Friday, January 23, 2009

Domainwise Analytics Talk : Insurance Sector

Business Challenges:

·         Increase sales revenue and profitability, while reducing operational costs
·         Improve loss ratios and achieve a higher return on equity
·         Market to customers across channels despite rising campaign costs and dismal response rates
·         Convert pool of data from functional, geographic , channel and other sources across the organization into valuable  intelligence for timely, effective business decisions

Business Intelligence Agenda:

          Align resource more efficiently
          Improve response to marketing campaigns
          Increased Customer Loyalty and Retention
          Maximize customer  Profitability
          Know current and prospective policyholders well enough to predict their profitability and risk
          Realize a rapid ROI

Analytics Techniques:

Agency management

          Agents, predominant sales channel, it is important to understand the essential distribution dynamics
          Analyze the cost of the channel and sub-channel
          Understand overall channel and sub-channel profitability
          Know which agents sell which insurance products to which customers
          Asses sales activity, reach, quality of sales/service and channel effectiveness from multiple dimensions
          Monitor channel performance continuously and intervene as needed with marketing support, training and controls

Risk Based Pricing

Competition and product commoditization have insurers struggling to grow profitability. Risk Based Pricing techniques are useful to analyze the loss experience, and to identify loss behavior influences. It also makes more granular rate structures to grow profitable classes, while charging adequately for other classes

Claims reporting

Claims Reporting is useful to monitor the performance of the P&C claims settlement process.
          Workload distribution reports across the claims handling organization
          Claim spend analyses for understanding true cost of settling claims
          The ability to monitor loss development by product, exposure type, service provider and other dimension to improve reserving accuracy

Customer segmentation

Classifying customers according to their likely behavior and profit potential is crucial for better customer communications and to determine optimum segmentations across customer base and product lines. It also helps in creating more accurate product offers in addition to conveying more effective product communications.

Customer retention

To identify the customers with the highest propensity of lapse and better understanding of their needs is very important. It helps to target high lapse risk customers to improve retention. After all getting new customer is not an easy thing to do, and any retention of customer is as good as getting a new one.

Cross-sell and Up-sell

Cross-sell or up-sell can be done using a score for customer’s cross-sell and up-sell potential. One way to do could be:
          Identify which customers are most likely to buy
          Determine which products they are most likely to buy next
          Target the right customers at the right time through the right channel
          Achieve higher conversion rates for cross-selling/up-selling campaigns

Customer lifetime value

CLV can be built by calculating the present value of customers by considering the current holding and then forecasting their future value, by considering cross-sell, loss and lapse probabilities over defined future period.
The business implementation could be to concentrate marketing spend on customers expected to bring future profitability and prioritize servicing levels accordingly.

Campaign management

Effective Campaign Results can be achieved efficiently by using quantitative, customer centric measurements, and strategic segmentation and behavior predictions. One way to do could be to optimize campaigns and channels by automatically tracking each campaign element and implement complex customer interaction strategies efficiently; it could be multichannel, multistage and event triggered campaigns too. This helps maximize customer intelligence to get the most return from your campaigns

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