ROLES AND RESPONSIBILITIES

DOES (The tasks / responsibilities that the role performs to address requirements in Key Result Areas)

Acquisition Policy Development & Optimization:

• Analyze and assess creditworthiness of potential eligible base (EB) using various data sources, alternative data metrics and internal scoring models.

• Contribute to the development, implementation, and refinement of acquisition credit risk strategies and eligibility policies, ensuring adaptability to both direct retail users and partner-led (B2B2C/B2B2B) segments.

• Monitor the effectiveness of current credit strategies and recommend adjustments based on portfolio performance, market trends, and risk appetite.

• Utilize statistical analysis and modeling techniques to enhance risk segmentation and decision-making frameworks.

• Evaluate the risk profile and operational stability of B2B platform partners while simultaneously designing consumer/merchant risk frameworks tailored to that partner's specific distribution channel.

Data Analysis & Reporting:

• Collect, analyze, and interpret large datasets related to loan originations, early portfolio performance, and partner-specific cohort behavioral trends .

• Develop and maintain regular reports on key risk indicators (KRIs), eligible bases (EBs), disbursements, partner program utilization, take-up rates, and other relevant metrics .

• Present findings and recommendations to senior management and other stakeholders in a clear and concise manner.

Portfolio Monitoring & Management:

• Monitor early portfolio performance at both the partner level (B2B concentration) and the end-user level (B2C credit performance) to spot emerging risk trends.

• Collaborate with collections and portfolio management teams to understand the impact of acquisition strategies on downstream performance.

Collaboration & Process Improvement:

• Work closely with cross-functional teams, including Products, Tech, Sales, and Business Development (BD), to optimize loan workflows and scale risk mitigation capabilities

• Support the BD team by evaluating the risk feasibility of new partnership ecosystems, co-creating flexible but secure commercial underwriting criteria..

• Identify opportunities for process improvements and automation within the credit risk function.

• Participate in ad-hoc projects and initiatives related to credit risk management.

QUALIFICATIONS (Minimum requirements in terms of experience and background, skills and competencies for sourcing purposes)

Education:

• Bachelor's degree in Finance, Economics, Statistics, Mathematics, Business Administration, or a related quantitative field. A Master's degree is a plus.

Experience:

• Ideally an experience in consumer credit risk management, underwriting, or a similar analytical role within the financial services industry.

• Experience or strong exposure to hybrid risk models, such as embedded finance, BNPL, marketplace lending, or partner-led/B2B2C distribution channels, is highly advantageous.

• Strong understanding of lending products, credit lifecycles, and automated credit risk principles. Basic familiarity with corporate financial health indicators or merchant risk factors is a plus.

• Experience with credit scoring models, statistical analysis, and risk assessment techniques.

• Knowledge of relevant regulatory requirements for retail and consumer lending.

Displays (The Knowledge, Skills, and Behaviors indicating how tasks / responsibilities will be performed)

• Excellent analytical and problem-solving skills with a strong attention to detail.

• Strong quantitative abilities and experience working with large datasets (encompassing both traditional consumer credit metrics and partner transactional logs).

• Familiarity with alternative data scoring (e.g., e-commerce transaction history, telco data, or payment gateway logs)

• Effective communication skills, both written and verbal, with the ability to present complex information clearly.

• Ability to work independently and as part of a team in a fast-paced environment.

• Strong organizational and time management skills.

• High level of integrity and ethical standards.

• Proactive and results-oriented mindset.

• Knowledge in data analysis tools (e.g., SQL, Python, R, SAS) 

KPIs

• Risk-Adjusted Revenue Growth: Contribution to revenue growth from new business initiatives, weighted by associated credit risk.