In Sir Arthur Conan Doyle’s novel “A Study in Scarlet,” the singular Sherlock Holmes proclaimed, “It is a capital mistake to theorize before one has data.” That’s not only sound advice for sleuths, but it’s also wisdom that many insurers should take to heart.
Data is a crucial component of the insurance business, but as any underwriter will tell you, it’s also wildly asymmetrical. No matter the case being handled, insurers never know everything about the risk they’re writing and are often at the mercy of information that, like a game of Telephone, flows from the policyholder to the agent and then, finally, to the insurer.
Even insurers that build in-house models can fall victim to the limitations of their data. That’s especially true if the insurer isn’t a massive company or is unable to leverage a consortium to flesh out a data set. A consortium — like the one we offer at Valen Analytics — provides a wealth of detailed transactional data that can fill in information gaps insurers might have and prevent them from making capital mistakes of their own.
Let the Numbers Even the Odds
The potential a more robust data set has to even out the balance of power between insurers and policyholders isn’t some pie-in-the-sky theory. The success insurers have had leveraging Valen’s data consortium to support their analytics programs show that it’s an investment worth making. Here are a few reasons a program built on data with greater breadth and depth can be such an asset to an insurer:
- It more accurately matches risk to price.
When properly built and utilized, advanced data analytics help ensure that policyholders are correctly charged for the risk they present. Underwriter and agent influences combine with data science to reach a more nuanced decision.
Metromile, for example, has instituted a pay-per-mile business model to provide customers with more affordable car insurance rates. The insurer uses data to calculate how much risk a driver poses and informs agents and underwriters. The approach not only implements transparency into pricing, but it also provides a more customer-friendly insurance experience.
Slice Labs used a similar concept to turn data-driven pricing into an entirely new business model. The outfit provides insurance for the Airbnb set. Hosts pay for only the length of time a guest is staying to receive coverage for things like property damage, high energy costs, and infestation.
- It can help identify fraud.
Getting rid of fraud benefits everyone, but regularly auditing every single policy on the books is simply unrealistic. While there are common methods to catch major instances of premium fraud, many smaller but still harmful incidents go unseen.
However, fraud analytics powered by a robust data set can perform checks and raise red flags much more efficiently than humans can, which can have a huge impact on a company’s bottom line. Extensive data sets can also be used to improve customer experience, specifically when it comes to identifying patterns of fraud and areas where fast claim processing can boost a customer’s satisfaction rating.
Insurers can use the existing data collected by consortiums to pinpoint those trends and reduce the need for additional questions and scrutiny when the policyholder is already in a vulnerable position. All these data points can be used to resolve claims fraud in an efficient, convenient, and clear manner.
- It can triage claims more quickly accurately.
Data analytics can be a boon to claims adjusters, ensuring they don’t overlook something important while reducing cycle times by as much as 15 percent, according to a LexisNexis study. They help adjusters more effectively triage claims and use more customized experiences to significantly improve claimant outcomes and get them back to full health faster.
An enhanced data science outlook can provide adjusters with a clearer picture of whether a specific claim could lead to large losses. In the long run, data analytics can ultimately be a cost-saving measure that allows insurers to anticipate risk and control claim costs.
Insurance has a reputation as a necessary evil. According to research by Ernst & Young, 57 percent of consumers are unhappy with their insurance. People use it only during times of pain and, even then, are reluctant to submit a claim for fear that their rates will increase. As insurers become more data-driven, increased fairness and transparency can change that perception.
With data analytics, insurers can become better acquainted with their customers and use that knowledge to provide high-quality, relevant, and cost-effective services. Capital mistakes are ill-affordable for insurers or policyholders. Let data close the book on them.
If you’re interested in finding ways to use data more deliberately and effectively, click on this link to see the number of solutions Valen Analytics provides.