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The secret to getting CECL ready

Current Expected Credit Loss, also known as CECL, is the buzzword everyone is talking about in the banking world right now. The clock is ticking—400 days, give or take, but who’s counting?—before the first CECL deadline hits. In about a year, are you confident you’ll have the required data you can trust to inform your modeling, forecasting, and strategy? If not, you’re not alone.

Our research shows you may be part of 46 percent of companies that either haven’t started or are unsure how to get started with their CECL action plan. It’s no secret this new, forward-thinking accounting standard is built off a foundation of data, but it’s hard to know where to begin. We’re here to help you take the ground breaking steps to get your data ready for CECL modeling.

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Data quality is the fundamental first step that will put you on the road for ongoing success to CECL compliance and beyond.

If you don’t have quality data—that is accurate, relevant, and complete data—from the get-go, it makes it very difficult to confidently move forward with any data project. In fact, 65 percent of respondents say inaccurate data is undermining key initiatives. With a regulation like CECL, you will not be able to reach full compliance without complete, clean, accurate data encompassed in a model that fits both CECL and your specifications. Investing in quality data establishes a foundation for your modeling you can trust.

Our solutions evaluate your current data landscape and determine what you need to do to clean it up and build a sustainable data quality and data governance strategy. Our data quality management platform has the tools you need to tackle consolidating, cleaning, and completing your database so you’re ready for CECL compliance.

Data profiling

Data Profiling

Identify how your database is structured and where the gaps lie within your data.

Data cleansing

Data Cleansing

Clean up your data by fixing incorrect, incomplete, and improperly formatted records.

Data deduplication

Data deduplication

Examine relationships across records to accurately consolidate consumer assets.

Data standardization

Data standardizing

Transform your data by creating a consistent format across all data sets.

Data monitoring

Data monitoring

Control your data to make sure your data quality efforts stay accurate and fit for purpose.

You have one year—that’s one year to clean up your datasets, append new data, test modeling techniques, and get buy-in from your stakeholders—to comply with CECL. When you consolidate, clean, and complete your data, you will have the confidence you’ll need to take on CECL.

 

Contact us to learn more about data quality and CECL!