Four Key Takeaways from Saul Ewing Arnstein & Lehr’s Seminar on InsurTech Fundamentals and Compliance Strategies for Implementation
Demands from millennials, who now represent the largest living generation, combined with a variety of technology advancements—such as Big Data, blockchain and artificial intelligence—are driving innovation across all stages of the insurance lifecycle, collectively referred to as "InsurTech." Saul Ewing Arnstein & Lehr's seminar on InsurTech Fundamentals and Compliance Strategies for Implementation that was recently held in Philadelphia explored these themes. Industry professionals participated both in person and via live-stream from across the U.S. Below are four key takeaways from the event:
- InsurTech addresses consumer demands by changing the insurance distribution model, but existing insurance laws and regulations continue to be an obstacle. Purchasers expect online applications, 24-hour access to account information through multiple channels, and quick turnaround on underwriting and claims decisions. More than 1,500 InsurTech startup companies are responding to these modern consumer demands by developing digital distribution models, such as Slice (Slice's chief underwriter officer was an event speaker) and Goji. Traditional insurance companies are seizing opportunities presented by InsurTech, including reaching new clients, creating a better customer experience, improving risk selection, reducing expenses and operating more efficiently. However, there are significant regulatory hurdles for InsurTech startups and established insurers who have partnerships with InsurTech startups relating to licensing, compensation for non-licensees, and cross-border issues. The NAIC has responded to the challenge of regulating InsurTech by forming the Innovation & Technology Task Force. Trade groups, such as the American Insurance Association, are also seeking to find ways to facilitate innovation through a proposed model law, the Insurance Innovation Regulatory Variance or Waiver Act. This Act would facilitate the creation of regulatory "sandboxes," which would permit InsurTech startups to operate in a monitored setting, with select laws temporarily relaxed to enable some companies to work out problems before they go to market.
- Blockchain has the potential to drastically increase efficiency for the insurance industry. Blockchain technology is defined as decentralized databases that serve as a digital ledger system for recording business transactions and events. Three key features of blockchain are: (1) data entered onto the blockchain is ubiquitous and instantaneous so everyone has access to the same data at the same time; (2) information on the blockchain is more easily verifiable because it cannot be deleted or altered; and (3) smart contracts can be added to automate functions. Blockchain presents a myriad of opportunities for insurers to increase efficiencies, such as by improving back-office operations, automating rule-based claims processing and improving transparency in compliance. According to one event speaker, there are now 20 to 30 "flavors" of blockchain that are constantly evolving and improving. He predicts that one version will likely emerge as the predominant structure. Keeping up with this evolving technology will likely be critical for insurers.
- Big Data offers insurers the ability to more effectively underwrite policies and detect fraud, but regulatory obstacles persist. Big Data is the shorthand term for the explosion of data now available to insurers—often from non-traditional sources such as the public web, social media and cookies. Using data analytics, cloud computing and artificial intelligence, carriers can produce new kinds of observations, measurements and predictions, which can be leveraged for developing new products, assessing risk more precisely, pricing more effectively, identifying highly rated customers, identifying most likely purchasers, servicing claims more quickly, detecting fraud and potentially preventing loss, e.g., sending customers text warnings for impending storms. However, while Big Data is effective at detecting correlations from large amounts of data, a correlation does not necessarily mean there is a causal connection between two factors. Big Data applications also present the potential for a number of other regulatory issues, such as price optimization, unfair discrimination, risk segmentation resulting in elimination of insurance for previously insurable groups, premium volatility, transparency and privacy. Developing compliance strategies will be key prior to implementation of these technologies.
- Insurers are using data analytics powered by artificial intelligence to improve claims processing, fraud determination, underwriting and customer service. Moving well beyond science fiction, artificial intelligence (AI) has significant potential in the insurance industry because it executes complex analyses and computations at lightning speed, resulting in nearly instantaneous insight for insurers. AI is used in many different ways, including: (1) machine learning, which uses algorithms to parse data to make a single determination or prediction ; (2) deep learning, which uses complex algorithms and multi-layered neural networks to learn and improve decision-making over time, e.g., face, image and pattern recognition; and (3) natural language processing, which is the analysis of and machine response in written and spoken language, e.g., Alexa and Siri. These AI methods increase the speed and accuracy of predictive modeling—all contributing to better claims handling, underwriting and customer service.
For more information on Saul Ewing Arnstein & Lehr's InsurTech services, click here.