Increasing market share and financial health for insurers

Today’s insurance industry faces unprecedented challenges ranging from increasing CAT risks, higher customer churn due to new entrants and distribution channels, rapidly advancing technology, and also monetary and social inflation. One of these factors, however, is different from the others: new technology can – and must – be harnessed to gain a competitive advantage, if not simply to maintain a stable position. As the pace of change accelerates, how quickly insurers accomplish this imperative will define market share over the next five to 10 years. Given the pace of these multiple ecosystemic changes, those future rankings will likely look different from today’s. This article provides a roadmap to lead insurance companies to a successful outcome.

Positioning P&C insurers for the required speed of innovation
A significant challenge for insurers is overcoming the limitations imposed by legacy technologies, coupled with product and cultural inertia. Whatever core systems carriers may be using, the ability to easily and quickly integrate with new partner APIs is critically important to innovation and to protecting and growing market share. As a case in point, a PwC report found insurers with higher levels of product innovation experience a 9% higher growth rate in DPW, compared with those launching fewer products. Despite the perceived high costs of new technology, maintaining legacy systems consumes on average 70% of an insurer’s annual IT budget. If insurers are spending a majority of resources paying off technical debt, they may need to invest more and faster, to take an adequately innovative position.

Emerging technologies drive success for innovative carriers
The trillion-dollar insurance industry is vital to holding together the economy, and indeed, peoples’ lives and dreams. The industry is also still undergoing several waves of technological evolutions. Some of these developments are foreseeable, historically inevitable and overdue. This is not the first time when powerful new technology transformations in early-adopter industries go on to impact older ones. In this case, large tech companies have been refining the world’s best new methods of predicting human behavior over the past twenty-plus years. Some of the biggest names in tech, in fact, are primarily predictive engines of human behavior, which happen to serve marketing and ecommerce applications. 

The size of the insurance industry is much larger than those applications, and arguably of greater importance to holding together economies, our largest investments and social trust itself. It is clear to virtually all industry analysts and thought leaders that the destiny of the insurance industry is to benefit from the superpowers of big-tech predictive engines of human behavior. Nowhere is this fate more obvious than in P&C personal and small business lines, where information on insured persons (as opposed to property) has been insufficient relative to its importance in accounting for insurance risk amongst individuals. The increase in lift achievable by adding in new and complementary signal via the adaptation of proven big-tech methods, is of greater consequence to predicting insurance risk than consumer credit was during the 2000s. Specifically, loss ratio reductions of three to 10 points are achievable.

The aggressive automation of tech platforms enables carriers to build and validate actuarial loss models using new and complementary signal, and to quantify dollar savings and loss ratio reduction, in under 24 hours, and to commercially deploy custom scores within minutes.

The future in 10 Years — or right now
Achieving these big-tech benefits for insurance is extremely complex. In fact, that’s a bit of an understatement. Adapting the predictive capabilities of companies like Google and Amazon to our highly regulated industry involves undergoing many dozens of evaluations of entirely new classes of data, knowing which types to exclude for various technical and regulatory reasons, building custom supply chains, pioneering the adaptation of deep learning and other state-of-the-art algorithms to the actuarial sciences, building regulatory compliance programs in multiple areas, providing explainability, solving difficult challenges in the area of identity resolution, and providing output in real time, among numerous other significant challenges. In short, achieving this goal requires building a new “Google” engine that has several additional, specialized layers of complexity.

There are critically important decision points that arise in the course of managing corporations when leaders must ask whether to build new capabilities from scratch, or to partner, license, or acquire a strategically valuable product. In this case, building from scratch is ill-advised because there are too many significant technical hurdles outside of the core business of insurance. To fully appreciate this point, consider just one area mentioned above: identity resolution. If an insurer feels inclined to build something from scratch, start with that challenge. If the team can match specialized existing solutions in performance, then a carrier may have what it takes.

However, achieving that and building the rest will easily take 10 years, and by then the insurer will be far behind. So, any of the other options — partnering, licensing or acquisition — are far superior because they set the course for near-term competitive advantage today. Insurers that have already begun embracing these strategic capabilities have ensured that they do not fall behind in their vital objectives of best serving their customers, increasing their financial health and growing their market share. The time is ripe to invest in proven, high-yield technologies now.  

Adopting new capabilities safely and wisely
Whether partnering with larger or smaller companies, and whether they use advanced AI or traditional methods, it’s important to vet them for compliance in several areas. Partners should have third-party audits to show compliance with privacy and information-security frameworks like SOC 2 Type 2 or similar. Prospective partners should also be able to furnish third-party legal and technical audits of compliance with regulatory frameworks related to fairness with respect to protected classes, as well as satisfying other key criteria. If there is any uncertainty on fairness criteria in the state-regulated insurance industry, then the most prudent approach is to look to adjacent industries in financial services with stricter levels of federal regulation, such as employment and housing.

The early adoption of more uniform and stricter standards with regard to fairness entails multiple benefits for carriers. These include being prepared for a future regulatory environment in which additional states prohibit the use of credit, zip code, natural language, or social media from insurance rating and underwriting. Positioning a company for a more equitable future also opens up profitable new market segments that previously lacked sufficient information for safe expansion.

Analyzing insureds as the true individuals who they are is more efficient for predicting insurance risk. And doing so is also fairer than grouping people into larger categories based on geography, demographics or even credit. So, gaining these strategic capabilities is not only a means to compete, grow your market share and do well; the right tech partnerships are also a means to do good.

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