What’s Insurtech, Anyway?

Perhaps it’s a symptom of buzzword fatigue that everyone in the insurance industry seems to use the word “insurtech” without agreeing on – or maybe even really thinking about – what it means.

Some use it as a noun, suggesting a type of company – typically a startup – that applies cutting-edge technology to insurance-related challenges. Others use it as an adjective to describe the technologies and applications themselves. Still others seem to take the position of U.S. Supreme Court Justice Potter Stewart, writing on a very different topic: “I know it when I see it.”

Whatever it is, insurtech is a rapidly growing feature of the insurance landscape, and many traditional insurers and venture capitalists are investing in it.

Insurtech doesn’t just mean offering products more quickly online. It means transforming the offerings and the customer experience.
Modernizing the value chain

Insurtech emerged around 2010 as an offshoot of a similar movement in banking, known as “fintech.” With providers of just about every other product and service embracing “Amazonation,” consumers have come to expect absolutely seamless service – wherever and whenever. Like those industries, insurers need to satisfy their customers while growing profitably and managing operational costs.

But insurtech doesn’t just mean offering products more quickly online. It means transforming the offerings and the customer experience.

Insurtech most consistently refers to the use of apps, wearables, big data, machine learning, and other technologies to automate and improve processes across the insurance value chain – from marketing and policy origination through underwriting, services, and claims.

Some applications focus on reducing friction in transactions; the time required to fill out an application and receive a quote is a classic example. Others seek to streamline and enhance back-end functions, such as risk assessment, pricing, loss control, and settling claims.

Claims: Ripe for insurtech

The claims process is particularly well suited for transformation. Insurers typically hire adjusters to determine the extent of their liability for a loss, damage, or injury and come up with a settlement. This can be time consuming, expensive, error prone, and, in some cases, dangerous.

Drivers can submit photos to their insurers via app immediately after an accident. Some insurers use machine learning and publicly available data to detect fraud.

Today, new approaches aid the claims process.

For example, drivers can submit photos to their insurers via app immediately after an accident. Some insurers also use machine learning and publicly available datasets to detect and flag potentially fraudulent claims.

As technology helps improve underwriting, policy administration and claims, new products are being developed and traditional ones can be handled differently.

One emerging approach – enabled by the intersection of telecommunications and big data known as “telematics” – is usage-based insurance (UBI), priced according to drivers’ own voluntarily provided behavioral data. A more recent stage in UBI’s evolution is pay-as-you-drive insurance, with monthly billing that varies based on mileage driven.

A similar trend involves using data from smart-home technology, such as water-monitoring systems that can anticipate and prevent leaks that might otherwise lead to claims. Advances in telematics and the Internet of Things are increasing the quantity and range of the data insurers will have at their disposal.

Obstacles remain

 Insurtech offers tremendous opportunities for innovation, but – as one of the most heavily regulated and publicly scrutinized industries – it faces obstacles. Many technologists driving the movement come from outside insurance. Few have navigated the legal, regulatory, and cultural minefields surrounding personal privacy and security.

Unlike many other industries, in which maximizing speed and satisfaction has become the prime directive, insurers are required by law to protect customers from privacy breaches and bias. Perusing social media for insights to help optimize user experience or using machine learning to anticipate and address changes in users’ buying behavior may be acceptable if you’re selling cars or cosmetics – but for insurers, their clients, and regulators it raises a host of red flags that have to be addressed.