CECL Insights: How to Manage your Data Challenges
Data is one of the biggest concerns institutions have when preparing for Current Expected Credit Losses (CECL). In fact, during a recent webinar we asked participants from various lending institutions to tell us about their greatest data challenge.
Almost two thirds of respondents said their main challenge was pulling together all necessary data. This demonstrates a lack of confidence in available data and a strong deficiency in sourcing and aggregating data.
How to Forecast Your Losses
The data that is available to you — and its granularity — will dictate your method for forecasting losses. For example, you may use a:
- Vintage model: tracking the performance of accounts originated within a particular quarter or year over time
- Vintage-Cohort model: looking at portfolio composition, grouping loans by similar characteristics and tracking the performance of each group over time from origination
- Loan-level model: performing a loan-by-loan analysis that forecasts the probability that a borrower will default, payoff or continue paying in each future month
Do You Need to Supplement Your Data?
Additionally, you must determine if you have sufficient historical data internally or will need to supplement from external sources. Institutions may benefit greatly from the use of external data sets either to augment their own history or to create industry-level forecasts. CreditForecast.com, a joint data solution from Moody’s Analytics and Equifax, was created specifically to meet these needs for consumer credit products.
Critical Questions You Should Answer
In addition, institutions should ask themselves:
- What’s the economic outlook for my footprint? Consider the economic data you have that best correlates with your actual portfolio.
- How do I automate the CECL allowance process? Make your tools and processes run more quickly and efficiently in order to meet your deadlines.
- How do I incorporate future conditions? Assess how many scenarios and views of the economy going forward will be incorporated into your loss modeling.
As you prepare for CECL, consider how you will overcome these challenges and continue to explore your options for implementation.
For more information on CECL requirements, take a look at my previous blog series where I cover:
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