Say The Quiet Part Out Loud: InsurTech Isn't Keeping Up With Insurance
Say The Quiet Part Out Loud: InsurTech “AI” Isn’t Keeping Up With Insurance

Say The Quiet Part Out Loud: InsurTech Isn't Keeping Up With Insurance

The past decade saw more than its fair share of insurtech solutions promising to harness the power of “AI.” Many of these tools use hard-to-train algorithms powered by technologies that are years—if not decades—old. These legacy underwriting tools may inject some process efficiencies but don’t address the fact that insurers are struggling more than ever to expand capacity and grow Gross Written Premiums (GWPs) per underwriter.?

A recent Accenture survey found that underwriters spend 40% of their time on administrative tasks—that’s a full two days of their work week. Inboxes are flooded with more submissions than ever, but by some estimates, underwriters are only able to respond to 10%.?

These aren’t challenges that companies can simply spend their way around; they require a fundamentally new approach. At Sixfold, we believe ascendent technologies, like LLM-powered generative AI, will lead the way. By moving beyond legacy solutions, carriers can take on today’s most pressing underwriting challenges–and the challenges on the horizon.

Ingesting and synthesizing data from disparate sources at scale

In the connected-everything world, insurers have access to more data than ever. This is a blessing and a challenge. On one hand, it guides decisioning and improves outcomes. On the other hand, there’s so much data from so many disparate sources, that it’s impossible to process efficiently.

Underwriters often find themselves sorting through hundreds of pages of documents for a single application. This limits capacity and squeezes GWP per underwriter. The only way to overcome these chokepoints without massively expanding headcount (and dinging already precarious expense ratios) is by using sophisticated AI tools to automate complex business tasks at scale.??

With Sixfold’s state-of-the-art underwriting AI, insurers can seamlessly integrate structured and unstructured data from multiple disparate sources. The platform reflects each company's unique risk appetite, so it automatically surfaces relevant information to accelerate UW decisioning.

Say it in plain language

Sixfold uses LLM-powered generative AI (the same tech behind ChatGPT, Bard, etc.) to summarize findings to underwriters in plain language, not spreadsheets.?

The platform, in effect, gives every underwriter their own virtual research team to build detailed reports on every application. Sixfold even generates coverage recommendations based on the company’s UW format. Compare this to legacy AI tools, which merely repackage information into number-heavy spreadsheets and dashboards, inevitably requiring additional inspection and contextualization from underwriters.

Even better? Plain language summations expand the underwriting talent pool by de-emphasizing technical and computational skillsets that are better handled by machines anyway. This is a crucial break from legacy tools, as insurers are now forced to compete for limited underwriting talent against private-equity-backed firms, insurtechs, MGAs, and other nontraditional insurance companies.?

Opacity in insurance is no longer an option

Sixfold was designed with transparency at its core because that’s what today’s customers expect and increasingly what regulators demand. The platform provides full sourcing and lineage of all underwriting decisions with clear semantic summaries, i.e. no more “black boxes.”

The platform provides clear reasoning for its conclusions on why a case is qualified, or, as in the case above, disqualified.

Continue reading on the Sixfold website ->

Andrew Khalatov

Executive Director @ Unqork | Value Creation | Private Equity / VC Portfolio Operations | Ex- Oliver Wyman, Ex- Accenture

1 年

Excellent article and even better Simpsons reference. Great job Alex!

Expanding the underwriting talent pool through plain language summation is an excellent example of what some studies have been finding lately. The least experienced people will benefit the most from working hand in hand with AI tools. ??

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