Just How Risky Is Your Portfolio?

Instead of basing your portfolio on a single credit score cut-off, a more sophisticated approach can help you to reduce losses, more accurately determine reserves and improve account acquisition and retention.

 

By Keith Carson

 

With the development of improved credit scoring methodologies, many risk executives have become reliant on credit scores as a means of determining risk acceptance for their credit union. However, in order to keep things simple, often one score is used as a cut-off in the decision to grant or deny credit to a member.

Since the mid-1980s credit reporting companies have developed increasingly sophisticated risk models to aid in the management of the growth and the risk in its loan portfolio. Today, many credit unions are benefiting from the use of these models.

So, how do you evaluate the risk in your portfolio? Do you simply rely on a single score cut-off and hope for the best? Has the risk in your portfolio been growing? Have you declined credit to members, who subsequently went to one of your competitors and secured a loan? Are your Loan and Lease Loss Reserves (LLLR) adequate?

It is the intention of this article to define the elements of a robust portfolio risk assessment program, and to demonstrate how a more sophisticated approach can help you to reduce losses, more accurately determine reserves and improve account acquisition and retention.

Components of a Robust Risk Management Program:
A robust risk management program should include all of the following capabilities:

  • The ability to consistently monitor historic risk trends in the portfolio.
  • The ability to determine the current risk profile in the portfolio.
  • Using risk forecasts to devise strategy
  • The means to differentiate risk within the credit union’s footprint
  • The ability to forecast risk on a geographic basis.

1. Monitoring Historical Risk Trends in the Portfolio:
Portfolio reviews should be used to identify groups of accounts which exhibit key credit file changes that are predictive for actions such as default, slow pay, bankruptcy filing, credit over-extension and the possibility of the account either attriting or churning. To get the maximum advantage out of portfolio review, it is crucial that they be conducted at least quarterly in order to identify adverse trends and to allow for the timely development of mitigation strategies.

2. Determining the Current Risk Profile in the Portfolio
An analysis of the current risk in the portfolio allows the credit union executive to determine the impact of the institution’s underwriting criteria. If the current risk profile of the members with a specific type of credit facility is too high, then the executive needs to consider modifying the underwriting criteria to a more conservative approach to yield a lower risk exposure for the credit union. Conversely, if the risk in the portfolio of a particular type of loan is below desirable levels, then the Credit Union may be overly conservative in their underwriting and they may be losing loans for members to competitors.

  • Portfolio Forecasts - a Tool to Develop Strategies

Using new predictive models, a risk executive can track projected risk trends to modify lending strategies for improved business results. These strategies include:

  • Credit line & authorization management
  • Concentration risk
  • Collection prioritization & loss forecasting
  • New account acquisition

4. Differentiating Risk within a Footprint
Although many credit unions consider their portfolios to be homogeneous in nature, it is crucial that the risk manager differentiate the risk between various markets and sub-markets that the credit union serves. With the availability of data at the Metropolitan Statistical Area (MSA) level, a risk executive now has the option of developing varying lending criteria to comport with the differing risk within the credit union’s footprint.

5. Forecasting Risk on a Geographical Basis
In an effort to improve on the traditional data that is available for planning and predictive analysis, new sources have emerged to allow for the development of data down to the state and MSA levels. This increased granularity allows for the development of robust predictive models, which can produce superior results.  This translates into a singular improvement in the ability to forecast risk.

In summary, risk executives in credit unions now have tools available to them that allow them to monitor and predict the risk in their portfolios in much greater detail than previously thought possible. The byproduct of the usage of these models is the ability to reduce risk and improve profits within the credit union and LLLR.

For more information, please visit us at www.transunion.com.

 
 

June 4, 2007


Comments

 
 
 

No comments have been posted yet. Be the first one.