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.
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’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 techniques to build default scorecards and customer cross-sell profiles. The team assessed the analytical objectives based on customer life cycle stages to build personalization and segment level recommendations.
BRIDGEi2i’s consulting team and AI labs built and deployed a customized recommender capable of recommending the next-best action to sales associates.