Prescriptive Analytics

Prescriptive analytics is the uppermost level of insurance analytics and also the most complex one to set up and execute. It examines data influx from a wide variety of internal and external sources and uses a number of techniques, like machine learning, image processing and statistics to come up with comprehensive insights. Prescriptive models not only tries to predict what will happen, but also reasons why it will happen and present variable options on how to take advantage of future opportunities.

Features of Prescriptive Analytics that benefits Insurance organization

  • Data Mining through Prescriptive analysis will reveal unknown and arcane patterns in the historic business processes.
  • Prescriptive pathways helps product design and strategy teams in building calculated plans and at the same time can create scenario based ‘what-if analysis’ that will strengthen strategy.
  • Prescriptive analytics uses optimization strategies to gain insights into what works best under different circumstances
  • Prescriptive models can gaze and plan to better appreciate how changing individual choices of products and services affects the way that people like and use a particular offering.
  • Similarly, it can be used to identify what changes are infeasible and could result in poorer performance.
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Related Pages :

Predictive Analytics Predictive Analytics Reporting & Dashboards Reporting & Dashboards Big DataBig Data Performance EngineeringPerformance Engineering BI AnalyticsBI Analytics

Prescriptive analytic models allow insurers to save millions by quickly detecting and expediting investigation of suspect providers, claimants and claim-level behavior.