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