While information is the primary currency of the business of insurance, many insurers lack adequate insight to operate as high performers

  • Conventional business intelligence has grown out of a history of compliance reporting requirements for regulatory bureaus and shareholders, and most MIS reflects this
  • The legacy system environment and history of mergers & acquisitions inhibits data quality and timely access
  • Inconsistent reporting standards globally forces complex reconciliation
  • Exposure measurement tools (e.g.., PML models) are confined to single line of business and single peril thereby constraining insurers’ ability to develop integrated, enterprise views of accumulation
  • Operational technologies (e.g.., task management, sales/submission management, call center) are not yet broadly adopted thereby limiting insights into service metrics, sales & submission outcomes, SLA compliance and individual service performance
  • Third party data (e.g.., peer bench-marking, industry loss experience, customer demographics) is not readily integrated into the product development and actuarial processes to ensure profitable alignment with growth expectations

Strategic Importance of Analytics for Insurance

Timely data access and robust analytical capabilities provide measurable, immediate value to the organization.

  • Loss Cost Improvement
  • Ability to more rapidly address pricing leakage issues or market leverage opportunities
  • Ability to optimize capacity allocation in catastrophe exposure territories
  • Improved insight into rating and pricing levers to optimize product filing strategies and underwriting practices
  • Better alignment between premium coding and claims coding to achieve more granular and precise profitability insights
  • Robust trending capabilities for improved loss development management
Expense Savings

  • More efficient and consistent data preparation facilitates data availability & reporting
  • Dashboard, Reporting and What If Modeling tools empower business users
  • Reduced exposure to regulatory fines due to incomplete or inaccurate data
Market share Growth

  • Improved product and geographic analytics enable more focused growth strategies
  • Real-time insight into leading indicators of book movement, market penetration and cross-sell/up sell to proactively manage growth drivers

Improved Customer Service

  • Timely operational metrics to address service turnaround, SLAs and customer retention
  • More granular distribution segmentation to optimize profitable customer segment growth


We take a functional approach to Big Data Analytics,

  • We consider Insurance Analytics as an integrated capability
  • True value and return on investment will only come from understanding core Insurance business functions and the insights to be gained across the spectrum of Insurance capabilities
  • Since end-to-end Analytics projects are often costly and duration long, we believe iteratively delivering value to the business is key to success

Use Cases


  • Product Research
  • Market Territory Analysis
  • Market Segment Analysis
  • Competitor Analysis
  • Distributor Analysis
  • Product Design Performance
  • Historical Product Analysis
  • Rate Making Analysis
  • Pricing Analysis
  • UW Rule Analysis
  • Loss Experience Analysis
  • Contract/ Forms Analysis
  • Product Launch
  • ROI Analysis
  • Product Launch Analysis
  • Impact/ Disruption Analysis
  • What/If Analysis
  • Regulatory/ Trend Analysis
  • DOI Relationship Analysis

  • Agent Performance / Profitability Analysis
  • NB & Quote Flow
  • Hit and Yield Analysis
  • Cancellation Analysis
  • Retention Analysis
  • in-Force Strategy
  • Agent/Distribution Performance Analysis
  • Channel/Access Method Analysis
  • Agency Management Analysis
  • Sales Tool Efficiency
  • Acquisition Cost Analysis
  • Cancellation Analysis
  • Compensation Analysis
  • Relationship Referral Analysis
  • New Business Sourcing Analysis
  • Cross Sell / Up Sell Analysis
  • Lead Management
Pricing / Actuarial

  • Pricing Performance including Tool Usage
  • Predictive Model inputs/outputs/final
  • Predictive Model deviations from Baseline
  • Predictive Model and UW Rule Integrated Analysis
  • Rate Adequacy Analysis
  • Marketplace Analysis
  • Profitability Analysis
  • Loss Ratio Analysis
  • Loss Development and Trending
  • Rate Development and Trending
  • Residual Market Loads (WC)
  • Involuntary Book Analysis
  • Off-Balance Analysis
  • Reserve Analysis
  • Expense Analysis

  • UW Productivity
  • UW Expense Analysis
  • SLA Management
  • Appetite Analysis
  • Segmentation Analysis
  • MBook Mix Analysis
  • Hit and Yield Analysis
  • Referral Rates
  • Authority Analysis
  • Rule Analysis
  • Price/Credit Analysis
  • Agent Performance by Account/Book
  • UW Service Utilization
  • Market Comparison Analysis
  • Competitor Analysis
  • Quality/ Audit Analysis
  • Exposure Management
  • CAT Management
  • Loss Experience Analysis
  • Reinsurance Analysis (Treaty, Fac)

  • Service Channel Analysis & Optimization
  • Service Channel Segmentation
  • Knowledge Management
  • Content Management
  • Workflow Analysis
  • SLA Management
  • Contact Mgmt
  • Turnaround Times
  • Cycle Times
  • Straight-thru processing volume
  • Escalation Analysis
  • Reassignment Analysis
  • Customer Complaint Analysis
  • Policy Error Analysis
  • Span of Control Analysis
  • Self-service Inquiry Analysis


  • Claims Assignment and Routing
  • Fraud Detection
  • Formula Based Reserving
  • Reserve Analysis
  • Claims Handling Effectiveness
  • Claims Processing Efficiency
  • Subrogation Analysis