand. Several factors contribute to mortgage interest rate volatility such as inflation, economic growth,…

Supervisory Guidance on Model Risk Management, known as SR 11-7, was published by the Federal Reserve in 2011, along with companion guidance from the OCC. Since then, the largest banks…

The second in a series of two workshops on Bias in machine learning models focused on methods for detecting and correcting bias. The workshop covers estimating fairness metrics using python,…

Machine learning (ML) advanced statistical and mathematical models are used in various partial or fully automated decision-making systems that affect individual lives. Today, these models are not only increasingly used…

The first in a series of two workshops on Bias in machine learning models focused on methods for detecting and correcting bias. The workshop covers an introduction to the topic,…

The Federal Reserve, the Office of the Comptroller of the Currency, and the Federal Deposit Insurance Corporation have all published guidance explaining how risk managers should meet Bank Secrecy Act…

In an era of financial uncertainty, effective liquidity risk management is critical for institutions seeking long-term stability. Liquidity stress modelling helps banks, asset managers, and other financial entities assess their…

Mortgages are the financial cornerstone that allows most American families to purchase their homes. However, some families face more difficulties than others when applying for a mortgage. Could applicants’ race…

Kevin D. Oden & Associates (KDOA) is pleased to announce that they have acquired a robust model risk management platform and validation reporting system through the purchase of Complify. This…