By Guoning Yang, Director, Quant Analytics, Fifth Third Bank.
Guoning, can you please tell the Risk Insights readers a little bit about yourself, your experiences and what your current professional focus is?
I’m responsible for credit risk modeling and analytics for Stress Testing and CECL of Fifth Third Consumer book (Auto loan, Credit Card, Home Equity, Mortgage and Personal Lending). I oversee models and analytics for long-term loss forecasting and stress testing, as well as production, submission and regulatory review support of stress testing. Starting this year, I was assigned to lead Consumer CECL modeling in partnership with Accounting, Finance and Capital Planning. Before Fifth Third, I worked at Capital One leading loss forecasting modeling and Basel modeling of their credit card portfolio.
At the CECL Congress 2018, you will be speaking on your insight regarding, ‘Considerations for CECL model approaches: New approaches vs. updating internal infrastructure’ Why is this a key talking point in the industry right now?
CECL accounting standard is the most impactful accounting change in over a decade for the banking industry and will continue to transform the way banks operate business in the future. From this perspective, banks may want to consider new approaches that reflect the fundamental changes associated with CECL. On the other hand, many banks have developed advanced approaches that can be leveraged or even directly adopted for CECL purpose over the years fulfilling Basel, Economic Capital, CCAR and DFAST. For efficiency and consistency, these banks may want to update the existing approaches for CECL. Therefore, banks need to be strategic with their decision on approaches, balancing factors like what’s the anticipated regulatory expectation on the bank, how’s their current approach compliant with CECL and is the remaining gap manageable through quantitative or qualitative adjustments, is their current approach robust enough for CECL tweak, is there any existing regulatory or managerial concerns on the current approaches that may aggravate if used for CECL, any road blocks prevent the bank from new approach such as data limitations, and etc. Of course, underneath all these factors are the banks’ portfolios. Some portfolios, such as short-term loans, may be indifferent to the change from the old to new approach while others, such as credit card, may result in crucial differences. Therefore, this is a very complicated consideration. I hope the discussion will help the peers to assess their position as well as meet regulatory expectation.
In your opinion, what do you think the limitations would be going forward?
Like for all modeling, the new standard may impose new challenges to data requirements, especially since CECL considers credit risk over the life of loan, which implies longer period of data needed and model/assumption of prepayment behavior. Therefore, I do expect data availability to define the adopted modeling approaches for some banks. In addition, CECL standard is more prescriptive than CCAR/DFAST. This increased expectation may limit the flexibility to tailor the approach for business use. Some workaround solutions in stress testing may not be CECL compliant. Another limitation is IT infrastructure, which may lag behind CECL standard for some banks. This includes data sourcing, extract, and construction, ECL computation and CECL reporting in a timely manner.
What are the key considerations that need to be made when examining the preliminary results under each approach?
I think the key considerations should reply on CECL standard and CECL compliance should be the overarching criterion assessing the alternative approaches. In addition and secondary to CECL compliance comes the business reasonableness and model performance, which add incremental perspectives. Last but not least, since the intent of CECL is to address the too little too late weakness of the current ALLL framework, I would think twice if any approach generates reserve lower than the current ALLL.
Can you provide a brief overview of reconciliation and explanation of differences?
We leveraged the existing CCAR PD/LGD approach but rebuilt some models to focus on accuracy under various economic conditions instead of sensitivity to stressed economic scenarios. In addition, prepayment models were built to enhance the existing framework to capture the behavioral life of loan. Alternative approaches were tested for the expected credit losses beyond reasonable and supportable period. In addition, discounted cash flow approach was also considered and the benefit from discounting was assessed. There are noticeable differences across the different approaches and we do observe a wide range of ECL estimates but they are consistent with the methodological distinctions.
Finally, what challenges do you foresee with CECL implementation over the coming years and how can institutions best plan to meet deadlines?
The data challenges will remain for a while and assumptions may be needed to work around the challenges. While institutions can continue to refine approaches to mitigate the reliance on these assumptions, new data should be collected starting now and a gap analysis on a regular basis is necessary to assess data readiness so that when the time comes, the institution can upgrade their approaches to rely on the data instead of the assumptions. Another challenge is regulatory expectations, which remains unclear for some CECL areas.
