Data Engineering, Analytics & AI/ML | Tech Mahindra

Enabling Custom Data Strategies

Insurers face significant challenges due to legacy systems, inconsistent data, and inadequate analytics. Rising customer expectations and risk management costs necessitate effective data strategies and governance. Key priorities for insurers include understanding customers, providing hyper-personalized services, and addressing operational inefficiencies like fraud, lengthy documentation processes, policy risk, and manual data validation.

Solution Overview

Insurers must deploy advanced analytics and AI/ML to streamline business operations and improve profitability. We help Insurers build data and analytics capabilities in the following four areas to address their business challenges:

Core Data Management
  • Consulting: Audit, Strategy, Roadmap 
  • Migration: On-Prem, Cloud, Multi-Cloud
  • Management: Data Governance, Data Catalog, Data Quality, MDM, Meta Data Management
  • Operations: Data Ops and Data Observability
Data Modernization
  • Data Platform Architecture and Build: EDW, Big Data, Data Lake, Delta Lake, Lakehouse
  • Modern Data Integration and Availability: ETL, Data Fabric, Data Mesh, Data Virtualization, Data Composability, Streaming Data
Value Realization
  • Data Marketplace
  • Data Visualization and Business Intelligence
  • AI/ML Model Engineering
  • AI Delivery
  • Data Science
  • Dissemination

Insurance Use Cases

Marketing, Sales and Distribution
  • Market basket analysis
  • Hyper-personalization
  • Agent/customer churn prevention (Retention management)
  • Value based prospecting
  • Distribution productivity management
Underwriting, Pricing and Risk Management
  • AI enabled underwriting optimization
  • Pricing analytics/agile pricing
  • Fraud detection
  • Predictive risk analysis
Claims Management
  • AI based claims management
  • Claim prevention using telematics
  • Digital FNOL
  • Claim cost optimization
  • AIML based document management
Proof Points
  • Advanced fraud analytics for a leading US P&C insurer resulting in identification of 21,000 (Fraudulent) referrals amounting to 14 Mn USD is a span on 5 years.
  • Streamlined operations across multiple countries with significant cost savings through ADMS for One of the largest US global life insurer
  • Lapsation modelling for a global insurance major for its India operations. Predictive models developed for agent retention analytics, agent LTV analytics, CLV analytics, lapsation and collection analytics and a business intelligence framework to enable collections intelligence to be used by 600 offices across India
  • End to end BI delivery through agile to a leading provider of general insurance, banking, life insurance and superannuation in Australia and New Zealand, resulting in reduced spend on application maintenance by over AUD 4 million/year and also achieving 98% on time availability of all critical applications

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