Credit Risk Analytics Role - BFSI

Skills required - Python , SQL, Credit Risk Analytics

1. Data Collection: collect extensive data on potential borrowers. This data includes personal information, financial statements, credit history, employment details, and more. They may also use alternative data sources such as social media activity and transaction history to build a comprehensive profile of the borrower.

2. Credit Scoring Models: Credit risk analytics involves the use of credit scoring models. These models assign a credit score to each applicant based on their credit history, income, debt, and other relevant factors. The credit score is a key determinant in the lending decision-making process.

3. Predictive Modeling: Hero Fincorp likely uses predictive modeling techniques to assess the likelihood of a borrower defaulting on their loan. They may employ statistical and machine learning models to analyze historical data and make predictions about future loan performance.

4. Risk Segmentation: Borrowers are often segmented into different risk categories based on their creditworthiness. This segmentation helps Hero Fincorp make more informed lending decisions and tailor loan terms, interest rates, and collateral requirements accordingly.

5. Monitoring and Portfolio Management: Credit risk analytics is an ongoing process. Hero Fincorp continuously monitors the credit quality of its loan portfolio. If borrowers' credit profiles deteriorate or economic conditions change, they may adjust their lending practices and risk management strategies accordingly.

6. Fraud Detection: In addition to assessing credit risk, Hero Fincorp uses analytics to detect and prevent fraud. They may employ advanced algorithms to identify suspicious loan applications and transactions.

7. Compliance: Compliance with regulatory requirements is a critical aspect of credit risk analytics. Hero Fincorp must ensure that its lending practices align with the regulations and guidelines set by the Reserve Bank of India (RBI) and other relevant authorities.

8. Data Security: Given the sensitivity of the data involved, data security and privacy are paramount in credit risk analytics. Hero Fincorp must implement robust security measures to protect customer information from breaches and unauthorized access.

9. Improvement and Innovation: To stay competitive and manage risk effectively, Hero Fincorp likely invests in research and development to improve their credit risk analytics models and incorporate innovative technologies such as artificial intelligence and machine learning.

Qualification - MBA, MTech/BE/ BTech/M.Sc.

Location - Delhi.

Note - Interested candidates can call in 9711096905