Product Risk Manager (Secured)

Aditya Birla Capital; Maharashtra; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Aditya Birla Capital in Mumbai seeks a Product Risk Manager to formulate and execute risk-based underwriting strategies balancing customer growth with robust risk controls. You will lead risk segmentation, develop models, and collaborate with Data Science, Product, Business, and Operations to align risk with business goals.

You will evaluate channel partners, mitigate operational risks, analyze MLAP/STSL elements such as fraud mitigation, KYC, and credit checks, and clearly communicate risk

Qualifications

• Bachelor's degree in finance, business, economics, or related field.
• 5–8 years of risk management experience in financial services.
• Strong understanding of MLAP/STSL policy and risk practices.

Responsibilities

• Formulate and execute risk-based underwriting strategies balancing growth with risk.
• Lead risk segmentation based on credit scores and behaviors.
• Develop and refine risk models to improve underwriting decisions.
• Collaborate with Data Science, Product, Business, and Operations teams.

Skills

Risk management

Data analytics

Stakeholder management

Credit risk

Education

Bachelor's degree in Finance/Business/Economics

Tools

R

Python

SQL

Job description

Job Title

Product Risk Manager

Location

Mumbai

• Formulate and execute risk-based underwriting strategies that balance customer acquisition with robust risk management.
• Lead risk segmentation efforts by categorizing loan applicants based on credit scores, financial behaviors, and other key risk indicators to optimize decision‑making.
• Develop and refine risk models to improve underwriting decisions and ensure a strong, high-quality loan portfolio.
• Collaborate closely with Data Science, Product, Business, and Operations teams to ensure risk strategies are aligned with broader business goals and objectives.
• Ensure the smooth execution of lending initiatives by integrating risk management processes and protocols throughout operations.
• Evaluate channel partners based on their business models, product offerings, operational processes, and overall creditworthiness, ensuring strategic alignment with organizational risk policies
• Assess and mitigate operational and process risks in collaboration with channel partners, focusing on minimizing external risks to the organization.
• Analyze and understand MLAP/STSL, including key elements such as fraud mitigation, KYC processes, credit checks, and customer onboarding, ensuring all practices adhere to regulatory standards and mitigate risk.
• Clearly articulate complex risk strategies to both technical and non-technical audiences, including senior management, clients, and channel partners.
• Exceptional presentation skills, capable of representing the organization in discussions with external partners, clients, and stakeholders.
• Demonstrated ability to lead and collaborate with cross‑functional teams across data science, product, operations, and business units.
• Strong interpersonal skills to build and maintain effective relationships with internal and external stakeholders.
• Ability to conduct detailed data analysis and risk assessments, interpreting metrics to drive strategic risk management decisions.
• Innovative problem‑solving approach to address complex underwriting and risk management challenges.

Key Responsibilities

• Formulate and execute risk-based underwriting strategies that balance customer acquisition with robust risk management.
• Lead risk segmentation efforts by categorizing loan applicants based on credit scores, financial behaviors, and other key risk indicators to optimize decision‑making.
• Develop and refine risk models to improve underwriting decisions and ensure a strong, high-quality loan portfolio.
• Collaborate closely with Data Science, Product, Business, and Operations teams to ensure risk strategies are aligned with broader business goals and objectives.
• Ensure the smooth execution of lending initiatives by integrating risk management processes and protocols throughout operations.
• Evaluate channel partners based on their business models, product offerings, operational processes, and overall creditworthiness, ensuring strategic alignment with organizational risk policies
• Assess and mitigate operational and process risks in collaboration with channel partners, focusing on minimizing external risks to the organization.
• Analyze and understand MLAP/STSL, including key elements such as fraud mitigation, KYC processes, credit checks, and customer onboarding, ensuring all practices adhere to regulatory standards and mitigate risk.

Expectations

• Clearly articulate complex risk strategies to both technical and non-technical audiences, including senior management, clients, and channel partners.
• Exceptional presentation skills, capable of representing the organization in discussions with external partners, clients, and stakeholders.
• Demonstrated ability to lead and collaborate with cross‑functional teams across data science, product, operations, and business units.
• Strong interpersonal skills to build and maintain effective relationships with internal and external stakeholders.
• Ability to conduct detailed data analysis and risk assessments, interpreting metrics to drive strategic risk management decisions.
• Innovative problem‑solving approach to address complex underwriting and risk management challenges.

Qualifications

• Bachelor's degree in Finance, Business, Economics, or a related field (MBA or advanced degree preferred).
• 5-8 years of experience in risk management, underwriting, or portfolio management in the financial services industry.
• Strong understanding of MLAP/STSL policy and the associated risk management practices, including fraud detection, credit checks, and process automation.
• Proficiency in risk assessment tools, data analytics, and customer segmentation models.
• Experience in credit risk underwriting, especially for retail or personal loans, is preferred.
• Proficiency in data tools (R, Python, SQL) and a deep understanding of risk models and scorecards.