Efficient Risk Management in Banking Through Artificial Intelligence

Artificial Intelligence (AI) and Machine Learning (ML) represent transformative technologies that offer significant opportunities for the banking sector. Concerning bank’s risk management, the use of AI and ML enables more efficient and accurate risk assessments and governance, which helps to ensure financial stability and security while increasing the efficiency of banking processes.

LBBW is currently in an early phase of incorporating AI/ML – initial ideas have been developed in various areas, but detailed strategies or implementation plans have not yet been formulated or executed.

Zühlke supports as an innovation partner in the development of a portfolio of relevant and value-adding AI/ML use cases. The development of the portfolio involves the participation of relevant stakeholders and departments at LBBW.

The joint approach takes place in three steps. The starting point is a comprehensive market and trend research. This is followed by:

In just eight weeks, Zühlke develops ten specific use cases based on previously identified challenges and pain points, where AI/ML technologies contribute to improving business processes, minimizing risks, or creating new opportunities.

The use cases range from appraisal generation and market research to sanctions clause contract reviews, property valuation checks, automatic customer monitoring, and focus requests in loan applications.

The chosen method enables use cases to be closely aligned with the challenges and needs of the respective departments.