HSBC's Credit Risk Data Analytics Programme

As a project manager, I led HSBC's Credit Risk data analytics programme, which was designed to manage the bank's credit risk exposure by predicting potential losses from its lending portfolio. The programme utilized data analytics tools and statistical modelling techniques to identify, measure, and manage credit-risk exposure proactively.

One of the significant challenges of the programme was balancing the conflicting objectives of the diverse stakeholders involved. Senior management sought more profits, while regulators aimed to reduce overall risk exposure, and this could sometimes lead to conflicts. To address these conflicts, I implemented a communication strategy that ensured transparency and clarification around the programme's objectives to reduce ambiguity and align stakeholders towards a common goal. Another challenge of the programme was the inherent limitations of the modelling process, which could potentially lead to inaccuracies in the data generated from the programme.

There were also data quality and availability challenges, resulting in incomplete or inadequate data. To mitigate these challenges, I oversaw the risk management of the program and enhanced the risk monitoring and management strategies with sensitivity analyses to enable the programme to provide a broader view and adjust to contextual changes more smoothly.