AVP - Credit Monitoring & Analytics (5-10 yrs)

Key Responsibilities

1. Portfolio Analysis:

o Analyze the performance of the mortgage loan portfolio to identify trends, risks, and opportunities.

o Monitor portfolio metrics such as delinquency, repayment trends, and credit quality.

2. Credit Underwriting Oversight:

o Oversee underwriting standards to ensure alignment with company policies and risk appetite.

o Evaluate high-value or exceptional cases as needed to support the underwriting team.

3. Risk Management:

o Identify early warning signals for potential defaults and recommend corrective actions.

o Develop and maintain credit risk models to forecast potential losses.

Data Collection & Reporting

1. Data Collection & Processing:

o Gather, clean, and validate data from multiple sources for analysis.

o Maintain a robust database for real-time monitoring of credit performance.

2. Reporting:

o Create dashboards and regular reports for senior management, summarizing portfolio health and performance.

o Provide insights and actionable recommendations to improve portfolio quality and profitability.

Stakeholder Management

1. Collaboration:

o Work closely with underwriting, risk, and collections teams to enhance credit monitoring processes.

o Liaise with technology teams to implement automated solutions for credit monitoring and data analysis.

2. Regulatory Compliance:

o Ensure adherence to regulatory requirements related to credit monitoring and portfolio management.

o Support internal and external audits as needed.

Key Skills and Competencies

- Technical Expertise:

o Proficiency in credit risk analysis, portfolio monitoring, and statistical modeling.

o Strong understanding of mortgage lending processes and underwriting standards.

- Analytical Skills:

o Advanced knowledge of statistical tools and software (e.g., SAS, R, Python, or Tableau).

o Ability to synthesize complex data into actionable insights.

- Leadership and Communication:

o Strong stakeholder management and the ability to present insights to senior leadership.

o Experience leading or mentoring teams in data-driven decision-making.

- Attention to Detail:

o High degree of accuracy in analyzing and interpreting data.

o Ability to identify and address anomalies effectively.