Bank & Credit Union Insights

XGBoost is a popular supervised machine learning algorithm and may be the new wave of modeling credit risk. Here are the basics of the mechanics behind the algorithm.

Machine learning has emerged as a popular and powerful credit risk modeling tool. Here's what banking executives need to know.

For better, more confident decision-making, consider the three key steps of a model risk management “health check.”

For Current Expected Credit Losses (CECL) models, building a sound monitoring program and creating periodic reporting can be challenging.

A quantitative perspective on the next economic downturn.

When planning the validation of any key risk models, always consider three effective challenge action items.

Everyone has that one friend, relative, or neighbor who always seems to ask the one question you don’t have an answer for.

To keep pace with competition and escalating regulatory expectations, many institutions have shifted their risk management philosophies.

DCG has performed model validations for banks and credit unions of all sizes and balance sheet complexities for well over a decade.

The Darling Consulting Group team has been in contact with hundreds of banks and credit unions since the bank failure situation unfolded.

Help ensure a smooth journey and long-term benefits by add these five CECL and MRM resolutions to your list for 2023!

This rate environment is different and every decision matters. Are your models up to the task?