Deep Vector, an AI platform for analyzing underwriting documents, closed its seed round of $1.5M, co-led by Aperture Venture Capital and InsurTech NY.
Deep Vector helps insurers and brokers translate the influx of analog documents used for underwriting risk—claims loss runs, Acord forms, motor vehicle records, and business records—into usable and actionable data. Previously known as Loss Scan, Deep Vector uses a proprietary algorithm and machine learning to classify documents from a library of 5,600+ formats specific to each insurance carrier’s forms. Once identified, Deep Vector processes and translates the documents into usable data for carriers, brokers, and risk managers.
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“Insurers have little incentive to make their loss run and claims analysis process easier because it is simply a cost center,” said David Gritz, Managing Director at InsurTech NY. “Deep Vector bridges the gap between the insurance broker and underwriter for complex commercial accounts and saves thousands of hours analyzing accounts.”
Deep Vector seeks to become the default translation layer for insurance data extraction. Over 30 of the top 100 insurance brokerages and many more carriers, underwriters, MGAs, and brokers have already transformed their operations with Loss Scan. The rapid adoption by industry leaders shows that Deep Vector isn’t just innovative – it’s delivering real results for the most demanding organizations in insurance.
“We are excited about the growth prospects for Deep Vector,” said Garnet Heraman, General Partner at Aperture VC. “The insurance industry is the largest data repository for business. Deep Vector unlocks that data for better risk modeling, resource management, and ultimately better customer experiences.”
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Founders Scott Knowles and Wesley Janse van Rensburg understand the market. Knowles started his career as a commercial insurance broker, and most recently, the team sold their insurance analytics business, Modgic, to Zywave.
“Deep Vector’s product Loss Scan breaks down the barriers that have locked away valuable claims data for decades. By automating the extraction of information from complex loss runs, we’re giving insurance professionals access to previously buried insights in PDFs and spreadsheets. It’s not just about saving time – it’s about unlocking data that transforms how underwriters assess risk and brokers serve their clients.” said Scott Knowles, co-founder of Deep Vector. “Only with the power of Deep Vector can brokers shift their time to true risk management and advisory instead of paperwork processing. By automating the tedious task of manual data extraction, we’re liberating insurance professionals to focus on what matters – analyzing risks and providing strategic guidance to their clients.”
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Source – PR Newswire
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