The Coronavirus 2019 (COVID-19) pandemic is disrupting our business and personal lives in ways we’ve never before experienced—and the situation is evolving rapidly. As I write this, the number of confirmed cases in the US is in the tens of thousands, and more than 13,000 lives have been lost around the world according to MarketWatch. A growing number of states, including DataCubes’ home state of Illinois, have issued lockdown orders for all but essential workers, and experts say a nationwide lockdown may soon be necessary as reported by Foreign Policy.
As the digital revolution continues to move forward, it brings about exciting opportunities for commercial P&C insurers. Facing disruptive change on many fronts, smart carriers are accelerating their technology adoption. Many are either developing their own innovative technologies or they are partnering with insuretch companies to deploy state-of-the-art solutions aimed at improving their ability to increase operational efficiencies, cope with nontraditional competitors and explore new business models, among many other things.
Determining a business’s risk profile is the heart of commercial P&C underwriting, but the research that goes into it is often tedious, time-consuming and error-prone. Underwriters may conduct dozens of web searches and direct numerous follow-up questions to the submitting agent as they work to build a comprehensive picture of the applicant company, its risks and its potential profitability as an insurance customer.
In insurtech as in other fields, implementations are often complex. It’s not unusual for problems to arise before a new solution is fully deployed, integrated with external technologies, and delivering robust business value.
DataCubes is in the midst of rapid growth, not only in the number of employees and customers but also in the maturity of our organization. One sign of the increasing maturity is the value placed in the creation of an established People Development function. I joined DataCubes two months ago as our first-ever Director of HR, with a mission to help manage and optimize our ongoing growth.
Optical character recognition (OCR) is a decades-old technology that converts scanned images to text, and it has played an important role across many industries throughout the years. But when it comes to digitizing applications for commercial insurance underwriting, OCR is just the first step of the innovative process. Having worked extensively with the improvement of the insurance application process, I would like to give some thoughts on ways to improve underwriting productivity. Artificial Intelligence (AI), and specifically machine learning, can take the intake process well beyond OCR, making it possible to capture data accurately from scanned documents, derive meaning from that data, and apply it in ways that make the underwriter’s job easier and more profitable.
Last week’s blog took a look back at DataCubes’ 2019 highlights. In this blog, I’d like to focus on where the industry stands today and what’s ahead for insurtech and AI in 2020.
2019 was a pivotal year at DataCubes—one that saw our partners make great progress in transforming their underwriting businesses. The year also saw DataCubes continue our exponential growth while taking important steps to create further success in 2020.
Profitably underwriting commercial auto is a critical problem area for most insurers. The National Association of Insurance Commissioners reports that commercial auto losses have risen for the past four years, despite rate increases every quarter since 2011. Commercial auto rates rose an estimated 6 to 12 percent in 2019, according to the risk management firm Willis Towers Watson.
DataCubes’ rapid growth shows there’s a real hunger for insurtech solutions that use sophisticated analytics to streamline and automate commercial underwriting. But breakthroughs in this field don’t come only from innovative startups like DataCubes. Academic institutions play an important role in the insurtech ecosystem. They introduce the next generation of insurance and insurtech leaders to recent machine learning methods and technologies, and expose them to current industry issues. They research and report on novel approaches to solving complex industry problems. They foster interdisciplinary collaboration.