Planck Resolution: Disrupting Commercial Insurance Underwriting

Insurance companies are one of the pioneers in advanced analytics, but most organizations have faced major impediments while trying to extract value from data. This was primarily due to the rapid growth of many carriers through mergers and acquisitions without paying proper attention to integrating front- and back-end systems while standardizing data. As a sign of better things to come, new fintech players such as Planck Resolution have “cracked the code” and have demonstrated real, scalable results in commercial insurance, integrating AI to legacy systems and delivering measurable value quickly. “We approached this issue, by avoiding long integrations on the customer side, and allowing them to use a simple API, while any required configuration is done on our end,” says Elad Tsur, CEO & Co-Founder at Planck Resolution.

For commercial insurers who want to reduce their loss ratios, increase conversion rates, grow sales, while reducing operational costs, the company has developed a disruptive platform that helps them achieve these results without changing their underwriting model and fields. The AI-based platform generates real-time, automated underwriting insights for commercial insurers with an accuracy and coverage of more than 90 percent. “The combination of rich, granular, up-to-date, data in the open web with AI and machine learning capabilities enables insurers to change the game,” adds Tsur. The platform enables clients to pre-fill and eliminate questions from questionnaires, to streamline the underwriting process while reducing loss ratio. Their clients can also leverage the platform to explore, collect, and analyze new data fields quickly and at a marginal cost, to generate smarter insight and better pricing. Clients can test the platform’s coverage and accuracy by running a quick POC, without any integration to see the value before writing a single line of code on the client’s end.

“To provide the carriers with up-to-date and highly accurate real-time data insights about any business, the platform runs a 3-phase process,” says Tsur. The platform first collects the data from thousands of resources. It then extracts the relevant information from the collected data through AI capabilities such as computer vision, NLP, semantic analysis of unstructured data and more.