Insurance and fintech find their way forward with “insurtech”

There’s pretty much nothing worse than dealing with a traditional insurance company and you have to actually talk to an agent, right? Yeah, “I love my insurance company,” said no one, ever. Much as one wants to shake one’s fist at the poor customer service rep you’re dealing with, they’re not to blame: Typically they’re working with legacy products and processes, and the company they work for is slow to embrace digital transformation.

Fintech startups that are taking on insurance, however, are free from the traditional product and process shackles from the get-go. They can use emerging technologies and build brand-new systems that are designed from the start to head off customer frustration. They can also build products that are very focused and respond to particular customer needs and offer specific value, instead of offering lengthy end-to-end solutions that don’t meet everyone’s needs.

For example, an insurtech can leverage artificial intelligence solutions (AI) (including AI-powered chatbots) to collect data from customers that help it personalize product offerings, or they can create tools to digitize inventories of possessions, or smart contracts can be unleashed to make underwriting and claims processing more efficient.

The other half of the customer experience secret sauce fintech has brought to insurance startups is a simple objective that has, historically, rarely been accomplished: addressing and eliminating the pain points customers have with banking companies.

For instance, while the pandemic made online portals a standard expectation, the incorporation of data science in fintech startups speaks for itself. Meeting the expectation, plainly, isn’t enough. Insurtechs review behavioral data to find what parts of their business processes as well as frontend interfaces are causing difficulty for customers and improve them.

Plainly stated, the customer is playing a larger role in insurance than ever before. Some of fintech’s biggest wins in competition with traditional insurance companies have come simply from fintech solutions like data science applications and AI to better learn what customers want.

When you’re building a fintech app of any type (and figuring out the cost of building a fintech app), you need to think carefully about your customer segments and what they actually want. Millennials, for example, naturally favor mobile channels for financial transactions, and they tend to look for a fun factor when it comes to their financial apps. Practically speaking, that means a substantial customer base is up for grabs no longer just based on premiums and deductibles, but on UX and UI. If you can nail developing a mobile app), that makes, say, filing a claim not only not-excruciating but also engaging, then you just might have a winner on your hands.

You didn’t think you’d get all the way through a tech article this month without someone bringing up AI, did you? Perfect! Because like everything else it’s touched, AI and machine learning have made huge impacts on the insurance industry, and in more ways than one.

For, well, pretty much the entire history of insurance, underwriters have ascertained assessments by having applicants submit information that they review and assign risk values to. The trouble with that is that an applicant can lie or accidentally provide incorrect information (“human error”).

Machine learning applications pore over all kinds of obscure data points. These could be posts on social media, filings with the SEC, business reviews, anything it can get its virtual hands on. Plus, robots have a sterling zero percent history of committing insurance fraud. That’s tough to compete with.

This one probably seems like a no-brainer. Computers are better at math? Say it ain’t so! But it goes beyond being a fancy calculator. Insurance claims have to factor in multiple variables, each unique to an individual claim.

A sophisticated AI app can input each relevant data point of the specific accident, but it can also analyze historical data to look at similar events for cost estimates. Machine learning programs can review incident images and video footage as well as sensor data (a data point most commonly found in car insurance claims). This ability to access all available data points, compare them with other claims while accounting for variance in individual claims, and combine all of it into a report that can then be reviewed by insurers makes for better, more accurate, and more cost-effective claims processing.

By leveraging emerging technologies, insurance companies can both provide a better customer experience to existing customers while meeting the demand generated by new potential clients. We’re already seeing rapidly developing innovations in AI specific to insurance needs. Companies like Lemonade are deploying advanced chatbots that provide customers with faster, more comprehensive access that also eliminates paperwork from the equation. (If you’re liking the sound of a bot, by the way, then check out our chatbot best practices).

The insurance industry is learning very quickly that the future is here for insurance as much as it is for everyone else. The question now is which insurers — big or small — will move with it.

Top of mind for me? Who’s going to pull ahead of the pack with blockchain-based smart contracts.