Question: How effective are insurers at sorting throughmounds of information and turning that allow them to makeinsightful decisions?

Overall, the insurance industry lags considerably behind otherfinancial services in sorting through the mounds of informationthey possess to make insightful decisions. The industryshould receive an “A” for aspiration, finally embracing the valueof analytics and beginning to invest significant resources to theprocess. At the same time the industry should receive no morethan a “C” for how effectively it has integrated analytics intodaily processes around underwriting, claims and customerservice.

Of course this evaluation varies significantly when looking atspecific insurers, lines of business and business functions. Some major insurers have been investing heavily in staff andoutside consulting services to begin mining data and enriching itwith external information. Certainly the greatest progresshas occurred in fraud investigation, catastrophe modeling, consumermarketing segmentation, personal insurance underwriting and highfrequency claims functions. Very little progress has beenmade in using advanced analytics for larger commercial insuranceand customer service support.

So what have been the major constraints to achieving greatereffectiveness to this point? It most definitely is not thelack of available analytics software and the skilled resources toprovide support to making insightful decisions. Tools fromthe robust suites available from firms like SAS and other softwaredevelopers to the services of major consulting firms like Accentureand IBM are readily available along with packaged servicesavailable to insurers.

In addition to internal staff, firms can use skilled low costoff-shore analytics resources. Massive amounts of data can bedownloaded onto portable drives that fit in a small briefcase. Theprimary constraints to faster adoption of analytics into insuranceoperations are internal and in some ways unique to theindustry.

1. Regulatory issues: All analytics must be developedthrough the prism of regulatory compliance. Many researcherscame from other industries with far fewer constraints on howinsightful information can be used and thus initially reached somedead ends that negatively influenced executive acceptance. Valuable opportunities have been lost when the analysis did notconsider from the outset how the insight could be implemented on astate-by-state basis.

2. Craft culture: The industry grew from a craft learningmodel where knowledge came from training by an expert andexperience, which still remains to a large extent. Thatphilosophy can undermine the acceptance of analytics support in thefield, especially when staff professionals interpret what theexecutive says about analytics being useful, but judgment is mostimportant. Behavior modification has proven difficult evenwhen available to the “expert”.

3. Systems priorities: Many times insightful researchcannot be implemented due to higher priority system requirements,suffering from less certain cost/benefit comparison to some morebrick and mortar process improvements. The most effectiveapplication of these insights require complex development of nearreal-time support for decision making by the underwriter, claimsspecialist or service representative.

The industry is on the road to using advanced analytics forinsightful decisions with exciting potential, but still hassignificant constraints to overcome in achieving highly actionableresults.

Frank Cacchione is CEO of TNC Management Group, specializingin applying advanced business analytics, systems development, andproject management support for the insurance industry. He has had awide range of consulting and senior management experience in theinsurance and reinsurance industry. He has consulted with Insuranceorganizations in North America, Europe, Latin America and theMiddleEastas a Partner with Tillinghast/TPF&C, PA Consulting Groupand AMRE Consultants.