Description

Key Responsibilities

Credit Strategy & Underwriting

  • Develop and optimize credit policies, underwriting rules, approval thresholds, credit limits, and pricing for personal loans.
  • Conduct deep dive analysis on application fraud, firstparty risk, and early delinquency signals.
  • Review complex manual underwriting cases and set escalation frameworks.

Portfolio Monitoring & Risk Analytics

  • Perform vintage analysis, roll rate analysis, and cohort forecasting to predict credit losses.
  • Track core risk KPIs including but not limited to: approval rate, default rates, day past due, roll rates, and loss given default.
  • Build automated dashboards and weekly/monthly risk MI for leadership and investors.
  • Identify emerging risks, early warning indicators, and portfolio concentration; recommend mitigation actions.
  • Conduct stress testing and scenario analysis under changing economic conditions.

Testing & Optimization

  • Design and measure A/B tests for credit rules, data sources, and customer segments.
  • Evaluate new alternative data to improve predictiveness.

Compliance & Governance

  • Ensure alignment with local lending regulations, fair lending, and responsible lending standards.
  • Support internal audit, risk reviews, and investor due diligence on credit policies and performance.
  • Document policies, decision logs, and model governance materials.

CrossFunctional Partnership

  • Advise product and engineering on credit risk features and decision engine logic.
  • Partner with operations to streamline verification and reduce friction.
  • Support funding partners and capital markets with portfolio risk reporting.

Required Qualifications & Experience

  • Bachelor’s degree in Finance, Economics, Statistics, Mathematics, Business, or a quantitative field.
  • 5–7 years of handson credit risk experience in personal loans, consumer finance, fintech, or NBFC/bank retail lending.
  • Proven track record building credit strategies, or underwriting policies for lending business.
  • Strong SQL and Excel proficiency; experience with Python/R or analytical tools (SAS, Tableau, Power BI) is required.
  • Deep understanding of risk metrics: PD, LGD, EAD, vintage analysis, roll rates, loss forecasting.
  • Experience with A/B testing, decision engines, and credit bureau data.
  • Knowledge of regulatory compliance in consumer lending (local laws, data privacy, fair lending).

Preferred Skills

  • Exposure to alternative data and machine learning in credit decisioning.
  • Strong stakeholder management and presentation skills.
  • Experience in an Ontario fintech startup or high-growth alternative lender.