Building Analytics into Insurance Value Chain

In times when Insurance industry is facing stiff competition and harsh regulatory regime, it becomes imperative for Insurers to develop capabilities for pro-active interventions. Such a capability can be developed through embedding Analytics in  day to day decision making which when combined with business judgement can deliver powerful results. Infusing analytics into the DNA of the company can help Insurers identify opportunities that are not easily visible. Predictive Analytics has achieved successful results for many Insurers worldwide.

  • A leading Insurer utilized customer behavioral analytics to increase profits by more than 2% of GWP.
  • An Australian life insurer used Predictive analytics to reduce lapse rate by 1.1% in six months, resulting in 7% increase in NPAT.

Analytics across Value Chain

Predictive Analytics can be adopted across different functions, namely, Customer Acquisition, Customer Retention, Agency Channel Productivity improvement and retention, New product development etc. Below graph represents key areas where analytics can be applied.

Starting your journey?

Business leaders and stakeholders often think about right time to start looking at analytics and sometimes fall shy due to concerns surrounding data availability, quality of data, conflicts between internal stakeholders and ROI from such an initiative. However Insurers need to develop robust analytics capabilities now more than ever. Following things need to be addressed for achieving success

  • Define your business objective clearly & start with a Pilot project
  • Take all stakeholders on board from respective functional teams, IT teams and other key decision makers.
  • Identify and involve right talent for execution.
  • Ensure right implementation and training of team members.
  • Have a proper feedback mechanism to capture results that will measure the success of initiative and help refine it further.

Key Initiative Areas

  • Persistency Improvement
  • Agency Channel Retention and Productivity Improvement
  • Policy Mis-Selling
  • Claim Fraud Detection
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