Insurance Analytics Suite 2.2™

Self-service Analytics Product for all involved in the Insurance Value Chain.

With years of insurance domain experience, we understand that the biggest pain-point for insurance carriers and intermediaries is realizing maximum value of and for the customer.

Our proprietary application Insurance Analytics Suite™ is essentially designed to meet this need. Insurance Analytics Suite addresses multiple insurance use-cases with the aim of maximizing customer value for insurers.

Designed to shift the onus of analytics processes from Data Analysts to Business Owners, Insurance Analytics Suite targets Ease of Use as a priority by offering a sequential workflow via a three-layered structure - Insurance Data Model, Machine Learning and Application - to cover all from data management to risk insights, planning and monitoring execution, all at one place.

customer value
customer value

Insurance Data Model

At the core of the Suite is Insurance Data Model - a highly scalable tool developed to cater to data management and accessibility needs of the organization.

Insurance Data Model can handle data from multiple data sources, formats, volumes, varieties and types (Numeric, Text and Image), and allows a competitive edge by consolidation of clean data across multiple systems. The model is also equipped to handle AL3 Standard based databases.

Covering Data Input, Data Quality, Automated Variable Mapping, Statistical Inferences and Visualization, it renders an analytics-ready environment for the insurer.

Machine Learning Models

Machine Learning-based predictive models generate propensity scores for retention and cross-sales at the level of each policy and each customer. Based on Policy Transaction Data and Customer Interaction Data, it generates Transaction Risk Scores and Interaction Risk Scores for Renewals and Cross-sales.

This layer allows the user to create predictive models specific to their needs within a few clicks. The 'Goodness of Fit' meter lets the user to check the validity of the model, basis which they can remodel and retune until the best fit is arrived at.

Applications

The Applications layer leverages the previous two layers to drive interventions. This is done through utilizing risk scores generated in the Machine Learning Layer through use-cases such as Retention, Cross-sell, Scenario Analysis, Contact Centre Optimization, Price Elasticity, Profitability among more.

Workflow suited for the business user

Insurance Analytics Suite is designed to generate a sequential workflow that navigates the end-user right from data handling to customer-level intelligence to actions, as well as modify this intelligence for specific actions.

Seamless UI and Role-wise access enable risk insights to reach the entire Insurance Value Chain

Insurance Value Chain Benefits

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