Case study: Personalized Recommendation Solution for a Leading Financial Services Firm
About the Client
The client is one of the largest financial services company in India, focused on lending, asset management, wealth management and insurance. The company is spread over 1400 locations, and is engaged in consumer finance businesses, life insurance, and general insurance.
Business Context
The client has huge Portfolio of products including lending, wealth, insurance and credit card. They were looking to improve cross-selling to counter growing competition. The challenge was to understand immediate and life stage-based customer needs and equip sales agents to sell better.
BRIDGEi2i Solution
BRIDGEi2i’s Personalization solution helped the client identify relevant cross-sell offers and design personalized recommendations for customers based on life stage and affluence. The solution brought much needed science to their campaign process and helped deliver enhanced customer experience.
The Data Engineering experts at BRIDGEi2i used pre-designed ETLs and API to read, extract, transform and load data. A host of data sources are used such as Decision System-DMP, Online property – CRM, Bureau, CMS/LMS, Geo-data, docs/images, Voice interaction, email and chat data, Social and external data were also considered.
BRIDGEi2i’s AI Labs deployed unsupervised learning and machine learning algorithms to build Personalized recommendations across multiple financial products based on customer life-stage. BRIDGEi2i’s personalized recommendation engine was implemented in business interaction layers such as customer app, for self-service, and CRM system that displayed recommended offer customized based on real-time customer information.
BRIDGEi2i’s consulting team and AI labs built and deployed a customized recommender capable of recommending the next-best action to sales associates.
