Driving competitive advantage through (Re)Insurance Risk and Exposure analytics
In May 2018, McKinsey & Company wrote a well-regarded piece titled: “Breaking away: The secrets to scaling analytics.” The authors proposed that breakaway companies—those who have achieved the elusive goal of analytics at scale—find success relative to their peers by significantly outperforming others in three key areas: 1) aligning on strategy; 2) building the right foundations of data, technologies, and people; and 3) conquering the last mile by embedding analytics into decision-making and processes.
More than three years on, companies are still struggling to break away: digital transformation, particularly for among insurers, remains a work in progress. Yet today—more than ever—it’s crucial that insurers be capable of change, to be able to confidently manage risk exposure through better-informed decisions, and improve their responses to global and regional events. It’s part and parcel of the drive to be data-driven.
As it relates to digital transformation, technology – applied appropriately—presents a powerful opportunity to mature. Insurers who can leverage advanced analytics to identify and minimize exposure to delimit risk across a variety of fronts, particularly as it relates to exposure to either major catastrophe events or attritional high frequency events, will be ones best positioned to disrupt the market—and emerge as the market leaders of tomorrow, the ones who will, as McKinsey describes, break away from the pack.
Why, though, despite incredible pressure to modernize analytics capabilities, does the insurance industry remain relatively immature relative to peer financial organizations? What particular circumstances hold them back? For one, incomplete, inaccurate data remains a thorny challenge. And two, (Re)insurers continue to face challenges with legacy software, processes and a lack of digitization, which disadvantages them against peers and market opportunities. What’s more, many lack the vital advanced analytics capabilities to align their business plans and efficient allocation of capital against net risk exposure—in both their existing portfolio, and through the pre-bind underwriting of new/renewal business.
As crucial as understanding risk exposure is to this class of (Re)Insurers, however, only 25% of insurance professionals believe that technology enables them to assess risk exposure across portfolios extremely accurately, according to a recent survey by Vanson Bourne.
Despite this low confidence, the need for commercial carriers and reinsurers to understand and manage risk exposure is more acute than ever. Reinsurers must be capable of analyzing large-scale complex financial structures to inform decisions on profit, loss, and exposure. The nuances and complexity of both the Insurer and Reinsurer underwriting process and contract structures requires the ability to negotiate and visualize large swathes of data rapidly and accurately to drive decision-making from the Underwriter to corporate senior management.
Counterintuitively, from an analytics maturity perspective, it’s where they can achieve the quickest wins. In the next five years, underwriting excellence (in the form of triage), the ability to quickly match risk to appetite and exposure management will be major areas where reinsurers can significantly improve their market position.
Fortunately, tomorrow doesn’t have to wait for today. Insurers—particularly those in the (Re)Insurance arena—can begin today to incrementally address exposure management capabilities and take advantage of advanced analytics techniques and emerging data resources with the right strategic partners.
By applying advanced analytics techniques with the fusion of AdvantageGo and Pyramid Analytics—and leveraging third party data resources—insurers can begin to break away and create competitive advantage against their peers. To ensure long-term differential and profitability, Insurers must commence augmenting their underwriters’ tacit knowledge and skill, and ultimately be able to make much faster decisions, in alignment with the overall risk appetite of the organization and optimized to deliver a higher ROI.