The document discusses using LARS regression to determine the optimal objective function for an efficient frontier analytic team. It analyzes the correlation between loan variables and finds that total loans has a strong correlation with total amount. It uses an LARS algorithm to select a model that best captures the relationship between total loans and other variables with the lowest predictive error. The recommended objective function includes total applications, approved applications, and total loans to capture loan volume and outcomes.

1. Using LARS Regression for Objective FunctionEfficient Frontier Analytic TeamJuly , 2010

2. GoalFind the best set of weights across the whole loan channelthat best capture the loan intent and conversion behaviors to help optimize SEM optimization.

3. Correlation Analysis Auto TD and UW_TD have positive correlation with Total.Apps

4. Total.Loans has strong correlation with Total Amount, so we will only put Total.Loans in the objective function. Variable Selection: LARS AlgorithmModel 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.

5. Recommended Objective FunctionTotal.Apps captures the volume of loan applications