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Big Data and Advanced Analytics – Deloitte

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Article Synopsis :

In the research presentation “Big Data and Advanced Analytics: Are You Behind the Competition?”, the Deloitte team highlights the current and futuristic use cases of predictive analytics in the field of P&C, health, and life insurance.

 The Digital Insurer reviews Deloitte’s Report on Big Data and Advanced Analytics - Are You Behind the Competition

Investing in and mastering Big Data and predictive analytics is a sure fire way for insurers to gain competitive advantage 

in Big Data and predictive analytics

In P&C, analytics is now considered essential to remain competitive. The leading P&C companies typically apply analytics across the entire insurance lifecycle:

  • Distribution
  • Rating and pricing – Rate Plans
  • Underwriting – Loss Ratio Models
  • Claims management – Fraud, Adjuster Assignments, Duration and Severity of claims
  • Customer Lifetime Value – Retention, Cross-sell, Up-sell and overall risk management

In Health, analytics have a growing presence in:

  • Consumer Acquisition
  • Member Retention
  • Impairment and Cost Prediction
  • Early Disease Identification
  • Wellness and Change Behavior

Though Life insurance lags P&C and Health in analytics tools and capabilities, Life insurers are coming alive to the power of analytics in:

  • Agent Recruitment
  • Target Marketing
  • Application Triage
  • Proactive Retention Management
  • Cross-Sell / Up-Sell

Farsighted leaders in a variety of domains are increasingly aware of the competitive and operational advantages that analytics can bring. IBM recently reported that nearly three-quarters of insurance companies believe big data and analytics will give them a competitive edge. The Chartered Institute of Loss Adjusters showed that 82% of industry professionals believe organisations which do not utilise big data will become uncompetitive.

Advanced analytics span the entire insurance value chain.   Key application areas identified in the report are:

  • Agent Recruitment / Retention
  • Design & Develop Products / Services
  • Marketing Campaigns
  • Assess Client Needs / Illustrate Value
  • Submit & Process Applications / Orders
  • Enroll New Customers / Applications / Orders
  • In-Force Management

The report identifies four key considerations for implementing an organisation-wide analytics program:

  1. Tools – Does your organization have the tools to capture, store, and analyse the expanding universe of data?
  2. Human Resources – Does your organization have the people with right business and technical skills to design, build and implement advanced analytics solutions?
  3. Big Data – Does your organization have a plan for dealing with Big Data (i.e., unstructured data from a variety of sources in massive volumes)?
  4. Patience – Is your organization committed to the vision? Developing analytics capabilities takes time, hard work and resources.

Link to Full Article:: click here

Digital Insurer's Comments

Most insurers today are focused primarily on mining internal data for potential customer and product insights. External data, collected on a daily basis through regular actions such as using a credit card, magazine subscriptions, prescription drug history, and lifestyle habits, available from sources such as Axciom, Experian, Carfax, LexisNexis, and the U.S. Census Bureau, is growing in availability and popularity.

Leveraging data for more effective decision-making in the fields of product design, sales, marketing, underwriting, and claims is a stated priority for over 60% of insurers. With cost- effective data analysis tools entering the market on an increasingly regular basis it makes sense to look to the data for new ways to  reduce costs, manage risk and improve pricing.  As highlighted by Deloitte, market leaders are already benefiting from investments in data capabilities. We believe the ability to warehouse data from internal and external sources is table stakes in insurance today.  The ability to synthesize and crunch large amounts of data from a growing array of sources will be the key differentiator moving forward.

Link to Source:: click here

 

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