CECL

Forecasting: Considerations for a Reasonable and Supportable CECL Forecast

Forecasting might not be top of mind as you prepare for CECL. Understanding the standard, deciding whether to handle the transition internally or engage third party assistance, gathering data, pooling, choosing a methodology – those issues drive our concerns well before we encounter a “reasonable and supportable” forecast. The forecasting piece is, in large part, what makes CECL different from incurred loss estimating. The Great Recession revealed the insufficiency of being able to reserve only for a probable or already incurred loss event; those years proved the incurred loss model “too little, too late.” The FASB determined we needed a forward-looking component to be prepared for an economic downturn when it comes – and not only a Great Recession, but a local economic jolt, like the closing of a factory that employs a significant portion of the local population. CECL allows us to do that, even to the extent of reacting to a rumor, be it from a credible source. Ultimately we are forecasting why the future is different from the past, be it better or worse. We do that using economic factors. External factors can be broad in scope, such as political turmoil or a trade war. Or they can be local, such as a weather event or the opening of a new business that will increase employment in your area. And they can reflect internal factors, like losing a quality loan officer to another institution, or signing new loan talent, or the closing of a competing institution. Here are a few things to consider when developing the forecasting piece of your CECL process: Initially, identify the variables that will determine expected losses. What specific factors apply to your population, your institution? Hone in on the most important factors; don’t complicate [...]

2018-11-05T13:17:42+00:00November 5th, 2018|Blog, CECL, Economic Forecasting|

What is the Vintage Methodology for CECL?

The Vintage Methodology under CECL (Current Expected Credit Loss) measures the expected loss calculation for future periods based on historical performance by the origination period of loans with similar life cycles and risk characteristics. It’s advantageous to pool similar loans that follow comparable loss curves that may be predictive for future periods. There are a handful of characteristics you should look at when segmenting your loans with the Vintage methodology. The most important risk driver is that all loans share a common origination period. Contrasted to the cohort method, loans are only included in tracking historical losses in the period in which they originated. Upon renewal of a loan, a new vintage is created. Critical data elements needed to run Vintage include loan number, balance at origination, loan balance, maturity date, renewal date, and loss information. The loans in the pools for this methodology should have similar risk characteristics and can be sub-segmented by an optional risk driver, like risk rating, although many times pools will become too granular to use this optional driver. Loan pools should  have very similar weighted average lives because loss rates in year two of a three-year loan looks vastly different than year two of a seven-year loan. Vintage works well with indirect auto loans and other consumer loans, credit portfolios, etc. To determine loss rates with this methodology, start with historical loss rates for each vintage and examine any trends in recent vintage loss rates. Fill in loss rates for future periods based upon historical trends as well as factoring in any changes for current conditions and reasonable and supportable forecast periods where you anticipate these periods are different from historical. Depending on differences in the makeup of the vintages, different adjustment factors may be required for each vintage. Depending on forecasted conditions, adjustments could be either positive or negative. When future years are no longer reasonably forecastable, revert to adjusted historical averages. Re-evaluate your Q factors with shifts in the economic landscape. When figuring out [...]

2018-10-26T13:07:18+00:00October 26th, 2018|Blog, CECL, Methodologies|

What is the PD/LGD Transition Matrix Model for CECL?

The transition matrix model (TMM) determines the probability of default (PD) of loans by tracking the historical movement of loans between loan states over a defined period of time – for example, from one year to the next – and establishes a probably of transition for those loan types between different loan states. […]

2018-10-24T11:14:12+00:00October 19th, 2018|CECL, Methodologies|

Florence Distorts Job Numbers; Labor Market Remains Strong

Guest blog by Dr. Tom Cunningham, Economist and MST Advisory Services, Senior Advisor- Economics The headline numbers from the Bureau of Labor Statistics’ (BLS) September jobs report suggest a mixed employment situation. New jobs came in at just 134,000, well below the expected 180,000, while that headline unemployment rate, U3, fell 0.2 percentage points to 3.7 percent, slightly lower than the 3.8 percent expected. […]

2018-10-23T17:31:16+00:00October 9th, 2018|CECL, Economic Forecasting, Economic Indicators|

Time – and CECL – Wait for No One

Use our industry experience to build your institution a CECL “backward timeline.”  From the very announcement of the CECL implementation dates, we have been working with lenders – and spilling a lot of ink – on timelines. When do you need to get started on your CECL transition to have enough time to be ready for your implementation date?  […]

2018-10-24T10:12:41+00:00October 5th, 2018|CECL|

Overcoming Organizational Obstacles in Transitioning to CECL

Who owns the present Allowance for Loan and Lease Losses (ALLL) and the new Allowance for Credit Losses (ACL) processes in your financial institution? The Chief Financial Officer (CFO)? The Chief Credit Officer (CCO)? The Chief Lending Officer (CLO)? Perhaps it is a shared function. In my 40 years in banking, I have seen the responsibility fall to each of these roles.  […]

2018-10-23T23:29:42+00:00September 28th, 2018|CECL|

ABA Endorses MST for CECL Software Solution

From the ABA . . . ABA Endorses MST, Sageworks for CECL Software Solutions WASHINGTON — The American Bankers Association today announced its endorsement of two software solutions to help banks meet the upcoming deadline for Current Expected Credit Loss (CECL) implementation. Sageworks ALLL and MST Loan Loss Analyzer (LLA) are software solutions that provide modeling and data management for CECL accounting. […]

2018-10-31T09:35:58+00:00September 17th, 2018|CECL|

CECL Panel: Answers to Your Top CECL Questions

October 10, 2018 | 2:00 - 3:30 p.m. ET Presented by MST, Sageworks, Grant Thornton, BKD and PWC Lenders are knee-deep in their transition to CECL and encountering challenges at every turn. In "Answers to Your Top CECL Questions," our panel of auditors from Grant Thornton, BKD and PWC, and CECL consultants from MST and Sageworks will discuss CECL and its enterprise-wide impact and respond to your questions. The panel is comprised of Regan Camp, MST; Neekis Hammond, Sageworks; Gordon Dobner, BKD; John Reedy, Grant Thornton; and Mike Shearer, PWC. To Access the Recording, click here.

2018-10-30T16:12:17+00:00September 14th, 2018|CECL, CECL Education|