Hailey College of Banking & Finance Lahore
Feb 25 - Mar 02, 2008

Risk-based pricing is the practice of lenders charging each borrower a specific interest rate based on credit risk rather than charging one single house rate. Financial Institutions are increasingly engaged in risk-based pricing. If properly quantified, the additional credit risk taken due to the lower operational risk parameters when originating high LTV mortgage can be compensated by higher interest rate charged to customers. High LTV mortgage is regulated to meet higher capital requirement and thus have higher funding cost. Current regulation raises regulatory capital requirement of banks on all high LTV mortgage holdings. On the whole, the results are in keeping with the predictions. For those obtaining loans, the premium paid per unit of risk became significantly larger over this time period, with the difference between high- and low-risk borrowers' interest rates approximately doubling for secured loans and increasing for most unsecured loans, as well. Given an increase in the probability of declaring bankruptcy i.e., accepting the increased level of credit risk, the corresponding interest rate increase more than doubles for first mortgages and automobile loans and went up nearly five times for second mortgages. According to a research by Dr. Wendy Edelberg of University of Chicago this phenomena is primarily dependent on three factors:

* The premium paid per unit of risk should increase.
* Debt levels should react accordingly.

* Fewer very high-risk households should be denied credit, further contributing to an increase in the spread between the interest rates paid by the highest and lowest risk borrowers.

The changes in the pricing practices by the lenders have been reflected in borrowing levels and access to debt, particularly for secured debt. While borrowing generally increased in the mid of the present decade, in part reflecting the overall lower levels of interest rates, it increased most for low-risk households who were least affected by these changes. For example, risk-based pricing may explain nearly 25% of increases mortgage levels. Furthermore, while these changes in pricing practices led to increased credit access for very high-risk households (again, particularly for secured debt), the increase in the risk premium faced by these households implied that their average borrowing levels either rose less or, for some loan types, fell.

The lending institutions usually consider the following factors while establishing a risk based interest price of any consumer financing product:

EMPIRICAL ANALYSIS: The primary goal of this empirical analysis is to estimate the role default risk plays in interest rate determination and see if that role has changed over time. As an illustration, increased education may be associated with reduced default risk. In this way, higher education may reduce interest rates for households. Conversely, more education may increase the likelihood of receiving a loan due to greater familiarity with financial markets or reduced search costs.

BANKRUPTCY: In selecting the consumer financing characteristics that belong in a bankruptcy model, quite a bit of research has been done in this area; chosen characteristics for the conditional bankruptcy risk are year, a second order polynomial in age, lack of a checking account, the natural log of income, whether a household is self employed, home ownership status, whether the ratio of unsecured debt to income is greater than two, net worth (with negative net worth set to zero), non-collateralized debt, if a family head is unemployed, race, an education class variable taking five values, and whether the head is a single parent and many more!

LATE PAYMENT: Predictions of the late payment indicator from a probit model use the same characteristics as those used to predict bankruptcy. Normally data-check facility and CIB report taken from State Bank of Pakistan form the basis of this report. Such reports separate the consumer delinquencies in the repayment of installments or service charges in different slabs namely 30-Days Past Due (DPD) 60-DPD and 90-DPD after which time any financing becomes Non-Performing under the Prudential Regulations imposed by the State Bank of Pakistan.

COMBINES ANALYSIS: This methodology requires one important qualification. These measures only offer a snapshot of a household's default risk at the survey date. In reality, a lender must forecast a borrower's possibly changing default risk over the entire course of the loan. The ideal data set would include what the lender observes at the time of the loan, and what the lender predicts for the borrower's attributes over the course of the loan - since these lead to a lender's predictions of the borrower's future default risk. Thus, the contribution of this series of default risks to the interest rate at loan origination would become apparent.

Moving on to the results, it has been observed from the available data on consumer financing from State Bank of Pakistan that the predicted interest rates plotted against conditional bankruptcy risk for each loan type predict the significant measures of default risk. It is significant to consider here that the results only from conditional bankruptcy and delinquency predictions in turn are reported. This is done because there is value-added from using both measures of default risk. With no conditional bankruptcy included, spreads are roughly unchanged for secured loans, though they are smaller across the board. For unsecured loans, the credit card loan interest rate spread, and the personal loan spread is significant. With no predicted late payment measure included except the ones as already discussed earlier. On the other hand, automobiles have also shown significant upward change in the interest rate and margin requirements over the period.