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Change Happens: How AI Decisioning Is Transforming Insurance

by | Last updated on Jan 22, 2024

More and more specialty and P&C insurers are discovering the many benefits of enhanced AI decisioning.

Among all service industries, insurance is one of the earliest. Wikipedia dates the first risk management measures to sea-going Babylonia, Chinese and Indian merchants in the 2nd and 3rd centuries who would distribute trading cargo among several boats as a hedge against treacherous waters and the threat of losing everything with the capsizing of a single cargo craft. Today, instead of high seas, businesses must contend with threats on sea, land, air, space, underground and undersea, not to mention the unseen world of fiber optic cables steaming endless strings of code to billions of devices in every corner of the globe.

All these potential risks spell real opportunities for today’s insurers, as well as boosts in their typically bond-heavy investment portfolios from a down economy. However, the ones poised to fully serve the many and evolving needs of today’s commercial customers are the ones that are already leveraging the power of no-code AI and enhanced decisioning.

Actuaries, underwriters, product and claims managers resistant to transformative change of integrated automation should check out some proven investment returns, namely:

80% time savings – No-code AI decisioning saves insurance organizations a reported average of 80% reduction in time spent changing or updating decision logic. Insurance subject matter experts can author, update and deploy their own decision logic faster and without IT intervention with easy-to-use menus and business language rules. InRule also connects and automatically extracts relevant data from external, siloed databases, allowing insurance subject matter experts more time to focus on their core jobs.

Effective balancing of sales vs. stop loss – Perhaps as old as the risk-assessment profession itself are the pressures actuaries and underwriters face from insistent sales and product managers to potentially raise stop-loss rates by approving as many applications as cash reserves will support. AI power is a friend and aid to both camps. Decisioning, backed by machine learning, empowers insurers to hit and maintain their desired risk levels, whatever they may be, while ensuring a safe and appropriate amount of risk.

Lower and lower churn rates – Explainable machine learning can comb data on every customer and transaction as well as available global databases, revealing the percentage likelihood of a customer churn and the factors behind their choice, listing the percentage impact of each and what might inspire them to renew. Armed with big-data insights, subject matter experts can hone decision logic to send the ideal offer at the moment of greatest impact. Any misfires that fail to win back a customer are just more data to further hone decision logic.

Efficiency that compliance demands – Every insurer with national or regional reach must contend with the multiplicity of laws, regulations and government bodies, both internal and external, overseeing the organization. Many tech-forward P&C and specialty insurers are finding regulatory and legal compliance a vital job that can be improved through automation. Insurance subject matter experts can help ensure all changing laws, deadlines and regulations are properly executed by leveraging enhanced decisioning supported by process automation.

Minimization of long-range payouts – A particular hazard for insurers is payouts for claims that arise years after policy initiation, even after the original policy expires. Explainable machine learning reveals the associated factors that may alert to potential long-range exposure. Decisioning provides an accessible way to put ML intelligence to work, flagging specified applications for further review and enforcing guardrails to reject policy applications that may result in a payout, years, even decades later.

Ownership of product markets by creating them – Powerful machine learning can comb mass data sets to inform product managers where policy needs are trending. AI-equipped insurers can leverage ML predictions to make more informed decisions on what products to bring to market, and AI decisioning can help set the rules that bring the product to life, introducing tailored coverage products to meet needs as quickly as they arise, and before competitors.

To learn how InRule empowers specialty and P&C insurers like Aon, Allstate, Beazley, Tokio Marine and Markel, download our latest white paper, Underwriting, Pricing, Claims, and Retention: The Power of AI Benefits Every Aspect of Insurance.

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