Sixfold Content

With our latest product updates, we’ve extended our commercial underwriting product with a suite of AI-powered features to facilitate end-to-end underwriting across all lines of business, scaling from transactional underwriting to complex, three-dimensional risks.

Sixfold’s number one superpower is to easily–and quickly–ingest carriers’ unique underwriting guidelines and automatically surface the submissions that match the carrier’s unique risk appetite. The platform empowers carriers to streamline the underwriting process by:

🔘 Analyzing publicly available information and ingesting data from multiple disparate sources in an instant for a comprehensive risk assessment

🔘 Generating a comprehensive summarization of the business’s operations and providing NAICS/SIC classification

🔘 Surfacing positive and negative risk factors tuned to a carrier’s unique appetite

🔘 Answering complex questions across large sets of documents

🔘 Prioritizing risks with an underwriter-facing dashboard for improved resource allocation

Over the past half, we’ve significantly matured our P&C underwriting platform with deep investments across accuracy, traceability, performance, and extensibility. Some of the key highlights include:

✔️ Improved Accuracy with Advanced Document Extraction  

As underwriters ask complex questions across large sets of documents, we’ve invested in new models to improve extraction across the universe of insurance documents. With Sixfold’s latest models, we’ve seen a 40% boost in accuracy in extracting data from the most illegible documents.

With our ongoing investments in extraction models tailored to the documents underwriters see daily, Sixfold ensures precise and reliable insights from large, challenging document sets, transforming how underwriters interact with data.

✔️ Appetite Match Scoring with Weighted Risk Scoring

To replicate underwriters’ cognitive processes, Sixfold is introducing weighted risk signals to reflect the nuance across how underwriting factors impact where a risk sits within a carrier’s appetite. Now, carriers can assign varying importance to different factors to prioritize risks more accurately based on alignment with their risk appetite.

✔️ Enhanced Transparency with Inline Citations

Not only can Sixfold answer complex questionnaires across lines of business, but now all answers are grounded in the original source material with citations to the most relevant sections for confident decision-making.

✔️ Bringing Risk Classification and Summarization Down to Seconds

With our continued commitment to investing in the Sixfold pipeline architecture to improve performance, availability, and resilience, we’ve brought down the median case processing time from 80 seconds to 31 seconds. With these enhancements, in less than a minute, Sixfold can research publicly available information to learn everything we can about a business and analyze the aggregated data for business summarization and NAICS/SIC classification.

✔️ Embed Sixfold across Underwriters’ Existing Workflows with our API

With the Sixfold API, carriers can seamlessly integrate Sixfold into existing workflows for enhanced productivity and unified risk management. From automated data gathering and ingestion to custom-tailored underwriting recommendations that can be embedded across existing workflows and systems, Sixfold cuts out the manual work and document handling overhead for 10x faster risk review processes.

✔️ Mitigating drift and bias with our Responsible AI framework 

Designed to navigate the rapidly evolving AI landscape confidently, Sixfold’s Responsible AI framework ensures carriers are well-insulated from risk with its enhanced auditability, data provenance, and traceability. By actively collaborating with regulatory bodies and legal counsel, Sixfold remains at the forefront of responsible AI innovation, safeguarding carriers with unparalleled diligence.

👀 Coming Soon: Research Assistant

Stay tuned for future launch updates to hear about upcoming capabilities like Sixfold’s Research Assistant, designed to find answers to complex research questions, all of which are grounded in the original source material with citations.

Want to see our new capabilities in action?
Get in touch →‍

It’s impossible in 2024 to be an insurance carrier and not also be an AI company. In this most data-focused of sectors, the winners will be the organizations making the best use of emerging AI tech to amplify capacity and improve accuracy.

This is a challenge and opportunity that Sixfold is uniquely suited to address thanks to our decades of collective industry and technological experience. We know insurers’ needs—intimately—and understand precisely how AI can overcome them. 

In previous posts, I’ve described how Sixfold uses state-of-the-art AI to ingest data from disparate sources, surface relevant information, and generate plain-language summarizations. Our platform, in effect, provides every underwriter with a virtual team of researchers and analysts who know exactly what’s needed to render a decision. But getting there is the rub. Training AI models (these “virtual teams”) to understand what information is relevant for specific product lines is no small task, but it’s where Sixfold excels.

To use AI is human, to create your own unique AI model is divine

Underwriting guidelines aren’t typically encapsulated in a single machine-readable document. They’re more likely to exist in an unordered web of internal documents and reflected in historic underwriting decisions. Distilling a diffuse cultural understanding into an AI model can take months using a traditional approach, but with Sixfold, it can be accomplished—and accomplished well—in as little as a few days.

Sixfold’s proprietary AI captures carriers’ unique risk appetite by ingesting a wide variety of inputs (be it a multi-hundred-page PDF of guidelines, a loose assortment of spreadsheets, or even past underwriting decisions) and translating it into an AI model that knows what information aligns with a positive risk signal, a negative one, or a disqualifying factor. 

With this virtual wisdom model in place, the platform can identify and ingest relevant data from submitted documents, supplement with information from public and third-party data sources, and generate semantic summaries of factors supporting its conclusions—all adhering to the carriers’ unique underwriting approach.

Frees human underwriters to do uniquely human tasks

It can take years for a human underwriter to master underwriting guidelines and rules, but that doesn’t mean human underwriters are no longer needed–quite the opposite. By offloading the administrative bulk to AI, underwriters can use their increased capacity to prioritize cases that align with their unique risk appetite. 

Consider a P&C carrier that prefers not to underwrite businesses that work with asbestos. When an application comes in, Sixfold’s platform processes all broker-submitted documents and supplements it with relevant data ingested from public and third-party data sources. If Sixfold were to then surface information about “assistance with obtaining asbestos abatement permits” from the applicant’s company website, it would automatically mark the finding as a negative risk signal (with clear sourcing and semantic explanation) in the underwriter-facing case dashboard. With Sixfold, underwriters can rapidly discern the applications that are incompatible with their underwriting criteria and quickly focus on cases aligned with their risk appetite.

Automating these previously resource-intensive data processing workflows allows carriers to obliterate traditional limits on underwriting capacity. The question for the industry has rapidly moved from “is automation possible?” to “how quickly can we get it implemented?” Sixfold’s purpose-built platform empowers customers to leapfrog competitors relying on traditional approaches to training AI underwriting models. We get you there faster–this is our superpower.

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New York City, January 9, 2024

‍Sixfold, the Generative AI exclusively built for insurance underwriters, today announced that the company has joined Guidewire’s Insurtech Vanguards program, an initiative led by property and casualty (P&C) cloud platform provider, Guidewire (NYSE: GWRE), to help insurers learn about the newest insurtechs and how to best leverage them.

Jane Tran, Co-founder & COO at Sixfold, expressed, “Guidewire stands as the industry's foremost policy vault, embodying the definitive source of truth. Collaborating with Guidewire empowers us to advance our enterprise-grade generative AI solutions tailored specifically for underwriters.”

Insurtech Vanguards is a community of select startups and technology providers that are bringing novel solutions to the P&C industry. As part of the program, Guidewire provides strategic guidance to and advocates for the participating insurtechs, while connecting them with Guidewire’s P&C customers. 

Sixfold seamlessly handles the ingestion, routing, classification, and summarization of submissions, and provides trustworthy, data-driven policy recommendations to underwriters in a user-friendly format.

About Sixfold

Sixfold brings the power of generative AI to the underwriting process. The platform significantly reduces manual workload for underwriters and amplifies confidence in every underwriting decision with improved accuracy, transparency, and capacity.

This time last year, Sixfold was little more than a name and a vague concept. But since officially launching in May, this remarkable team (now 17-strong and growing!) has revolutionized insurance underwriting. That’s a bold statement from a biased observer, but I think I can back it up. 

First, let’s briefly explore the state of affairs coming into 2023.

Modern carriers process vast amounts of data from a wide array of sources to inform underwriting decisions. Today’s competitive advantages are secured—or lost—based on the efficiency and accuracy with which one handles this data. 

Over the years, multiple data-tech vendors have promised to help carriers keep pace, but they haven’t been even close to sufficient. Meanwhile, data ecosystems have grown more expansive and the tools gap, more glaring.

At Sixfold, we saw this challenge compounding by the day—not for lack of trying, but for lack of imagination. It’s what inspired us to develop a new approach that prioritizes transformation over iteration.

Our platform was uniquely built to accelerate the bewilderingly complex process of modeling risk appetite, no matter the starting point. Is your risk tolerance detailed in a loose assortment of PDFs? An Excel document? Or just a bundle of past submissions? We can make sense of it all. And that’s just the start. Our proprietary generative AI engine ingests applicant data from disparate sources at scale and—unlike traditional “intelligent” data processing tools, which merely extract data—generates clear summaries, fully aligned with carriers’ appetites, empowering underwriters to move with unprecedented accuracy and speed.

And it’s been effective. Ridiculously effective. Let’s run through a few quick examples:

✅ A leading general liability carrier was averaging 4 hours for its submission-to-quote cycles, but once they implemented Sixfold, that time was slashed to just 4 minutes.

✅ Last year, a large global cyber carrier measured its submission-to-quote cycles in weeks; now they do it in 3 minutes and 24 seconds.

✅ Before adding Sixfold to its tech stack, a major life & health carrier needed days to extract, surface, and package relevant data from multiple sources for a single life insurance application. Now the entire process is handled automatically in a fraction of the time.

Perhaps you can see where the industry is headed and why this is the area where Sixfold is focusing.

The journey from there to here

The progress our engineering team has made over this not-even-a-full year has been nothing short of astonishing. Gen AI is moving forward at warp speed–and Sixfold is moving even faster. 

In just the past few months we’ve transitioned from relying on a single LLM vendor to tapping and training a plethora of platforms based on their unique abilities. Additionally, we’ve tailor-built our own proprietary AI models to increase speed, accuracy, and privacy—we’ll be tripling down on our internal R&D efforts in the years ahead. (As a side note: I can’t wait to show you what our engineers have been working on…more on that during our January webinar.)

The only thing evolving faster than AI technology is society’s views of it. More people are voicing concerns about the potential negative impact of AI, particularly around issues of scaled bias. We get it. We have a shared interest in ensuring that AI is deployed with a human-first approach. 

Sixfold has been proactively and uniquely engaged in the conversation. I, and other Sixfold leaders, have repeatedly met with the state regulators and commissioners throughout the year to better understand their concerns and thinking. These meetings have helped us design our platform in anticipation of new regulations and, conversely, offer our unique insights to influence the formation of emerging rules that will allow AI to work better for everyone.

Hello, 2024

We’re exclusively obsessed with insurance underwriting. We have been from the beginning and we will continue to be in the future.

I’m beyond proud of what this team has accomplished over the past 7 months, and I can’t wait to share with you what’s in store in 2024. Join us this coming January for our first-ever virtual session, Boost Underwriting Capacity in 2024: Discover the Sixfold Impact, for a demo of how our platform enhances underwriting capacity in P&C, Life, and Specialty insurance sectors.

None of this would have been possible without the support and backing of Charles Birnbaum and Jeremy Levine at Bessemer Venture Partners, and Jonathan Crystal and Stephen McGovern at Crystal Venture Partners. We’re grateful for our bold customers and partners who understood our vision and joined us on the first leg of our journey. And of course, I can’t say enough about the Sixfold team including my co-founders Jane and Brian as well as our growing lineup of researchers, innovators, and visionaries: Brooke, Drew, Emil, Gregg, Ian, Lana, Laurence, Leonardo, Lucas, Maja, Marie, Omeed, Stewart, and Ryan.

Don’t miss our 2023 recap. See you all next year!

This post was originally published on LinkedIn.

Insurance underwriting isn’t for the weak. It’s a dizzyingly complex undertaking that requires connecting data points across disparate sources to support consequential decisions—all while meeting modern expectations for speed, accuracy, and compliance. 

The role has grown exponentially more challenging as technology has become more ubiquitous, stretching our information-rich digital trails ever longer.

Over the past two decades, various vendors have developed Intelligent Data Processing (IDP) tools to manage all this information by automating the extraction, ingestion, and structuring of data at scale. These tools have been widely adopted by carriers, but fall short of today’s mounting data challenges–in fact, they’re exasperating them.

McKinsey estimates that underwriters spend 30-to-40% of their time on rote administrative tasks “such as rekeying data or manually executing analysis.” These were the types of tasks that IDPs were supposed to automate and make more efficient—but that’s not what’s happening. In a recent Accenture survey, 64% of underwriters reported that today’s tech either makes no difference or increases their workload. 

Automated data extraction was, until recently, the only way to tame the information deluge. New technologies have paved the way for a better, more seamless approach. Emerging LLM-powered AI represents a new paradigm that eliminates extraction chokepoints, reduces the burden on overtaxed underwriters, and accelerates decisioning.

Generative AI in insurance changes everything

Traditional IDPs were designed to exhaustively extract every piece of data–no matter how irrelevant or repetitive—so that it can be structured into a centralized database and passed along to overloaded human underwriters to query and scrutinize. The more complex and document-laden a process (e.g., loss run reports with intricate hierarchical ordering of nested sets), the more odious the inefficiencies and the more work tossed onto underwriters’ plates.

Insurance solutions touting the “most efficient” or “fastest” data extraction are about as meaningful in 2023 as boasting the “highest print-quality” fax machine. Comprehensive extraction is a relic of a fading technological paradigm. The industry is rightly turning to next-gen AI technologies to free underwriters from repetitive data work (which is better handled by machines anyway) so they can focus on building value and closing deals. 

Sixfold uses state-of-the-art LLMs to synthesize information across multiple sources and generate summaries in plain language for underwriter review. No processing power is misspent on redundant extraction; underwriters’ valuable time is no longer wasted sorting through virtual buckets of well-structured (but context-free) data. 

When processing a life insurance application, traditional IDPs will, for example, extract each mention of the applicant having diabetes, even if it appears across dozens of documents. Unlike AI-powered platforms, IDPs are incapable of discerning meaning from data—underwriters are still required to connect the dots. Sixfold skips the needless chronicling of data points and independently generates clear summations of relevant throughlines (e.g., “The applicant was diagnosed with type 2 diabetes 12 years ago and it’s being properly managed with insulin and diet”), thus freeing underwriters to forgo the data work and render decisions faster.

Sixfold brings the power of advanced AI to insurance underwriting

In effect, Sixfold provides underwriters with a virtual army of researchers, data processors, and writers who know precisely what information is needed to render decisions quickly (and just as importantly, what isn’t). 

It’s already having a huge impact. With Sixfold, companies are accelerating submission-to-quote cycles by as much as 43%, clearing backlogged queues, and massively increasing GWP per underwriter. 

Even better? It’s far easier to get up and running with Sixfold than a traditional IDP. These older systems required huge investments in time and resources to train their ML models on an organization’s unique needs. Sixfold, on the other hand, can be easily—and quickly—configured to match the appetite and needs of specific carriers and programs. It’s more-or-less ready to go out-of-the-box (or out of the virtual SaaS box).

AI is reshaping insurance before our eyes

The marketplace is littered with the remnants of corporate behemoths that misread the technological tea leaves—and in today’s world, giants fall fast. Consider how, in just one decade, Yahoo slid from the world’s most popular website to near-irrelevance. Or how Kodak only took eight years to complete its journey from top-five global brand to ejection from the Dow Jones. Or how, in a mere six years, Blockbuster leaped from its 9,000-plus-location peak into bankruptcy. 

The takeaway: Past performance will not save you. New technological paradigms can seemingly come out of nowhere to reward leaders who had an eye on the future—and expose those who didn’t.

I’m confident that this year will be remembered as an inflection point for generative AI. The way insurance is handled moving forward will be a radical departure from the past. There’s now a clear industry-wide divide between those pursuing iteration and those seeking transformation. Which side do you want to be on?