First introduced by the Financial Accounting Standards Board (FASB) in June 2016, implementation of the Current and Expected Credit Loss (CECL) model is delayed until 2023 for most financial institutions. However, before moving it down on your priority list, consider the CECL delay as an opportunity to enhance your institution’s capabilities with data, which will ultimately provide a better CECL model and will have positive long-term effects for your organization.
CECL requires a vast amount of data to be considered and modeled to accurately predict credit losses. Most financial institutions will need to compile this data from various loan origination systems, core platforms and other systems of record. Compiling and connecting this data can be an enormous challenge. Furthermore, to produce lifetime estimates, more data will need to be collected and stored, as many systems have limitations on and access to data beyond certain timeframes.
While most CECL software programs house data extracts, it’s important to think about your organizational data needs. While CECL is driving many organizations to use data differently, many other areas of the organization could benefit from enhanced data warehousing, like marketing and member relationship management. Therefore, when considering the CECL strategy, it is also necessary to consider the organizational data strategy.
Owning and controlling your data is critically important for financial institutions. Relying on core providers to give you access to data and reporting tools further ties your institution to the core and limits the amount of data truly available for analysis. By creating an organizational data strategy, institutions can begin compiling data from the core and other third-party systems to marry data sets and start to understand the big picture.
Once you’ve determined what data you want to capture and which systems house the data, begin your search for tools to help you warehouse and mine the data. There are many reliable platforms to consider, including Sisense, Tableau, Microsoft Power BI and Qlik. Define whether the data will live in your environment or in the cloud, and be sure to establish the necessary security parameters to protect your valuable corporate assets.
If you’re not sure where to start, working with an outside advisor can set you on the right track toward data management and analysis.