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By Taming Large Knowledge with AI, Cytora Goals to Rework Industrial Underwriting – jj

By Taming Large Knowledge with AI, Cytora Goals to Rework Industrial Underwriting


Since its launch in 2014, Cytora has raised close to $39 million and built an AI-powered platform that tames and translates big data for underwriters with risks in Europe and Australia. In addition, plans are underway to expand into new geographies by the end of 2019.

Richard Hartley

Cytora’s platform “gives insurance companies a more accurate view of the underlying risk and helps them make, ultimately, better risk selection and pricing decisions,” said Richard Hartley, CEO and co-founder of London-based Cytora, in an interview with Carrier Management.

“If you do that well as an insurance company, you can set the right prices to cover the claims. On the other hand, if you do it badly, your combined operating ratios could suffer.”

Insurance companies want to underwrite more profitably, but their margins are being squeezed, he explained. “They want to find ways to improve their combined operating ratios by three or four percentage points.” While it is hard to affect broker acquisition costs, the areas they can actually shift in a meaningful way are their front-line underwriting expenses and their loss ratios, which is where Cytora can help, Hartley said.

Granular Data

The Cytora platform is powered by an AI risk engine designed to help insurance companies take frictional cost out of their underwriting process, he said. “It helps them underwrite more efficiently, in a more cost-effective way, which improves their expense ratios. It also helps them underwrite more accurately, which helps them improve their loss ratio by differentiating the risk in a more granular way.”

At the same time, Cytora can help improve the experience for customers who want to buy insurance in a faster and easier way, with greater transparency, he affirmed.

So, how does Cytora’s AI-powered platform work for underwriting?

Insurers use Cytora’s APIs, or application program interfaces, to add capabilities—like submission verification and prioritization—to their underwriting workflow. For example, when a property or casualty submission comes in, Cytora’s Verify API corrects and enriches the information in the submission using external data that describes the risk in more detail—data that the underwriter would like to have but often isn’t provided by the broker. Indeed, the insured may not even have such granular information. (See related sidebar about APIs).

This data would include construction information, weather information, information on the company and its financials, Hartley said.

“We build a more accurate view of the risk and then provide a score to the underwriter from an A-grade risk to an F-grade risk,” he said, noting that an F-grade risk would have a very high claims cost.

“So, it gives them more view of the risk and helps them make a better and faster decision,” he continued.

Discussing the merits of using AI data in the small and medium-sized enterprises (SME) space, Hartley said the Cytora platform enables insurers to completely automate the underwriting process from end to end with no manual underwriting input needed, which helps insurers make money in a sector where the risk premium is low.

He pointed to the example of small businesses with five employees with a risk premium of perhaps $2,000. “Ultimately with that kind of business you want to be using artificial intelligence to make the underwriting decision, not a human,” he continued. “It’s way too inefficient to underwrite that type of business on a manual basis. It’s too expensive, and it doesn’t allow the insurance company to be profitable on that particular size of risk.”

Hartley recalled an insurance executive who told him: “Every time one of our underwriters picks up the phone to speak to a broker, we’ve already lost money on the risk because it takes too long. It takes three to four days to make a decision. So, it’s just too costly to use a manual underwriting approach for smaller risks.”

The Cytora tool also can be applied for mid-market commercial business “where it helps underwriters make faster and more accurate risk selection decisions, which are aligned with their appetite and risk profile,” he noted. (Cytora is initially focusing on customers with SME and mid-market commercial business.)

Will such AI data tools make underwriters obsolete?

Hartley emphasized that in the mid-market and large commercial space, with complex risks, humans will continue to be needed to make judgment calls on the risks.

P/C Data Universe

Where does the Cytora AI tool gather the information from?

Cytora’s risk engine captures the digital footprint of a business by ingesting and analyzing data from multiple sources, including company websites, news articles and government datasets.

“We’re constantly gathering more information about each company and property, which means when a broker gives a submission to an underwriter, we have huge amounts of information that can be quickly used to help an underwriter make a selection faster,” Hartley affirmed.

While property risks include data about construction and location, Hartley said casualty underwriting focuses more on the company, collecting data points on its financial state, earnings and share volatility, corporate governance, attitude toward risk, and the quality of its management and directors.

(See related sidebar: InsurTech Enables Insurers to Become Tech Companies)

“A well-run company is going to have a good property loss ratio and a good liability loss ratio, because generally speaking they’ll be making the right choices in relation to risk and return,” he emphasized.

“The more data we gather on companies and property, the better view we’ll get of the business as a whole,” he said. “That’s why we’re beginning to see correlations between different perils. Relatively speaking, a company that has low property losses will also have low liability losses, because the management team’s attitude to risk will be the main decisive factor in how that company performs.”

Ultimately, insurers will be able to reward companies that are well run with a lower premium, he said. “That’s a big part of what we’re trying to do.”

Flexible Solution

Hartley said Cytora aims to provide a flexible solution by “providing the building blocks for insurance companies to build their best underwriting workflows and processes.”

For example, some Cytora customers are trying to improve the way they prioritize submissions to make sure they are focusing the greatest amount of their time on the most attractive submissions. Other companies want to automate their entire underwriting processes because they want to be able to offer lower-priced coverage.

“We have another customer who says, ‘We’re trying to compete on how we select risk. We want to focus on selecting risk in a more granular way than our competitors,” he continued.

“We’re providing an underwriting platform that helps insurers build the best possible underwriting process, powered by all the data points that we hold.”

Cytora provides customers with diversified solutions by using its flexible API platform, so insurance companies can build and configure their own underwriting workflows to meet their unique business requirements. This enables them to compete using their own underwriting criteria.

Hartley explained that an insurance company may want to build a quotation platform on its website that allows direct insurance purchasing. Such a platform can be built using Cytora’s APIs.

“Or a company may want to display our risk scores in an underwriting workflow tool. They can again use our API for that. The important point is that it gives them the flexibility to use the Cytora underwriting platform how they like, based on their particular business objectives.”

Another Cytora customer has built an entire quotation platform, which allows a small business owner to get a direct quote. By using Cytora’s platform, the customer was able “to build something entirely new from scratch.”

Data Liquidity

Hartley said the Cytora platform also provides “data liquidity” for commercial insurers, which enables underwriters to enter new lines where they have zero underwriting experience.

He explained that insurance companies are generally pretty rigid in what they do, specializing in particular lines of business or sectors. One insurer may understand how to underwrite for restaurants but have difficulty expanding into other lines, such as directors and officers insurance, because it is costly to build up the underwriting team.

However, with the “data liquidity” provided by Cytora, insurers can move more easily into new lines of business and new sectors based on the data advantage they can get from Cytora’s AI platform. “It should mean that they can grow faster and more cost-effectively into new areas,” he noted.

The tool removes some of the risk of entering new lines of business, which increases the liquidity in insurance and benefits the end customers because they get more choice, Hartley went on to say.

“We have, for example, customers who have gone into SME risks for the first time in a completely automated way, where they don’t have a team in place,” he said. “We help them underwrite the risk when they don’t have any experience. By working with us, they can make that shift a lot faster and at a lot lower cost, which benefits the customer at the end of the day because they get a bit more choice.”

While underwriting teams are still needed for larger, more complicated risks, the data tool helps teams better understand new lines they might want to enter, he said.

Improving the Customer Experience

Cytora also is aiming to improve the customer experience. For example, Hartley said Cytora supports an insurer that offers SMEs a direct U.K. commercial combined (property and casualty) policy. Customers only have to provide their company’s name and address as well as the number of employees. Other underwriters might want the company’s name and address along with its revenues.

“It’s helping small businesses buy insurance quickly and easily; they can get a quote in under a minute and buy insurance in a couple of minutes,” compared to many online portals that currently require 30-40 questions to be answered and 20 or more minutes of time.

“That’s immensely frustrating for business owners, to spend that amount of time and to give that amount of information just to get a quote for a $1,000 policy.”

What’s Ahead for Cytora?

Hartley has big ambitions, which makes it an exciting time for Cytora. “We’re trying to accelerate the transformation of the industry. We’re building out our products to power the point of the underwriting workflow from end to end. And then we want to build out the coverage, so by applying it, insurers can streamline their businesses…”

In April 2019, Cytora raised $32 million to accelerate expansion of the company’s product suite as well as its entry into new geographies, he said.

There is a lot of big data available, but sometimes it takes an insurtech startup to find ways to tame it to help improve risk selection and industry efficiencies.

This article first appeared in the July/August edition of Insurance Journal’s sister publication, Carrier Management. The magazine’s print edition was published in June 2019.


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