Efficient Frontier Analytic TeamJuly , 2010

Using LARS Regression for

Objective Function

Goal

Find the best set of weights across the whole loan channel

that best capture the loan intent and conversion

behaviors to help optimize SEM optimization.

Correlation Analysis

Auto TD and UW_TD have positive correlation with Total.Apps

Total.Loans has strong correlation with Total Amount, so we will only put

Total.Loans in the objective function.

Variable Selection: LARS Algorithm

Model Total.Apps AutoTD UW_TD ApprovedPredictive

Error

0 0 0 0 0 1.36

1 0 0 0 0.130 0.81

2 0.007 0 0 0.159 0.73

3 0.010 0 -0.003 0.156 0.75

4 0.027 0.024 -0.028 0.136 0.78

Model 2 captures the best relationship between Total Loan and

other variable best.

By using this model, we can give best prediction of Total Loan

with lowest predictive error based on other variables.

Recommended Objective Function

LoanTotalApprovedAppsTotalObjective .116.0.007.0

Total.Apps captures the volume of loan applications

Approved captures the volume of qualified applications

Total Loan captures the final confirmed loan.