Why we invested in Artificial. There is great innovation in insurance… | Tom Dines | Exceeding mass | October, 2022 | So Good News

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Earlier this year we led Articial’s £9.5m Series A round. This was interesting for us as we have been watching the company for some time and waiting for the right time to invest.

Insurance is a space with huge innovation potential, but the industry’s willingness to adopt new technologies has lagged behind the broader fintech sector. This is changing now.

Why is that? We’ll get to that, but first we need to set the scene.

What is specialist insurance?

The $880 billion global specialty insurance market covers a wide range of commercial risks, from property damage to highly complex liabilities arising from events such as the Evergreen tanker grounding in the Suez Canal.

A major financial disadvantage of these insurance contracts is that they require that these risks be shared between several insurers, which is why the Lloyd’s and London market is called the “subscription market”. Traditionally, this was done by a broker who physically walked the London market to negotiate and obtain agreements from underwriter to underwriter to place the risks.

This paradoxical situation of insurers competing with each other at the company level but cooperating on the risks they underwrite is very difficult to regulate. Each insurer has different management systems and therefore data in different formats. This will do Data exchange and integration between parties’ systems is very difficult. It is for this reason that processes in the specialized insurance market are carried out manually.

Legacy IT systems, unstructured data, and the inability to share this data make custom insurance contracts inefficient and expensive to deploy. In some cases, five separate intermediaries sit between the party seeking the policy and the insurer writing the risk. Each intermediary takes a cut, so the insurer receives only 58% of the premium paid by the insured. This is where Artificial appears.

Since 2013, Artificial has developed solutions for the insurance industry that make these processes more efficient. When combined, these component solutions become an artificial platform: technology that enables insurers to automate the underwriting process through smart data ingestion and algorithmic underwriting.

Three artificial points of difference:

  1. Artificially developed proprietary programming language for insurance all artificial products are based on it. Since the language is designed for insurance products, there is no need to explain to the computer what commission, insurance and limit are. This makes the process of acquiring, structuring and enriching data and making decisions very fast and easily configurable to the needs of clients.
  2. Artificial is an API-first company, meaning their products easily integrated with the core systems of brokers and insurers sharing structured, quantitative data. This allows Artificial to be the glue that holds insurance companies’ legacy systems together, rather than just another legacy system in the ecosystem. This is an important competitive advantage to which we will return.
  3. An artificial algorithmic underwriting platform is possible automatic acceptance, referral or waiver of risks based on the underwriting appetite encoded in the platform. A platform’s rules or appetite can be simple or very complex and can be easily changed, offering a transparent audit trail. Once a decision to accept, refer or reject has been reached, it can integration with clients’ pricing models underwriting risk.

The technology allows insurers to cut processing costs by 90%, while reducing the time it takes for underwriters to make an application decision from days to seconds.

As mentioned above, if the industry has been underperforming for years, why is now the right time for a Series A?

Innovations in the market have forced the insurance industry to rethink how it does business.

The industry is looking for solutions.

The success of an algorithmic underwriting platform called Ki has awakened the specialty insurance market to the potential of algorithmic underwriting for insurers.

Launched in 2021, Key handled £400m of GWP in its first year and led to a lower overall cost ratio for its owning insurer Brit. Insurers are now looking at Key’s progress and will all be working through algorithmic underwriting buy or build analysis. However, doing this successfully in-house is only possible with a very high investment of time, money and expertise with no guarantee of results. This is where Artificial appears.

With Ki proving the algorithmic concept due to the unsustainably high cost of doing business in the specialist insurance market, demand for Artificial’s technology grew, driving the company’s ARR above £1m. But this is only the beginning. Almost all sales inquiries come in now and have the advantage of being able to choose Artificial Strategic Partnerships.

The artificial results speak for themselves, so it should come as no surprise that we got a big impression from the team. It was created by David King and Johnny Bridges. Our contacts in the insurance industry have told us repeatedly that these two are a team to watch. Everyone we’ve worked with since has supported that.

The Artificial team combines the technological skills needed to fundamentally improve the insurance sector with the industry knowledge needed to bring the big players on board.

The recent investment has allowed the team to add a number of features that will allow it to grow over the coming months and years. It has already made several hires in product engineering and business development, with more to come.

We are very excited to be able to invest as the company’s proposition begins to take shape. We have Alma Mundi and MS&AD Ventures as well as #9 and others. We have invested together with insurtech specialists.

Artificial intelligence embodies many of the things we want to see in startups: innovation in old industries, leveraging technology to radically improve processes, and top-notch founders who understand how businesses can do better. If this sounds like your startup, contact us here.

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