The insurance industry is facing the challenges of disruption caused by the technological advancements in artificial intelligence (AI) and machine learning (ML). Insurance carriers are now able to know more about their customers than ever before. They can use data mining with AI and ML to develop compelling product offerings. Customers may enjoy a more personalized experience that has faster and more accurate claims processing capabilities resulting in vastly improved customer service.
Is your organization prepared to benefit from this technological trend that will ultimately determine its competitive advantage and, therefore, lead to a greater market share? Or, will your company be left behind as these disruptive technologies are embraced by your competition?
The salient points from the debates held during the Sixth Annual Insurance Nexus AI and Analytics USA Summit in 2019 have been compiled into a whitepaper, giving you the opportunity to learn more on this business-critical area. One hot topic that was up for debate was the need to effectively manage a rapidly-changing insurance business, while at the same time maintaining corporate integrity. Innovations in AI and ML fundamentally challenge this process.
Three industry experts weighed in with their thoughts about how innovations in AI and ML are being applied to the insurance sector. These innovations will disrupt the industry with a major transformation of insurance carriers’ operations in the near term and over the next decades. The experts included: 1) Glenn Fung, Chief Research Scientist, AI & Machine Learning Research Director, American Family Insurance; 2) Lee Ng, Vice President for Innovation, Travelers, and; 3) Ted Stucky, Managing Director, QBE Ventures.
Calling on external experts to come in, to help an organization, is a way to more rapidly benefit from the necessary advanced skills that would take considerable time to acquire internally. Nevertheless, maintaining proprietary insurance expertise provides a critical portion of an insurance carrier’s competency and competitive advantage.
Glenn Fung, Chief Research Scientist, AI & Machine Learning Research Director, American Family Insurance, explains “A lot of the focus on getting transformation [happening] was leaning to people outside [the company] to integrate venture capital and innovation, AI and ML. My team was 95% of external people. But, as a whole, in terms of digital transformation, we value internal expertise”.
The best-case scenarios for the rapid deployment of innovative AI systems combine significant external support with internal expertise. Insurance carriers need to embrace the sector changes and AI innovations because this will be the determining factor in competitive success going forward. At the same time, there is the recognition of the overwhelming influence of legacy systems and the natural resistance to trying anything new in ways that were never done before.
It is important to make the distinction between risks and uncertainty. Risks which are known, produce a specific unwanted outcome. Strategic planning may mitigate some of these risks. Risks, which are unknown, are more accurately described as uncertainty. With uncertainty, the outcome is not possible to determine. Lee Ng, Vice President for Innovation at Travelers, says: “No amount of thinking and research is going to eliminate that uncertainty”.
Traditionally, important decisions are made by understanding the data and then analyzing it, in light of the macro trends. For known risks, fact-based decision-making may be sufficient as long as the risk is truly known. With the uncertainty that comes from innovation, relying on a fact-based decision-making process is not sufficient.
This is like tying a rowboat to a dock, getting in the boat, and then rowing like crazy. The boat is safe, the risks are known; however, you will not go anywhere. Innovation is embracing the uncertainty of rowing out to sea, not knowing exactly what will happen. Lee Ng says “When you’re dealing with uncertainty, don’t overdo it on analysis”.
One of the greatest challenges is to make adjustments as part of an ongoing process. In some cases, these adjustments may be counter-intuitive. AI processes may uncover new patterns, which are not expected. Innovation is not linear. It does not follow a neatly organized step-by-step plan. A business-critical approach does not allow for unexpected discoveries and discovery is what AI and ML are all about.
Insurance carriers should consider business development with three perspectives, these include; taking care of the fundamental operational needs, enhancing return on investment (ROI) by exploiting ROI-driven initiatives, and the overall impacts of disruption.
Carriers’ operations are improving because the systems are getting better and more efficient. This does not mean that every technology innovation and implementation will be perfect. In fact, demand is driving things to rapidly come to market leaving insufficient time to hold back new systems deployment until everything is perfect. Software development that used to take months, or even years, now benefits from cloud service offerings that allow the deployment of some innovations within weeks.
Ted Stucky, Managing Director, QBE Ventures, QBE, tells how one of his projects was to upgrade medical form information capture that used optical character recognition (OCR) with an AI system to increase claims processing speed. Stucky says, “We wanted to see how quickly we could get it to market. From the initial conversation to the time that it was operationally deployed, it was seven weeks”.
As long as the systems are integrated properly, the technological elements are not at issue. The problems come from the people involved in the business use and their resistance or enthusiasm for using the technology. An important factor to understand is how people will actually engage with the technology, as engagement is critical to have a successful outcome.
Carriers will likely face new challenges, and competition, from sources that they had never considered before. This is already happening through the integration of global financial systems and the bundling of insurance products and service offerings with other financial products. To keep up with all of these trends requires significant agility.
This white paper, Agility Is The Key To Successful AI-Powered Innovation In Insurance, was created in conjunction with the upcoming Insurance Nexus Reuters Events™ conference, Insurance AI and Innovative Tech USA 2020, taking place May 12-13, 2020, at the Radisson Blu Aqua Hotel, Chicago, USA.
Expecting the attendance of over 500 senior analytics executives and insurance industry business leaders, the conference will feature the latest trends in AI-driven technological innovation. Over 60 expert speakers, who are pioneers in AI and innovators in insurance, will share insights about AI and cutting-edge analytics. Attendees will have the opportunity to participate in more than 25 hours of rigorous debates, discussions, and learn from presentations of more than 45 real-world case studies.
For more information, please visit the website: https://events.insurancenexus.com/analyticsusa/