Purpose of the role

• The Financial Crime (FC) Detection & Digital Enablement CoE is an integral part of the HSBC group’s Financial Crime function. The CoE helps detect and mitigate Financial Crime Risks across HSBC group and regions through conceptualization, development, deployment and maintenance of Financial Crime Detection solutions.
• Risk Analytics & Modelling roles are responsible for modelling and analytic controls covering design, development, implementation, optimisation and validation. They provide provision of analytics to identify risks, new risk trends, management information, forecasts, and recommend model or control amendments to address these specifically for non-Regulatory Risk purposes.

In this role, you will:

• Conduct end-to-end model monitoring, including performance evaluation, drift detection, and trend analysis for machine learning models.
• Collect and analyze data related to model performance identifying potential issues and areas of improvement.
• Evaluate model performance against predefined metrics and identify potential degradation or bias.
• Investigate and diagnose the root causes of performance issues, collaborating with model developers to address them
• Independently develop and implement monitoring tests to measure model accuracy, efficiency, and stability.
• Communicate model performance insights clearly and concisely to senior stakeholders and suggest potential solutions for model degradation.
• Collaborate with internal and external stakeholders to ensure comprehensive monitoring and alignment with business priorities. Support feedback loops for model refinement and retraining as needed.
• Provide input and insights for governance, audit, and compliance reviews as necessary.
• Ensure adherence to governance frameworks, policies, and best practices in model monitoring.

To be successful you will:

• Have a strong background in statistics, data analytics, and machine learning, along with knowledge of Machine Learning Operations and model monitoring best practices.
• Experience with machine learning models and algorithms. Understanding of different model types and their performance characteristics
• Understanding of Global Financial Crime landscape and the various risk typologies/dimensions/classifications and having good visibility to the eminent changes in landscape.
• Existing Financial Crime Detection capabilities and the limitations therein.
• Awareness of technological advancements in Financial Crime detection capabilities.
• In-depth Knowledge & work experience in tools like SQL, Python, and any visualization tool like Qliksense would be added advantage.

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You’ll achieve more at HSBC

HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.”

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