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CECL Builder Plan

There are many steps in the process to get to your CECL 'answer'. Our structured process helps you know and use your data quickly and easily to get to CECL. But it also sets you up to build more, allowing you to leverage your data fully, adding value to your business and your customers.

How Do We Get Started?

This is the question that most financial institutions are starting to ask. Here is exactly how we can help.

Discover What Data You Need

Organize Data to Support Analytics

Ask Questions And Do the Analysis

Document and Communicate

The Data You Need

Two specific data sources are needed. First is application data. You need this to capture the full set of applicants. Details contained here such as demographics and credit bureau data can improve forecast accuracy through segmentation.
Second is performance data. Balance, delinquency levels, bankruptcy and write-off dates and loss amounts all are needed for each month. Loan payoff dates also are needed to measure persistancy.
You can supplement this further with 3rd party data to use for segmentation and targeting of marketing and risk programs. Its use can reduce credit and marketing costs and is worth considering as you expand your analytic capabilities.

How much data do you need?

As much as possible. The further back you go in time the more likely that your CECL forecasts will factor in changing economic cycles. What if you only have a few years of data? No worries. That's where the pooling of data will help fill in the gaps to enhance your forecasts.
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Organize The Data

You need to put the data in a form that supports CECL analysis. This means you need a time series structure. You need to be able to relate delinquency and loss events to the age of the accounts.
You need to relate account performance to the original pool of accounts. This forms the basis of a lifecycle loss forecast.This is one method of determining your CECL reserve requirement. It also serves as a way to gauge whether performance is getting better or worse with newer vintages.
Ideally data should be segmented in a way to improve forecast accuracy while providing additional insights into customer behavior.
As you establish your CECL database you can also use it to track key performance indicators (KPI's) such as application volumes and approval rates over time. You can view cross-sell penetration rates and the success of marketing programs. And you can relate this back to branch performance.
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Ask The Right Questions

CECL forecasts deliver a number. But they should deliver so much more.
Beyond asking how much, it's more important to ask Why? What types of loans are driving the loss forecast? How does the mix of customers and loan types affect the forecast? What has changed since the prior forecast? Is our performance getting better or worse and why?
  • What segments pose the greatest risk?
  • Are these segments unprofitable?
  • Is our performance getting better or worse?
  • How does our performance compare to our peers?

What happens if new questions come up?

Chances are every question you answer will give you new insights and lead to 10 more questions. It's imperative that you keep learning by digging into your data to understand your customers and portfolios to an ever greater degree.
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Document and Communicate

Once you answer the questions it's time to get the word out. What have you learned and what should you do about it?
Each forecast needs to document the collection of the data (reconciliation to source systems), analysis of delinquency and loss trends, and what assumptions have been used in forecasting the remaining life of loan losses. Your choice of assumptions may prove to be the most challenging aspect.
You likely have a credit committee or even a specific CECL committee. Each member should understand what you have learned about what has worked and what needs to be improved. This might mean taking steps to tightening underwriting criteria. Or it might mean working harder to find more of the 'right' types of customers.
Who are the 'right' customers? Using just CECL loss forecast data will probably give you the wrong answer. After all the economics of a loan go beyond losses. It's also important to consider the cost of acquiring a new account, how much revenue they'll generate and for how long.
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If the CECL model is implemented properly, the data it uses could assist banks in better pricing loans and pre-purchase assessments of investments. It could also lead to improved credit risk management and transparency to investors.

Thomas J. Curry

Comptroller of the Currency, US Treasury Department

Some More of the Details
Where Challenges Hide

CECL can be complicated but it's made much simpler by using our structured process
CECLNow delivers ease, speed and accuracy all at a low cost

Collect Your Data

Identify the products and their related source systems for both new account processing and servicing. How much customer history is available? Are there other sources of data that can help describe each customer and help in detailing customer segments?
Skills Required:  Business Knowledge, Data Management

Depersonalize

Strip out personally identifying information while maintaining the ability to link monthly account data together for each account. Ideally a unique customer identifier should be added to round out customer level profiling and profit calculations.
Skills Required:  Systems, Data Management

Transmit data to CECLNow

Share your data with us. We will provide profiles to confirm accuracy while also giving you insights into your customers and trends including comparisons to your peers.
Skills Required:  Systems, Data Security

Develop CECL Forecasts

CECLNow develops a range of CECL models to determine the most appropriate method to apply to your product and customers. By pooling your depersonalized data with other institutions' data we can deliver more stable and accurate forecasts.
Skills Required:  Forecasting, Economics

Document the Forecast

Based on your data we will compile the information you need to fully document the forecast including the profile of your customers, how the forecast was developed, and the performance of the forecast model that serves as the basis for your forecast.
Skills Required:  Business Knowledge, Plotting, Communications

Communicate the Information

In addition to the forecasted loss reserve you will gain insights into your business to share across the business. This will include areas of opportunity to profitably grow your business, cross-sell to existing customers with greater success, and retain your best customers. All this can lead to greater profitability for you and more value delivered to your customers.
Skills Required:  Business Integration,  Marketing, Risk

Garbage In, Garbage Out -- The Role of Data Quality

What You Need To Do

You provide the business knowledge of who your customers are, how you've marketed to them, and how you've made lending decisions. Your understanding of what you've done is critical to accurately capturing, cleaning, and analyzing the data.

This information needs to be captured and documented. Ideally as much data as possible will be used to improve reporting and analysis. For example, if you use different marketing channels (branches, direct mail, internet, etc.) including this information in the data will help understand which channel is performing best and whether significant differences exist.

What We Do

We take your data and structure it in a way to support tracking and analysis. This starts with your new account acquisition data. With it  you are able to drill down into new account info by product, channel, demographics, and risk parameters. The degree you can do this will be limited by how much data exists.

Account performance over time can be tracked in the same way allowing you to dig into how accounts are performing in terms of unit and balance activation and on-going active rates, balance persistency, revenues, delinquency and loss rates. If the data is available risk adjusted yields can be calculated.

Drilling down into this data allows you to discover insights into your business and customers that can business strategy and practices. Hence, the value of your data can go well beyond coming up with your CECL reserve requirement.

Data Is Always A Big Challenge

Competitors who are leveraging data effectively have already tackled the data quality and scope challenge. You need to do it, too, to build accurate CECL models and to get the most out of your data to move your business forward.

Complete?

Having the data you need is the first step. Are all fields complete for all of your customers? If not, how much data is missing? Have you changed the way or what data is captured?

Accurate?

To support analysis you need to start with clean data. We present data distributions to detail the range of values to ensure all are acceptable. Also, you need to make sure the data is consistent over time.

Timely?

You want to capture data at the time you make a decision to aid later analysis. But you also need to obtain a 'fresh look' at the data to make your next decision. Obtaining updated credit and demographic data can aid targeting.

Comprehensive?

How far back in time does your data cover? Does your data cover a full economic cycle? If not you may need to add higher reserves to account for this uncertainty.
"It takes something more than intelligence to act intelligently."
Fyoder Dostoyevsky
Author and  early proponent of data-based decision making
"Investigate what is, and not what pleases."
Johann Wolfgang von Goethe
Writer and statesman

Ready for Action?

Meet all your CECL and regulatory compliance requirements and start down the road to gain insights into your business, improve strategies and tactics, and boost overall profits by contacting us now.
215.740.7028
info@CECLNow.com
LET'S GO!
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