Risk Manager
LEFTFIELD SOLUTIONS Abu Dhabi
Job Description
A key role responsible for overseeing the health and performance of the company&aposs portfolio at the group level. This position involves developing and implementing robust monitoring frameworks, conducting in-depth data analysis to identify trends, risks, and opportunities, and providing actionable insights to support strategic decision-making, risk mitigation, and portfolio optimization.The role will collaborate closely with risk, credit, product, and finance teams to ensure the portfolio aligns with the organizations risk appetite and business objectives.
Portfolio Monitoring & Reporting:
- Design, develop, and maintain comprehensive portfolio monitoring dashboards and reports tracking key performance indicators (KPIs) and key risk indicators (KRIs) such as delinquency rates, default rates, loss severity, vintage performance, and portfolio concentration.
- Automate and streamline reporting processes to ensure timely and accurate dissemination of portfolio insights to stakeholders.
- Monitor portfolio trends against established benchmarks, risk appetite limits, and industry best practices.
Data Analysis & Insights:
- Conduct deep-dive analyses of the loan portfolio to identify emerging risks, uncover performance drivers, and assess the impact of new initiatives or market changes.
- Perform segmentation analysis (e.g., by product, geography, customer segment, credit score bands) to understand varying risk-return profiles.
- Analyse portfolio vintage performance to assess underwriting quality and the effectiveness of credit policies over time.
Early Warning Systems:
- Develop and implement early warning systems to proactively identify deteriorating credit quality or adverse portfolio trends.
Risk Analytics & Modelling Support:
- Support the development, validation, and ongoing monitoring of credit risk models (e.g., Probability of Default, Loss Given Default, Exposure at Default).
- Utilize statistical and analytical techniques to forecast portfolio losses, provisions, and other key metrics.
- Collaborate with the data science team to leverage advanced analytics and machine learning for predictive insights and risk assessment.
Cross-Functional Collaboration & Communication:
- Work closely with the Risk team to provide data-driven insights for policy adjustments and underwriting criteria.
- Partner with Product teams to assess the risk implications of new product launches or changes to existing products.
- Collaborate with Finance and Collections teams on forecasting, provisioning, and recovery strategies.
- Clearly and concisely present analytical findings, insights, and recommendations to senior management and other stakeholders.
Data Governance & Quality:
- Responsible for fetching and mapping standardised templates for holding companies and supporting subsidiaries.
- Ensure the accuracy, completeness, and integrity of data used for portfolio analysis and reporting.
- Work with data engineering and IT teams to improve data infrastructure and accessibility for analytics purposes.
Qualifications:
- Bachelors degree in a quantitative field such as Statistics, Economics, Finance, Mathematics, Computer Science, Engineering, or a related discipline.
- 10-15+ years of experience in data analytics, portfolio monitoring, or credit risk management, preferably within the lending or fintech industry.
- Strong proficiency in SQL for data extraction, manipulation, and analysis.
- Advanced skills in data visualization tools (e.g., Tableau, Power BI, Qlik Sense) to create impactful reports and dashboards.
- Experience with statistical programming languages (e.g., Python, R) for data analysis and modelling.
- Solid understanding of credit products, credit lifecycle, and key risk metrics.
- Excellent analytical, problem-solving, and critical-thinking skills with a strong attention to detail.
- Ability to translate complex data into actionable business insights.
- Strong communication and presentation skills, with the ability to convey technical information to non-technical audiences.
- Proven ability to work collaboratively in a team-oriented environment.
Preferred Qualifications:
- A relevant professional certification (e.g., FRM, CFA) is a plus.
- Experience with big data technologies and cloud-based data warehousing solutions.
- Familiarity with AI & machine learning techniques and their application in credit risk.
Experience in developing and implementing automated reporting solutions.
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Job Description
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Job Description
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