Decoding AI Decisioning: A Game-changer for the Insurance Industry
Revolutionize insurance with AI decisioning to boost efficiency, customer satisfaction, and top-line growth for insurers.
Rafael Goldberg, head of decisions at Sapiens International, explores the future of insurance. Discover how AI decisioning transforms the industry, drives efficiency, and enhances customer satisfaction.
Generative AI, the latest groundbreaking technological leap to send shockwaves through our digital world, is predicted to soar to a staggering market value of $110.8 billion by 2030. And it’s not the only cutting-edge AI advancement with a bright future – Machine Learning is on an even faster trajectory, with some growth projections estimating it will reach a market value of up to $225.9 billion by 2030, according to Fortune Business Insights.
This impending boom comes partly at the hands of the two AI technologies’ widespread use case opportunities across industries – a few corners of business and industry will be left untouched by the potential of these disruptive forces.
The insurance industry is no exception.
But as with any innovative tech, jumping on the bandwagon of a hot new tech trend won’t go very far without a keen strategy pulling the wagon from the front. For insurers hoping to unleash the full power of Generative AI and machine learning, a winning strategy combines it with decision management technology, which shows tremendous promise as a path forward for revolutionizing insurance in the automated age.
Though perhaps not as sexy or trendy as its AI and ML counterparts, decision management technology is arguably just as important – consider that the market size of decision management technology is expected to nearly triple by the end of the decade, as per Fortune Business Insights.
Aptly dubbed The Great Unlock, the rise of “AI decisioning” – a dynamic fusion of cutting-edge AI technology with decision management solutions – can improve top-line growth, elevate customer service, and streamline operational efficiency throughout the insurance value chain.
Uniting Probabilistic Processes and Deterministic Outcomes
The heart of AI decisioning lies in combining two distinct capabilities crucial for insurance: probabilistic models facilitated by AI and machine learning and deterministic models dictated by decision management tools.
The former provides probabilistic results – insightful, creative, and intuitive outcomes but not definitive. Alternatively, the latter offers computational precision, guaranteeing that consistent and specified conditions yield specific and consistent outcomes with certainty – algorithms that tell you exactly what you expect every time.
Think of it as the right and left brains of cutting-edge insurance processes. Each side of the brain has unique and equally noteworthy strengths, but they are limitless together.
In this sense, AI decisioning is so uniquely promising in its ability to seamlessly unite the creative extrapolation needed to glean unique insights with the precision to act on those insights consistently and efficiently. The result is a perfect combination of automated processes for an industry that walks a fine line between risk assessment, which exists in uncertainty, and strategic planning, which requires as much certainty and consistency as possible.
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Creating Decision Models with Generative AI
Thanks to Large Language Model (LLM) APIs – think, for example, an AI-powered chatbot or a message-based help center on the homepage of a business – readily accessible generative AI tools are paving the way for AI decisioning to be seamlessly integrated into the insurance industry.
Like their consumer-facing counterparts, these integrated large language models offer insurance professionals a dialogue-like interface to articulate decision model conditions while working on internal processes using internal platforms. In the same way that a blogger or content writer might prompt ChatGPT to generate a bulleted outline they use as the basis for writing a compelling original article, insurers can turn their business policy into practical decision models uniquely suited to the needs of any given insurance operation.
Integrating Machine Learning Models within Decision Models
Today, machine learning models are the domain of data scientists and thus remain a black box to many business professionals who otherwise lack training in that realm. This is not unlike many professionals’ relationship with decision models in an earlier era of tech-driven business when developers implemented business rules before business-friendly decision management systems.
With the low barrier to entry of AI decisioning tools, insurers can now more readily gain visibility and control over powerful machine learning models by integrating those capabilities into decision management systems where the visual modeling, testing, and governance are well established for non-technical users. As ML models become strategically integrated within decision models, insurers of all technical backgrounds and skill sets will be better equipped to fully understand, control, and navigate their decisions through the lens of both uncertain risk factors and certain policy factors.
Reaping the Benefits
What are the tangible benefits of AI decisioning for insurers?
Across the value chain, insurers struggle to stay competitive – from the 12-18 months it can take to bring new products to market to marketing new products and packages, underwriting and servicing claims for products, insurers constantly face a slew of challenges. Fortunately, insurers can apply the combination of AI and decision management across increasing points during the product lifecycle to powerful effect.
In addition to greater cost efficiencies and improved customer satisfaction in customer service and claims, insurers can drive top-line growth with use cases like next-generation recommendation engines. These will ensure, for example, that only the most well-suited products are offered to the right customers at the right time, place, and price, maximizing the effectiveness of sales efforts and improving customer satisfaction and loyalty.
A New Landscape
The process of bringing AI and decision management together demands meticulous orchestration. As insurance companies navigate the unique contours of their industry, from risk assessments to customer interactions, they are bound to face distinct challenges.
But the potential of The Great Unlock is clear, and the insurance industry is on the verge of an era defined by this unprecedented synergy. Through synthesizing probabilistic and deterministic models, insurers can create unified decisions driven by the real-time insights AI can provide, executed with the precision of keen decision management.
The result: A more flexible insurance industry with quicker introduction of new products, increased customer engagement, and well-optimized operational systems across the board.
How is AI decisioning reshaping the insurance landscape? Why is it essential for insurers today? Let us know on Facebook, X, and LinkedIn. We’d love to hear from you!
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