Tag Archives: Actionable Data

Big Data? How About Quality Data?

While talking about data has become trendy — with terms like big data, small data, dirty data all good candidates for buzzword bingo — the reality is that, big or small, even if it is clean, data is useless unless it drives actionable insights.

Data is the foundational layer that underpins almost every industry, and it is a survival requirement for business today. Industries like retail, travel and finance have all tapped into the power of data to drive consumerization. And, while the health insurance sector may have fallen behind these industries, it is catching up, as today’s health insurance consumers are demanding actionable information in the form of choice, transparency and simple user experiences.

The good news is that innovators in the space are responding to these consumer demands by creating ground-breaking tools — tools that leverage modern technology, powerful software design and quality data. Today’s health insurance innovators are making waves in the insurtech industry by building products and features that truly solve consumer pain points.

So, who are these innovators? What are they creating? And why is the underlying data so crucial?

Who are the innovators?

According to CB Insights, $1.7 billion was invested in insurtech in 2016. Essentially, the insurtech category encompasses all new technologies, companies, apps and business models that are pushing to revolutionize the insurance industry itself. And, thanks to advances in technology and funding, this category is seeing rapid growth.

See also: Why to Refocus on Data and Analytics 

Jump Capital recently pulled together its view of the movers and shakers that are disrupting the insurance industry. With so many new vendors in the market, it is safe to say that there is definitely a lot of moving and shaking going on in insurtech.

These companies are finding different ways to meet consumer demands and remove the complexity associated with the insurance industry. The companies included in the healthcare segment of this infographic are, for the most part, delivering new ways to help consumers find, buy and receive health insurance. Collectively, health insurtech platforms answer a consumer cry for help. But none of these platforms are functional, let alone useful, without a foundational layer of quality data on which to build.

What are the innovators creating?

Health insurtech innovators are working to answer a variety of consumer demands. They’re creating tools that simplify the health insurance shopping experience. Tools that help doctors find prescription drugs that are covered by a patient’s insurance plan. Tools that help consumers find doctors that are in-network. The problems that these platforms solve are many.

Here are just a few examples of innovative tools and features being created to deliver value to health insurance consumers:

1. Decision Support Tools for the Individual Market

A variety of web-based entities (WBEs) have popped up to help individual consumers find and purchase a health insurance plan that is right for them. PolicyGenius is a good example of an innovative platform doing just that. The company prides itself on delivering simple benefits that are personally designed for the individual. A consumer enters a few bits of information, and PolicyGenius recommends health insurance plans for that individual — all delivered through a seamless digital experience.

2. Analysis Tools for the Small Group Market

Certain broker-facing platforms are starting to build analytical tools that help strengthen group health plan recommendations. These tools allow platforms to compare and contrast different health plans, including each plan’s network, aiding in disruption analysis and delivering value to their employer customers.

3. In-Network Provider Search and Notification Features

Many health insurtech platforms offer customers provider-network search and notification features. Stroll Health, for example, delivers personal recommendations for imaging centers based on a patient’s insurance plan. And some HR and benefits administration platforms now have the ability to notify employees if an employee’s preferred doctor drops out of network. Thoughtful features like these save consumers time and money.

See also: Next Step: Merging Big Data and AI  

Why is the data so crucial?

While data may not be the sexiest element of a tech platform, the data layer enables all features. For example, for those broker-facing analysis tools to be useful, the broker platform must have access to accurate and timely data on the benefits and rates of every health plan they’ll compare. For an HR and benefits administration platform to alert an employee when a doctor drops out of network, the platform must first know when that doctor drops out of network. This means the platform must have access to an accurate and extremely granular database of providers in the specific network being tracked. Quality data is what informs today’s innovators, pushing them to take action and build exciting applications that solve real problems.

Health is a complex space, but there are many brilliant minds working to improve the health insurance industry. Putting the right data into the hands of these innovators allows them to do what they do best — solve problems with creative technology solutions. Continuing to do this will allow today’s innovators to respond to consumer pain points and transform the health insurance industry.

New Data Strategies for Workers’ Comp

Workers’ compensation is widely recognized as one of the most challenging lines of business, suffering years of poor results. Insurance companies are under increasing pressure to achieve profitability by focusing on their operations, such as underwriting and claims.

Insurers can no longer count on cycles, where a soft market follows a hard one. The traditional length of a hard or soft market is evolving in a global economy where capital moves faster than ever and competitors are using increasingly sophisticated growth, segmentation and pricing strategies.

Insurance executives also cite regulatory and legislative pressures, such as healthcare and tax reform, as inhibitors of growth. Furthermore, medical costs continue to rise, making it particularly difficult to price for risk exposure. The long tail of a workers’ compensation claim means that the cost to treat someone continues to increase as time elapses and becomes a compounding problem.

Despite recent improvements in combined ratios, there are still many challenges within workers’ compensation that have to be reconciled. The savviest insurers are evaluating the availability of technologies, advanced data and analytics to more accurately price risk – and ultimately ensure profitability.

The ‘Unknown’ in Workers’ Compensation

Information asymmetry has made it difficult for insurers to accurately determine who is a high-risk customer and who is low-risk. At the point of new business, a workers’ compensation insurer is likely to have the least amount of information about those they are insuring, and it’s easy to understand why. The insured knows exactly who is on the payroll and what types of duties employees have. Some of that information is relayed to an agent, and then finally to the carrier, but, as in any game of telephone, the final message becomes distorted from the original.

This imbalance of information is one reason why fraud is rampant, and why insurers ultimately pay the price. Payroll misclassification – or “premium fraud” – occurs when businesses pay salaries off the books, misrepresent the type of work an employee does or purposely misclassify employees as independent contractors. Some misclassifications are not nefarious. But whatever the cause, they create significant revenue and expense challenges for carriers that rely on self-reporting.

The ‘Silent’ Killer

Without the right insight or analytical tools, insurance companies have a hard time discerning between their policyholders and making consistent and fair decisions on how much premium to charge on each policy. When an insurer begins to use predictive analytics, competitors that are still catching up run the risk of falling victim to adverse selection. When we hear executives say things like, “The competition has crazy pricing,” it raises a red flag. We immediately begin looking for warning signs of adverse selection, such as losing profitable business and an increasing loss ratio.

The problem is that it takes time to recognize that a more sophisticated competitor is stealing your good business by lowering prices while also sending you the worst-performing business. By the time you recognize adverse selection is occurring, you’re falling behind and have to respond quickly.

The Power of Actionable Data

Fortunately, there are technologies available for insurers of all sizes to make more informed, evidence-based decisions. But when it comes to data, there is still some confusion: Is more data always better? And how can carriers turn data into actionable results?

It’s not always about the volume of data that an insurer has; it’s about the business value you can derive from it.

If an insurer is just beginning to store, govern and structure its data, it is likely not receiving actionable insights from historic data assets. Accessing a more holistic data set with multiple variables (from states/geography, premium size, hazard groups, class codes, etc.) through a third party or partner can help to avoid selection bias, while encouraging rigorous testing and cataloging of data variables. Having access to a variety of information is key when it comes to making data-driven decisions.

The conundrum insurers face when delivering actionable intelligence that underwriters can use is that they only know the business they write. They know very little about business they quote and nothing about business they don’t even see. What complicates this picture is that an insurer’s data is skewed by its specific risk appetite and growth strategies. It’s up to the insurer to fill in the blind spots in its own data set to ensure accurate pricing and risk assessment. As we know, what an insurance company doesn’t know can hurt it.

As insurers increasingly turn to advanced data and analytics, the next question that keeps insurers up at night is, “When everything looks good, how do I know what isn’t really good?” One way that Valen Analytics is helping insurers answer that question is by providing companies with a “Risk Score,” a standard measure of risk quality. By tapping into Valen’s contributory database, workers’ compensation underwriters can have better insight into all the policies they write – even historically loss-free policies. In fact, the Risk Score accurately identifies a 30% loss ratio difference between the best- and worst-performing loss-free policies. This is one example of how the power of data can push the industry forward.

Despite its many challenges, the workers’ compensation industry is becoming more analytically driven and improving its profitability. A comprehensive data strategy drives pricing accuracy and business growth while allowing insurers to achieve efficiencies in underwriting decision-making. By keeping up with technological advances, insurers can use data and analytics to grow into new markets and areas of business, while also protecting their profitable market share.

While NCCI’s annual “State of the Line” report labeled workers’ compensation as “balanced” this year, we may soon see the integration of data and analytics push the industry to be recognized as “innovative.”