Loan pricing is not an accurate science rather it requires adjustments as per the ever-evolving business environment. So a better way to return proper value to its members is through the reassessment of loan pricing by using analytics of loan-pricing model. This article inculcates how reassessment of the existing loan pricing model can help in determining existing troubles thereby allocating resources for the adoption of a better one.

Here is an example from one of a credit union ($1.8 B in asset) that provides a guide to the reassessment of existing loan pricing thereby do away with the complexity of the pricing involved. Since 70% of their loans were vehicle loans so they wanted to check on the suspicion that they were over-pricing on some other key segments mainly those folks in the higher tiers.

They tried finding solutions through the loan pricing model approach. It includes-

1. Financial Metrics- direct allocations, dealer reserve, etc.
2. Predicted values- the probability of default, loss is given in default, interest actualized, etc.
3. Model inference- It is used to create data-driven risk profiles to restructure the rate sheet.

The primary purpose of the model is to try building new rationing which would be the result of the inferences. The findings from reassessing loan pricing model are summarized below:

• Membership tenure

  Membership tenure is a huge factor in accelerating revenue. The longer the member has a relationship with the organization, it is more likely that they’re going to save more. This way they would move out of debt and thereby improving their credit situation.

• Loan Term

  The original term does not appear to be a factor in people’s pricing decisions and the organization can grant longer-term credit even on prepayments.

• Loan- to- value represents challenges and opportunities

  Loan to value ratio and membership tenure plays a bigger part and can help one in earning a higher rate of interest and thereby building market leaders.

• Too much margin on high-risk loans

  Sometimes even minority members can contribute to making a majority of revenue. Since unintentionally subsidizing loans to most affluent members with proceeds from least affluent members appeared to be an ignoring problem.

• Loss given default consideration

  High lines vehicle should have their pricing sheets of their own.

Following suggestions were given for reassessing Loan Pricing Models to get the desired positive outcomes:

• Origination Volume

  Continuous increase in the membership area and tenure allowed getting most of the sales providing with premiums.

• Per unit profitability

  Since fewer loans make more money so divesting from all long portfolios and focusing on the best loans is necessary.

• Interest earned

  It is the controlling factor as an increase in membership and origination volume would result in higher interest earnings.

• Probability default
  It has not changed dramatically rather it has stayed roughly where it was before the change.

Since changes in the market are often dynamic so there are a few steps that should be followed periodically for implementing an effective loan pricing model.

1. Continuous monitoring and adjustment - Dashboards allowing people to do micro pricing strategy to bring in small yet incremental changes.
2. Replicate programs for other portfolios - This program can be replicated across home equity, credit cards and in fact, effective yield figures can be compared if one wants to invest in more home equities.
3. Extensible to loan participants - Some partners/ earners help in extending loan participation and including future analytics.
4. Resource for balance sheet restructuring from member level to call out level, it has been a huge resource.

To conclude, market changes are new and ongoing so it is better to revise the pricing policy periodically to bring forth favorable returns for its stakeholders.