Head - Credit Risk Analytics - BFS

Area of Responsibility :

- Responsible for developing, directing and monitoring sophisticated credit risk management strategies associated with loan acquisition activities.

- Create, update and optimize the risk engine, business rules and scorecards, to assess credit worthiness of customers and their affordability.

Work Activities :

- Act as Thought Leader and Subject Matter Expert in Credit Risk Analytics.

- Responsible for developing, directing and monitoring sophisticated credit risk management strategies associate with loan acquisition activities.

- Drive the "data strategy" - thinking of new data sources, making those data sources available, talking to third parties.

- Align the analytical approach and available data, with Company's strategy.

- Manage data and provide insights from data analysis and statistical models, to enable lending decisions and recommend optimizations

- Willing to get into previously unchartered territory, build completely new Risk Models, with data that has not been traditionally used for Risk Assessment.

- Create, update and optimize the risk engine, business rules and scorecards, to assess credit worthiness of customers and their affordability.

- Own the Predictive Analytics and use data to predict customer behaviour.

- Be the face of the company for external risk and analytics related requirements.

- Operate as a start-up to work with all stakeholders and partners to deliver world class capability.

- Work closely with the Technology and Business Heads.

- Build the Analytics team that is self-sustaining and can make decisions to impact business significantly.

- Develop the team continuously across technical and business architecture .

RELEVANT EXPERIENCE :

- 10-18 years of relevant experience, preferably in credit risk analysis.

- Strong business acumen with prior experience of Credit Risk for Retail Lending/Unsecured Loans in a financial services setup (Banks, NBFCs, MFIs).

- He/she will be a senior analytics leader who has led analytics team and has experience in building a team from the scratch.

- Proven record of delivering significant business value from developing and implementing advanced analytical tools and insights. Love data, the more the merrier. 

- Exposure to machine learning techniques is desirable. Good command over Statistical Techniques such as Logistic Regression, Linear Regression, Predictive Analysis, and Decision Trees. 

- Proficiency in one or more of analytical tools like SAS, R etc. Experience in Python is desirable.

- Ability to network and influence C-Level executives; work in a collaborative environment Experience in a start-up environment and/or in growing a business/organization will be an added advantage.