Credit Risk Management for SAS
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As any credit manager in the banking industry knows, controlling risk is a delicate business. Too much credit exposure can lead to high default rates and charge-off percentages; too little exposure often means lost business and revenue. SAS helps banks manage this balancing act with SAS Credit Scoring for Banking, which provides fast, accurate credit scoring for nearly all consumer-lending products.
There is a wide range of strategies for measuring the credit worthiness of new and existing customers in the banking industry, but many of them have serious limitations. Outsourced strategies can lead to long development cycles or high annual expenditures. Makeshift in-house scoring strategies often lack the ability to access necessary data for accurate scoring, leaving credit managers with no effective way to identify how much potential income or loss rides on their decisions.
Course Outline
1. Introduction to Risk Management
a. Why Risk Management
b. Credit Bureau
2. Introduction to Credit Risk Management
3. Logistic Regression in SAS
a. Introduction to Logistic Regression
b. Variable Selections
c. Build a Logistic Regression in SAS
d. An example
4. Development of a Credit Scorecard
a. Data Preparation
b. Initial Analysis
c. Reject Inference
d. Score Allocation
e. Monitoring of Credit Scorecard
5. Project
6. Introduction to SAS Enterprise Miner
a. SEMMA Scheme
b. An example
【Audience】
1. People with SAS skills, who is looking for risk management job in banks.
2. Recent graduates who want to apply for financial jobs.
3. Bank employees who want to change his/her career to risk management in retail banking..
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