The value and impact of data could not be any more present, and important, in each of our lives today. From Google to Facebook and even IBM’s development of “Watson,” data and intelligence are quite literally changing our world.
The insurance industry is built on information. This isn’t breaking news. Certainly underwriters and risk managers have understood the value of data for years. Every policy issued is underwritten based on both historical and predictive data. In many ways, insurers have been at the forefront of data analytics. But at the same time, there is one area where our industry has fallen a bit short: integrating analytics into the claims process.
Building a claims strategy that better leverages data and analytics is the key to unlocking powerful business efficiencies for insurers, large and small. Here are four considerations to keep in mind when developing your claims data analytics strategy:
Break Down the Silos
Too often, varying departments within an insurer simply don’t share information. That’s not to say they don’t talk or communicate, but the real time sharing of information isn’t always happening. Underwriting, pricing, risk management, etc., often are operating in a silo from the claims team. Sure, underwriting looks at historical claims data, but do they understand the story behind that data and are they using the most recent data to inform current day underwriting standards?
Carriers can combat these issues by better facilitating the sharing of data and analysis across business functions. Collaboration is critical, as is speaking the same language (is everyone in your organization using the word “weather claim” the same or is there deviation?).
As elementary as it sounds, it bears repeating that your claims department is your frontline ambassador to customers. By leveraging their data and intel you can build a product (and a business) that fosters deeper relationships with your customers on both an individual and group basis.
Claims departments have access to data that can better inform underwriting, pricing and risk management decisions. By breaking down these silos and increasing communication through analytics, carriers can improve customer services while improving efficiency in their own operational procedures.
Invest in Claims Analytics Personnel
The insurance industry is quickly coming to a precipice whereby we must foster the development of the next generation of professionals. This is a story many have discussed.
But what is not often highlighted as part of this conversation is the importance of attracting professionals with an in-depth understanding of data analytics. Within the insurance industry, there is a limited talent pool of people who are knowledgeable about analytics, big data and insurance. It is time that insurers work to highlight the data-oriented career opportunities that extend beyond traditional IT, marketing and business analytics positions. This is especially important when it comes to claims.
The claims function is no longer simply about inventorying, approving or denying customer requests for coverage. It’s far from it. Today’s carriers must embrace claims data and use this information to the benefit of the entire organization, not just to meet their transactional and operational needs of the individual claim. As such, successful claims teams are hiring individuals who can evaluate and use data to tell bigger, trend stories that inform other portions of the business.
Developing a close collaboration with HR to bolster your company’s ability to compete for scarce analytic talent is critical. If recruiting data talent proves too difficult, look for opportunities to provide training and advancement opportunities for current team members. Building a team of claims professionals who understand how to analyze and tell the story of your data will benefit your organization.
Harness the ‘Right’ Data
Part of the challenge facing claims teams (and insurers in general) is how to decipher the meaningful, important data from the noise. In our technology driven society, access to data is only going to increase as will the cost of building proprietary systems to capture this data.
In order for claims analytics to be effective in deciphering the right balance between customer satisfaction, proper indemnity and overall expense for closing a claim, having access to meaningful (and relevant) data is essential. But what happens when you don’t have access to all the data you need? Don’t have proprietary data in place? No problem. Technology is now providing simpler, streamlined access to third-party data resources like law enforcement databases, insurance industry databases, as well as public record databases that can provide the information claims teams need. These resources can supplement and enhance internal analytics data on claims, providing a fuller picture that expedites claim resolutions.
In a data driven society, more is not always better. The key for claims teams is to identify the right data (whether you own it or not) and use it to build guardrails that help both you and the insured.
Don’t Forget the Customer!
It seems straight forward, but the true power of data and analytics lies in its ability to help the carrier and the customer. Consider this: The Insurance Information Institute estimates that insurance fraud costs property/casualty insurers over $30 billion annually. Unsurprisingly, in many cases these costs will be passed on to the customer. Analytics can (and should) be used to combat this issue. Insurers can protect themselves, improve operational efficiency and (eventually) lower premiums for insureds by more effectively using historical data to identify fraud.
Another customer-centric and important use for analytics is for the prevention of losses before a major weather event like, Superstorm Sandy. Aggregating and understanding data before, during and after a major storm will help claims departments to more effectively deploy resources in the event’s aftermath. How? Before the storm, carriers can pinpoint what policyholders are at risk and can proactively share information on how to prevent a loss.
In preparation for, and in response to a storm, claims teams should harness multiple levels of customer data to build storm severity maps and eventually, a claims loss map. Further, analytics can be used to triage and prioritize claims by providing insights that will reduce travel time for adjusters and decrease the time it takes to address customers during a difficult time.
There is no question that we are in an era of data. As we continue to look for opportunities to innovate and better analyze information we are collecting, insurers must seek to better leverage analytics with regards to claims. Doing so will enhance operations, mitigate losses, and ultimately, allow for a deeper understanding of the markets.
Bob Crowley is vice president of Claims for American Modern Insurance Group.
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