There is no denying that Artificial Intelligence (AI) can radically transform the insurance industry. However, many organizations have only begun to scratch the surface of its capabilities. How can they truly harness its potential? In a recent LinkedIn Live Webinar, Philipp Schaeuble, Associate Partner & Co-Lead Insurance at Alaika Advisory; Aditya Vimal, Senior Vice President, WNS Insurance; and Gijsbert Cox, Insurance Industry Leader at Appian, shared invaluable insights and guidance.

Many insurance enterprises are integrating AI to enhance customer service, streamline operations and combat fraud. Nevertheless, like numerous other sectors, the insurance industry grapples with the rapid evolution of this technology, which challenges conventional paradigms and threatens to disrupt longstanding operational norms. According to Schaeuble, Vimal and Cox, while AI adoption is proliferating across the industry, many insurers struggle to identify and scale viable use cases, with several projected initiatives failing to materialize.

Critical to success is the strategic alignment of AI initiatives with organizational goals. Insurers must determine whether their AI endeavors prioritize efficiency or efficacy – whether they aim to reduce costs or enhance customer experiences. Ideally, the approach should encompass both, with fraud mitigation as a foundational objective.

Case Study: AI in Motor Insurance

The LinkedIn Live showcased a compelling case study within the Property and Casualty (P&C) domain, where advanced analytics was seamlessly integrated into a specialist carrier's systems. Through an AI application, data extraction from diverse sources facilitated the generation of risk summaries for each case, resulting in a 13 percent increase in daily underwriting project throughput.

Moreover, AI expedited claims processing, delivering cost efficiencies and elevating customer experience. Under the traditional system, vehicle inspections entailed a 14-day wait period, imposing both financial strain and prolonged uncertainty on customers. A predictive AI model was devised that swiftly identifies fraudulent claims and determines repairability during customer-agent interactions, reducing claim management timelines from 30 days to a mere three while concurrently elevating customer Net Promoter Scores by 25 percentage points.

AI's versatility extends beyond text and voice analysis to encompass visual data interpretation. Take the example of a logistics company where trucks are driven from Southampton to Glasgow. The insurer can leverage video feeds from the cab to monitor driver behavior in real-time, ensuring compliance with safety protocols and pre-empting potential liabilities.

AI in Legal Insurance

AI applications can extract relevant information from legal documents such as contracts and submissions, reducing processing time from days to hours. By automating e-mail triage and extracting actionable insights from vast datasets, AI augments operational efficiencies and liberates legal professionals from mundane tasks, empowering them to focus on value-added client engagements.

Despite AI's immense potential, widespread adoption remains a work in progress, Research from Boston Consulting Group ascertains that while 80 percent of business leaders say that they use Generative AI regularly, the figure for non-management employees is a mere 20 percent.

Maximizing the Benefits of AI: Three Actions Insurers Must Take

To overcome challenges and unlock AI's potential, insurance leaders must undertake three pivotal actions:

  1. To navigate the swiftly changing landscape and immense transformative power of this technology, business leaders must proactively craft a strategy to identify and prioritize particular use cases, ensuring optimal ROI. Even the rudimentary implementation of AI tools can yield significant returns on capital expenditure in specific scenarios.

    Insurers must be agile and ready to fail fast and fail forward. While their core expertise lies in insurance rather than technology, they should seek out reliable partners, a trend already gaining momentum among an increasing number of insurers.

  2. Second, the vast data reservoirs that insurance companies hold present them with both an opportunity – and a challenge. They need to start cleaning, categorizing and preparing data for use by the Large Language Models (LLM) that AI uses to “learn” from. Pre-trained LLMs can transform unstructured data, such as phone conversations and e-mail exchanges, into structured data more quickly and efficiently.

    Simultaneously, insurers must consider issues such as security and privacy. Some may think focusing on their own data for LLMs is safer and will produce results more tailored to their needs.

  3. In addition to deploying the technology, insurers must consider cultural change. A Boston Consulting Group survey found that while 44 percent of leaders have received AI training, only 14 percent of front-line employees have received similar training.

    Insurance industry leaders must proactively address any apprehension among their teams regarding job security. They need to foster an understanding that AI serves to complement and augment their roles rather than supplanting them entirely. Encouragingly, there is evidence indicating that once claim handlers, underwriters and other personnel witness first-hand how AI enhances their daily tasks, they readily embrace the technology instead of resisting it.

In conclusion, we must remember that the AI we currently observe represents the baseline of its potential. As AI systems continually ingest more data and acquire deeper insights, their capabilities will only improve over time. With AI poised to revolutionize the insurance sector, delivering significant benefits to insurers and their clientele, there's no better moment (than now) for the industry to wholeheartedly embrace this transformative technology.

Ready to dive deeper into AI's transformative potential in the insurance industry? Watch the insightful discussion HERE.

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