In financial services, as in other industry contexts, the transformation process towards an Ai-driven company is underway. The heart of the banking system revolves around the customer. The Customer is “centric” in this context, and the Banks are in great competition to offer increasingly adequate services to the end customer. In this context, the request was to update Customer Insight services with Machine Learning technologies.
It is a modern Customer Insight solution based on Big Data with the use of Machine Learning services in order to know the value of Customer data (from loans, to payments, to mortgages, to insurance, to customer care) present in the various banking “silos”, integrate them and provide Advanced Analytics thanks to Machine Learning.
The Machine Learning services implemented are: usable services such as Advanced Analytics; are based on Customer Scoring to determine Customer Value; are able to forecast in the future based on its financial behavior to help make decisions in Retention strategies.
The 360-degree view of the customer provides customer profiling and captures and updates their behaviors continuously thanks to continuous learning.
In this context, Machine Learning processes exceed the objective of Business Intelligence processes, in most of the banks already present in the company, but collaborate with these systems to study the data collected, and give value to the customer with a medium, short and long-term predictability of customer behavior.
Customer Insight is obviously not a new topic, but, in an increasingly rapid and rapid context, capturing customer behavioral changes over time quickly, thanks to Machine Learning, assumes a decisive importance in order to help the Management of a Bank to define new solutions or new proposals to end customers.
Realization of the end-to-end Machine Learning service, from the creation of Machine Learning Models, Integration into Business Systems, MLOPS Procedures (with ApiRest & microservices), and Advanced Analytics.