“Think of us as providing the ability to insurers to understand their risk – the risk of their portfolio and their insurance in a completely different way, which is in real time and provides the real picture,” DalleMule said. “We will find the truth about small and medium businesses…”
Planck has raised roughly $71 million in venture capital since its founding six years ago. Investors include Nationwide Insurance, Team8, Greenfield, Arbor Ventures, Viola, 3L Capital and HDI. The company expects to announce new financing information soon, it said. Planck’s customers in the US, Europe and Japan include Attune, Chubb, Republic Indemnity (Great American Insurance Group) and Sompo. Beyond a large number of commercial insurance carriers, MGAs and some brokers round out the customer base.
Nearly 100 people work for Planck, which maintains headquarters in Tel Aviv and New York. Hiring is expected to continue through 2022, DalleMule said.
Not enough good data
Planck’s focus is on addressing what DalleMule terms as a shortage of quality data for the underwriting process.
“One of the problems that exists … is the lack of good quality data to underwrite into price balances, because the traditional methods involve typically asking a series of questions from agents … directly to business owners about their operations,” DalleMule said.
Those answers often have lower accuracy rates, and the process is very manual with dozens of questions, he noted.
“We not only automate that process, but we also provide higher accuracy, and we answer a high number of questions because the machine does it,” DalleMule said. “Instead of relying on one source, we use AI to really tap into the open web and everything that is out there about that entity that the insurer is trying to” underwrite.
Planck’s platform, by tapping into that open web data source, accesses business and governmental websites and social media. It processes the data to come up with answers to underwriting questions that help to better analyze the risk at hand.
The company’s technology tools that help make this happen include its proprietary web crawlers, which help collect as many rough data points as possible. Another key piece of technology involves using algorithms to help interpret raw data, such as pictures or licenses, and convert it into something more usable for the underwriter. AI is the third major piece of technology, specifically machine learning, which helps make sense of all the data and develop usable answers.
Customers who want to integrate with Planck’s platform can choose to have a digital portal that makes calls, and, thanks to API connections, gains answers to underwriting questions. They can also use a web application interface where they just log in to use the system and enter a business name and address to obtain underwriting data as needed.
For a more formal integration via a digital portal, the first step is for Planck to determine where in a client’s system the integration will take place, such as with a policy administration system or an internal system.
According to DalleMule, Planck’s APIs make an integration very simple in a process that typically takes a few weeks. Also part of the equation: “A little bit of IT time” and some training.
Planck does not charge clients based on how many calls they make to the platform, something DalleMule referred to as a “by the drink” approach. Rather, clients pay Planck based on a percentage of their premium that passes through the platform.
“We’re doing this because we make money when customers make money,” DalleMule said “They make money when they write policies, and if they write good policies even better, so we are going to get a small percentage of that as a fee.”
In other words, Planck links its growth with its clients.
“We will grow if they grow and we are completely aligned with them,” DalleMule said. “That’s a very different approach but it has worked really well so far.”