Loan Default Scoring Analysis

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Hey Erik B., I have carefully read through the project requirements for the Loan Default Scoring Analysis. With my expertise in statistics, business analysis, and proficiency in R programming language, I am well-equipped to handle this task effectively. To achieve the desired outcome, I will begin by analyzing the financial data to track loan defaults and borrower details. Utilizing statistical methods, I will generate the Gini coefficient, Information Value (IV), and Weight of Evidence (WoE) calculations. Following this, I will focus on reducing the number of categories while maintaining a GINI above 20%. This process will involve shortlisting categories, conducting analysis using SAS, and performing maximum likelihood estimates tests on both in-sample and out-sample data. The final deliverables will include tables showcasing Gini, IV, WoE, the shortlisted categories, the reduction in categories, and the SAS table with the Analysis of Maximum Likelihood Estimates. Best regards

HI!! I'm proficient in SAS, statistical methods, and have experience with loan data analysis. My skills align perfectly with your project's requirements: Gini, IV, WoE Calculation: Comfortable calculating these metrics and interpreting results. Category Optimization: Strategic approach to category reduction while maintaining Gini thresholds. SAS Modeling: In-depth SAS knowledge for maximum likelihood estimation and in/out-of-sample testing. Clear Reporting: Will provide concise tables summarizing findings and methodology. I've reviewed your attached description and am ready to start. Let's discuss your timeframe and specific deliverables. Regards, Muhammad