Job Title: Head - Analytics (Leading listed NBFC)

About the Company:

The client is a Non-Banking Finance Company (NBFC) registered with Reserve Bank of India (RBI) as ND-SI (Non-Deposit taking systemically important) and is listed on both the Bombay Stock Exchange (BSE) and the National Stock Exchange (NSE).

Lending Business: The company lends primarily to three sectors:

1. Real Estate Lending: The client provides short to medium term loans to real estate developers at different stages of project implementation including the project approval stage funding or as a last mile funding

2. SME and Retail Lending:The client provides financial solutions for micro, small and medium entity/s by providing short to medium term loans for acquiring capital assets like machinery /equipment, Loan against property, Loan against Property Rentals, etc.

3. Affordable Housing Finance: The company has has an aggressive Affordable Housing finance business and is progressively venturing into tier 2/3/4 towns.

About the opportunity:

The company has a book size of around Rs 5000 Cr and it has aggressive plans to increase the book size to around Rs 15,000 Cr over next 3 years. The volume of business has been growing rapidly and the number of customers even faster because of the focus on small ticket size SME / Housing loans. Hence Analytics is becoming a core requirement of the organization which can lead to cost savings and bring competitive edge.

Job Description:

Responsible for Data Analytics related to Risk, Cross Selling, Business/ Process Development of SME and retail asset segment of the Bank; Provide analytics support for all portfolios on as needed basis

3. Enable analytics driven decision making across risk, business and collections

Some of the projects could include:

Risk Analytics:

1. Development & Validation of Application Scorecards for various loan segments

2. Controlling Business Attrition using Commercial Bureau Triggers

3. Risk Monitoring of Loan Portfolio

4. Monitoring of Loan portfolio:

5. Delinquency Analysis

6. Flow Rates

7. Vintage Curve

8. Attrition Analysis

9. Exploring Multi Bureau Usage for Credit Underwriting in SME/Retail Segment

Sales / Marketing analytics:

Using statistical & predictive modelling techniques like linear regression, logistic regression, decision trees, k-means clustering etc. for various areas of Asset Analytics like:

1. Customer acquisition and attrition

2. Portfolio level customer segmentation

3. Propensity for cross-holdings, product per customer, next-best product

4. Identifying potential customersfor up-migration to higher customer segment

5. Development of X-sell programs

6. Generating Analytics based Leads using Commercial Bureau data

7. Loan approval Scorecard

8. Risk based pricing model

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