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InProfix: Profitable Portfolio Assurance with AI and Analytics

Tanya Kolosova, Chief Analytics Officer

Digital transformation in the world of insurance has been a topic of discussion for quite some time, especially in the property and casualty (P and C) landscape. While many organization within the space have already adopted and experienced the endless benefits of using advanced technologies such as AI, machine learning, and analytics, there remain a few others who are either reluctant to go with the industrial shift or fail to implement or afford the new-age business arsenal. Due to the lack of adoption of modern technologies within these organizations, there have been records of them paying for losses in millions or even billions. One of the biggest challenges of P and C insurers are creating profitable portfolios, which is critical for their long-term stability. While consensus labeled this space as a stagnant market, one company saw an opportunity to not only help insurers successfully transform but also touch the sky of being profitable. Founded in 2016, InProfix develops artificial intelligence solutions for automation of underwriting decision-making process. “Based on proprietary analytical technologies, our solutions help insurers find the right price for the insurance application by intelligently assessing the risk of claim along with a time-to-claim prediction," says Tanya Kolosova, the Chief Analytics Officer at InProfix.

Specializing in insurance analytics, Tanya highlights that, one of the challenges insurers face is to establish the right price for the right risk. Insurance rate setting is a complex process, where it is determined by predicting two dependent trends: the frequency of claims (how many) and the severity (cost) of each claim. Traditionally, strategies to analyze claims rarely deliver on insurers’ expectations; conventional approaches to set up insurance rates are based on loss estimation, which prevents the development of competitive and highly relevant insurance products.

InProfix develops radically new approaches to address these challenges by developing artificial intelligence solutions for automation of underwriting decision-making process

Furthermore, the industry is struggling with lowered quality in underwriting processes. For years, the success of underwriting depended on the judgment, experience and most often, the “gut feeling” of underwriters. “InProfix develops radically new approaches to address these challenges by developing artificial intelligence solutions for automation of underwriting decision-making process,” asserts Tanya.

InProfix’S versatile platform takes a radically new approach to claims modeling and prediction, which is based on applying machine-learning algorithms to project time-to-claim events. It supplements and enhances the commonly used analysis of the frequency of claims (how many) and the severity (cost) of each claim. Unlike any other insurance solutions, InProfix adopts a fundamentally new methodology for collecting insurance quotes from brokers and agents and analyzing competitive prices for insurance products using their proprietary analytical methods. The firm has created an insurance shopping panel that is robust and trusted and can be used by commercial insurers to make educated business decisions. Also, the revolutionary new solution for automation of underwriting decision-making process captures the knowledge and experience of skilled underwriters and generalizes them for unseen data. Lastly, the offering’s advanced price recommendation algorithms do not use non-risk-related factors and serves as the basis for automation of underwriting decision-making process.

Over the years, InProfix has successfully revolutionized the P and C insurance vertical and has developed an expertise in the workers' compensation area. Tanya highlights that the firm is currently performing a feasibility study (proof of concept) with one of Europe’s leading financial and insurance institution. Looking ahead, InProfix aims at enhancing the features of the Insurance Analytics Platform, alongside growing the proprietary insurance shopping panel.

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Company
InProfix

Headquarters
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Management
Tanya Kolosova, Chief Analytics Officer

Description
InProfix, a stealth mode startup, develops analytical technologies that intelligently and automatically match the right risk with the right price helping insurers to create and maintain profitable portfolios. It develops a radically new approach for claims modeling and prediction and for collecting and analyzing competitive prices for insurance products. The company’s proprietary approach is based on applying machine-learning algorithms to predict time-to-claim events