Leveraging existing infrastructure and progress to recalibrate for CECL

Leveraging existing infrastructure and progress to recalibrate for CECL

By Ankur Goel, SVP, Head of Consumer Modeling, PNC

Could you please tell our readers a little bit about yourself, your experience and what your current professional focus is?

I graduated from Indian Institute of Technology (IIT), India, and then received PhD from University of Texas at Austin, Austin, TX. Before joining PNC, I was a Professor at Case Western Reserve University, Cleveland, OH, where I taught Supply Chain Management in the MBA program, and published research in the areas related to energy supply chain and commodity risk management. At PNC, I am leading the credit risk modelling efforts in CCAR / CECL for retail products such as Auto, Credit Card, Student Lending and personal loans

What, for you, are the benefits of attending a conference like the CECL Congress and what can attendees expect to learn from your session?

The benefits from attending the CECL congress is to learn from peer banks about their approaches, methods and preparedness in tackling with the implementation of CECL.

Attendees can learn from my session on how to leverage the current CCAR models for CECL while maintaining the “element of conservatism” of CCAR, and also adhering to the accuracy requirements for CECL. Attendees would also learn about the Payment allocation methods in Credit Card for the purpose of EAD modelling. My session will also focus on how to estimate the portfolio losses beyond the Reasonable and Supportable period of economic forecast.

What challenges and opportunities do you see in the coming years regarding CECL implementation and how can financial institutions best prepare to overcome these challenges?

In my view, CECL would have two major impacts. The one time impact of the realized losses on the income statement and the subsequent volatility in the reserves due to the changes in the economic scenario. Communication with the investor community in explaining these changes will be an important endeavour for the banks. In addition, analytics to explain the attribution of the reserve changes across time will be another key element in managing the expectations of the investors, regulators and clients.

What are the key benefits and challenges financial institutions could face when applying the CCAR model for loss and economic forecast?

The key challenge would be to benchmark the losses of an asset class horizontally across different banks. Since there is no economic scenario provided by the regulators, teasing out the differences in the CECL losses due to portfolio, economic scenarios or assumptions would be a challenging task.

The benefits of CECL would be more granular risk quantification, which would have an impact on the pricing of the final product offered by the banks.

In your opinion, is it important to leverage historical mean loss rate?

Yes, leveraging historical mean loss rate is important for the periods beyond mean reversion. In particular Long Run Average (LRA) would be a significant component of loss forecast for the long dated assets such as mortgage. However, it is required to make reasonable adjustments in the historical loss rates to account for changes in portfolio mix, underwriting strategy and macro-economic environment to adapt to the forward looking losses.

How do you see CECL impacting the financial risk landscape over the next 6-12 months?

CECL does not mitigate the underlying credit risk, but would be instrumental in managing the procyclic losses, which emanate from the back-ward looking feature of the current accounting standard. However, the new approach is not without its own challenges and potential pitfalls.  Lack of concrete guidance from the regulators would possibly create a spectrum of assumptions and economic outlooks across the banks, which might be difficult for the investors to understand.

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