Price Behavior of Seasoned Loans, OCC Chief Otting on CRA Reform

by | Sep 2, 2018 | Blog | 0 comments

Greetings,

The US economy continues its growth streak with 2nd quarter GDP growth revised upwards to 4.2%. Core PCE, the Fed’s preferred inflation indicator, came in at 2% keeping the Committee on track to raise rates at the next meeting. The US consumer also remains on a strong footing with the Consumer Board Confidence measure reaching an 18-year high of 133.4, driven by decades-low unemployment.

In regulatory news, the Comptroller of the Currency, Joseph Otting is looking to modernize the Community Reinvestment Act (CRA). The OCC has invited comments on how to redesign the CRA’s regulatory framework. The CRA is designed to encourage banks to meet the needs of borrowers in all segments of their communities, including low and moderate-income neighborhoods.

In an op-ed, Otting laid out his views on how he would like to modernize the CRA. He also noted that there was broad support from a variety of stakeholders to improve CRA rules to better provide financial services to underserved communities. Specifically, Otting would like to:

Revisit how we define the communities that banks serve

PeerIQ View: The CRA was designed in era where brick-and-mortar bank branches made loans in their local geography. Otting seeks to revise how assessment areas are defined under the CRA and expand what qualified for CRA consideration. By defining “community” as underserved populations, rather than a geographic area in proximity to a bank’s branches, a bank can expand financial inclusion while not narrowly limiting to their geography. Nevertheless, some weight would be assigned to CRA activities in specific geographies to ensure that all population groups are served.

Establish metric-based thresholds for CRA performance ratings

PeerIQ View: Today, banks lack a clear and measurable standard to understand whether they satisfy CRA guidelines. Failure to meet CRA guidelines carries severe regulatory risk. Metric-based thresholds can reduce the cost and regulatory burden on banks, and also create transparency in the CRA evaluation process. The OCC should be wary of banks gaming the evaluation process and establish measurable and high-quality standards.

Make CRA performance evaluations more timely and useful

PeerIQ View: Regular and periodic evaluations of banks’ CRA activities will help ensure that the new laws are working as intended, and provide banks with the feedback needed to fine tune their activities to reach the broader goal.

We believe that this is a major step forward in increasing financial inclusion by modernizing the decades-old CRA. We also believe data & analytics technology will play a key role in helping banks monitor standards and measure progress against CRA objectives.

 

This week we conclude our series on whole-loan valuation by looking at the price profiles of unsecured consumer loans under various CPR and CDR scenarios.

You can read the previous articles from our valuation series here:

Valuing whole-loan pools is difficult without loan-level technology. The best results are achieved using a big-data and machine learning approach to generate cashflows on individual loans in a SEC and CECL compliant manner. Reach out to learn how PeerIQ can help you with valuations.

Below we show the price behavior for loans under various prepay and default scenarios. We start with idealized scenarios and then layer on realistic behavior and complexity to illustrate real-world price behavior.

Scenario 1: 0% CPR and 0% CDR – The Scheduled Amortization Price Profile

Exhibit 1 shows the profiles of the price and outstanding balance of a loan under a 0% CPR and 0% CDR scenario. The loan amortizes without any prepayments or defaults. Under this idealized no default scenario, the price of the loan steadily increases and peaks at roughly 2/3rds of the way into the life of the loan, and then price pulls to par as the loan approaches maturity.

Exhibit 1: Price and Outstanding Balance Profiles for 0% CPR / CDR Curves

Source: PeerIQ

 

Scenario 2: Prepayments and No Defaults – 10% CPR and 0% CDR

Introducing prepayments (indicated by higher CPR speeds) to the typical amortization accelerates principal paydowns. The amortization curve (the blue triangle below) steepens as the outstanding balance pays down faster. Higher prepayments also cap how high the price of a loan the rises after origination. This makes intuitive sense as coupon payments are applied on a smaller loan balance – there are less future cashflows to discount.

Exhibit 2: Price and Outstanding Balance Profiles for 10% CPR / 0% CDR Curves

Source: PeerIQ

 

Scenario 3: Defaults but no Prepayment – 0% CPR and 10% CDR

Adding defaults to the typical amortization curve shown in exhibit 1 reduces the principal received. (We assume here no recoveries on charge-offs.) Here, defaults are assumed to be evenly distributed over the life of the loan. In this scenario, price does not rise much above par and would drop below par if CDR (the rate of defaults) speeds increase.

Exhibit 3: Price and Outstanding Balance Profiles for 0% CPR / 10% CDR Curves

Source: PeerIQ

 

Scenario 4: Front-Loaded Default Rates

In Exhibit 4, the front-loaded CDR curve ramps to 20% CDR in month 12 and then drops to 10% by month 24. Loans that experience up-front losses have lower prices early in their life. The price drops initially due to high losses, but stabilizes around par as the loan seasons and losses decrease. The loan price then “pulls to par” at maturity.

Exhibit 4: Price and Outstanding Balance Profiles for a Front Loaded CDR Curve

Source: PeerIQ

 

Scenario 5: Back-Loaded Default Rates

Exhibit 5 shows step-wise ramping up of the CDR curve up to month 24, after which the loan has a constant 30% CDR until maturity. Loans that experience a back-loaded loss rate have a prolonged price drop after origination. In approximately month 20, the loan is priced at its steepest discount, before the price pushes to par by maturity. The price drop is significant as the balance of the loan is higher in the beginning, and results in a higher market value mark down.

Exhibit 5: Price and Outstanding Balance Profiles for a Back Loaded CDR Curve

Source: PeerIQ

 

Here is a table summarizing the price behavior of loans under various scenarios. (Note we’re also assuming that interest rates at origination and in capital markets are held constant to build intuition.)

Scenario Prepay / Default Behavior

Price Pattern
1.      Scheduled Amortization, No prepays, No losses · The price of the loan steadily increases and peaks at roughly 2/3rds of the way into the life of the loan, and then price pulls to par as the loan approaches maturity.

 
2.      Prepayments (evenly distributed), No defaults · Higher prepayments also cap how high the price of a loan the rises after origination
3.      Defaults (evenly distributed), No prepayments · Price may not rise above par/UPB and would drop below par if CDR (the rate of defaults) speeds increase.

 
4.      Front-Loaded Default Rates

 

 · Loans that experience up-front losses have lower prices early in their life. The price drops initially due to high losses, but stabilizes around par as the loan seasons and losses decrease.
5.      Back-loaded Default Rates · Loans that experience a back-loaded loss rate have a prolonged price drop after origination. In approximately month 20, the loan is priced at its steepest discount, before the price pushes to par by maturity.

In virtually all real-world scenarios, the price of a seasoned loan is generally different than par. Prices may be above or below par based on the front or back-loading of defaults, time to maturity, and changes in rates (in the above we hold interest rates constant).  Real-world unsecured personal loans typically exhibit front-loaded default rates (Scenario 4). However, prepayments are also not generally distributed.

Sophisticated loan-level technology and modelling capabilities are required to bring all these components together to deliver a fair value mark. Reach out to learn how PeerIQ can help you with valuations.

 

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