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REASONS WHY YOU NEED A DATA WAREHOUSE STRATEGY – PART 1

REASONS WHY YOU NEED A DATA WAREHOUSE STRATEGY – PART 1
Posted: Feb 7, 2019
Comments: 0
Author: Randy Daigle

CECL is One of Them

So, you can now breathe a little easier, just a little, with the Financial Accounting Standards Board (“FASB”) officially delaying Current Expected Credit Loss (“CECL”) implementation to fiscal years beginning after December 2021. Basically, the credit union will need to move from estimating Allowance Loan and Lease Losses (“ALLL”) based on averages of historical losses (that is, looking in the rear-view mirror) to developing future predictive models to estimate loan losses and to set loss reserves in 2022. This must be done for each individual loan booked, on the day the loan closes, and ongoing throughout the loan.

The good news is that it seems that the FASB will allow credit unions the flexibility to choose a model that ranges from simple to very complex to estimate loan losses to satisfy the regulators. Proactive credit unions/CFOs who are desiring control and some flexibility in the estimation of ALLL should already be on their way to collecting CECL data, understanding it and reviewing their current loan portfolio strategy under CECL.

The bad news is that whichever CECL model you choose it will most likely require a one-time capital adjustment after December 15, 2021, for 2022. The size of that adjustment varies based on how much data the credit union has for its model. Planning and forecasting the required capital investment should start as early as possible to have the needed capital in place, giving adequate time to finance the capital outlay.

It is recommended that you collect at least two (2) to three (3) years of historical CECL data points, so the credit union should start in 2019 before it is too late. Having these data points, before 2022, will allow the credit union to test different CECL models and scenarios, and possibly make strategic changes to the loan portfolio make-up. The bottom line is that the more historical data points the credit union has available to analyze, the more options and flexibility the credit union will have to make any adjustment to ALLL to satisfy the regulators.

The simple vintage model requires you to collect the least amount of data between now and 2022:

1.     Pool loan balance on the date the pool was formed

2.     Loan losses net charge-offs from initial pool date to report date

3.     Origination dates of loans that had losses for the reporting period

This simple model will most likely result in a higher CECL allowance for loan loss balance estimates, requiring additional funding by the credit union.

Collecting additional CECL data results in a better, more accurate model possibly lowering loan loss reserves relative to simpler models, but it also adds complexity to your data warehouse strategy. Your credit union should think about what needs to be collected, from what sources, how it is collected, and archived (e.g., core data processor, full-service credit processor or best-in-class mortgage loan originator). The following is a short list of some items that should be retrievable for analysis from your data warehouse solution:

Data Points for Members and Loan Activity:

1.     Member loan number/ID, balance, book/contract balance

2.     Loan to value (LTV) and cumulative loan to value (CLTV)

3.     Loan product type, coupon rate, revolving status, and maturity date

4.     Member loan duration, and charge-offs/recoveries (partial and full)

5.     Historical member credit scores and risk rating for members’ loan

6.     Member change in income, employment status and/or cash flow

7.     Tracking member’s collateral/asset type

Data Points for Loan Portfolio Concentration/Segmentation:

1.     Beginning balance of pool (oldest loan) and ending loan balance (longest duration)

2.     Individual loan balances in the pool, past due and charge-offs/recoveries (partial and full)

3.     Loan portfolio segmentation, historical performance status, and tracking portfolio changes

4.     Loan pool interest basis, floor, ceiling interest rate, and revolving status

5.     The risk rating for each individual loan and tracking historical quality risk

6.     Determine a unique time horizon and unique loss rate for each portfolio segment

7.     Alternatively, for small credit unions or small portfolio segments, peer data can be used

Data Points for Economic Forecasting:

1.     Tracking national credit scores and trends

2.     Tracking federal funds rate

3.     Tracking employment rates, income, and discretionary income

4.     Tracking during times of economic uncertainty, economic growth or recession

5.     Tracking interest rates (inflation or deflation)

Next steps for credit unions

If you are not already in the evaluation process, initiate a discussion today with the executive leadership team at your credit union to highlight the risks of not addressing the CECL requirements now. Some specific suggestions:

·       Secure resources to develop a strategic plan and move forward with urgency.

·       Put together a team of subject matter experts (SMEs) to review and fully understand the CECL data that the credit union is already collecting, and archiving.

·       Determine what additional CECL data the credit union need to start harvesting.

·    Evaluate what data warehouse capabilities the credit union has on-premises and/or cloud resources to collect the CECL data today, over the next 3-years, and beyond.

Finally, if you need assistance defining or implementing your data warehouse strategy, contact the Trellance team at info@trellance.com. We would love to help!

 

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Randy Daigle

Randy DaigleRandy Daigle

Randy is Trellance's Vendor Management Consultant. With more than 21 years of project management experience, Randy is adept at managing international and domestic IT vendor evaluations, conversions, and contract negotiations, for core, online/mobile banking, and credit/debit card processors for

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