Author Seph Mard

With the continued unfolding of the COVID-19 pandemic, the world’s economies and societies are going through an extended period of uncertainty. This ongoing volatility brings new challenges for organizations and teams managing predictive models.  It’s tricky to maintain a grip on production model management and monitoring under normal circumstances. The current turbulent times highlight this issue even further, with models…

Current Expected Credit Loss (CECL) compliance standards are extremely complex, with many moving pieces. CECL streamlines credit loss expectations across the industry by factoring in future expected losses into capital reserves. Ultimately, this will drive greater reliability of expected loss estimates and capital reserve targets across the industry. To put it simply, the CECL methodology is intended to capture the…

The roadmap to a successful CECL banking program using DataRobot We are currently in the midst of one of the most significant regulatory changes in the history of the global financial system. New accounting regulations and standards will soon fundamentally change how financial institutions must estimate expected loss. These new changes will impact the entire financial system. The new regulations…

Driving value into the model validation process using automated machine learning In recent years, the big data revolution has expanded the integration of machine learning models into more and more business processes. It is no surprise that accurate models are a valuable asset to any business. However, due to an increased reliance on models for everyday business processes and decisions,…