Relationship managers of financial services firms are increasingly challenged with achieving a trusted advisor status with their clients. There is a tremendous opportunity to gain a deeper understanding of what a client really values by the correlation and analysis of massive amounts of client, product, and market-related data at their disposal. However, conventional approaches that rely on business intuition and armies of analysts cannot keep pace with evolving client behavior, products, market conditions, and regulations, as well as the growing complexity of the data. While these approaches can surface the macro-trends in client preferences, they fail to uncover the more subtle relationships that exist between a bank’s clients and its products.
Machine intelligence software represents an innovative, new approach to helping banks create behavior-based client profiles to meet that goal. It brings together a broad range of machine learning, geometric, and statistical algorithms with TDA to rapidly correlate and analyze client, product, and market-related data. It uncovers subtle, precise client sub-segments from highly complex data. The underlying attributes that describe each segment inform the development of precise client profiles as well as predictive models that can be dynamically updated.
Using Ayasdi’s software and resultant financial segmentation models, banks can create models that help precisely segment their clients and predict the likelihood of their transacting in specific products. They can precisely segment their best and worst performing relationship managers and identify optimal client-manager pairings. Banks can also create models that inform the composition of optimal portfolios based on specific market conditions. They can also develop models that accurately predict asset churn to devise targeted retention strategies. Ayasdi’s software can empower relationship managers with data-driven insights and analysis that help them personalize product recommendations to clients, thereby driving higher-value relationships and revenue.