I decided to do a follow-up article on Artificial Intelligence (AI) and insurance broking following the massive advancements in Generative AI in the past year. AI is a buzzword we’ve all heard a ton of, but 2024 is proving to be a game-changing year, especially when we talk about generative AI. We have witnessed a surge in AI capabilities, pushing the boundaries of what was once considered science fiction. From the emergence of hyper-realistic deep fakes to the continued evolution of predictive analytics, these advancements are poised to reshape the world as we fundamentally know it.
It’s nearly impossible to go a day without hearing about the potential uses and implications of generative AI—and for a good reason. Generative AI has the potential not just to repurpose or optimize existing data or processes, it can rapidly generate novel and creative outputs for just about any individual or business, regardless of technical know-how. It may come as no surprise then that generative AI could have significant implications for the insurance industry.
Rapid Advancements and Opportunities
Predictive analytics are already changing the way brokers think about risk, coverage, and costs. Using predictive analytics can help brokers change their approach to building strong customer relationships as well.
Tools like predictive analytics, however, demand a more personalized approach to insurance. Instead of seeing customers as examples of a general, homogenized set of risks and needs, predictive analytics create both the challenge and the opportunity for brokers to see their customers as individuals. Thus, disrupting not only how insurance brokers do their work, but also how they think about the insurance business.
Generative AI – a type of artificial intelligence that has the ability to create material such as images, music, or text – is already a proven disruptor and its adoption is growing at an explosive rate
The insurance market's understanding of generative AI-related risk is in a nascent stage. This developing form of AI will impact many lines of insurance including Technology E&O/Cyber, Professional Liability, Media Liability, and Employment Practices Liability among others. Insurance policies can potentially address AI risks through affirmative coverage, specific exclusions, or by remaining silent, which creates ambiguity. AI presents significant opportunities but also introduces new risks.
In today’s formative era of generative AI, the popular enterprise opportunities and use cases are general purpose and are applicable across various industries or functions; sometimes categorized as “horizontal” use cases. Examples include dialogue generation for virtual assistants, automated code generation, marketing and sales content generation, etc. This use-case convergence across industries enables organizations to leverage capabilities built by others to improve speed to market and become fast followers.
However, the insurance industry presents distinctive sector-specific sustainable value-creation opportunities, referred to as “vertical” use cases, requiring domain knowledge, contextual understanding, expertise, and potential investment in fine-tuning existing models and building special purpose models. For example, point solutions are created for the analysis of unstructured data to identify risk patterns that inform underwriting decisions or provide claimants with instant information when they file the first notice of loss. The real game changer for the insurance industry will likely be bringing disparate use cases together to build a holistic, seamless, end-to-end solution at scale.
Deep Fakes
In an age where technology continuously shapes and reshapes our reality, the insurance sector faces a formidable challenge: the rise of deepfake AI fraud. As AI becomes increasingly sophisticated, so do the methods employed by fraudsters, leaving businesses, individuals, and insurers in a precarious position
Deepfake technology utilizes AI and machine learning algorithms to create hyper-realistic video and audio recordings. Initially gaining notoriety in celebrity fake videos and misinformation campaigns, this technology is now being exploited more sinisterly, particularly in executing elaborate scams and fraudulent activities.
Recent incidents underscore the gravity of this issue. A finance worker at a multinational firm was deceived into transferring $25 million to fraudsters who used deepfake technology to impersonate a company executive during a video call. This incident is among a series of similar deepfake scams, highlighting a disturbing trend of AI-generated heists that have successfully conned individuals and businesses out of substantial sums.
As deepfake technology continues to evolve, so must the strategies employed by the insurance industry to combat its misuse. By staying informed about technological advancements, investing in cutting-edge detection tools, and fostering a culture of vigilance and education, insurers can better protect themselves and their policyholders from the growing threat of deepfake AI fraud. In an era where seeing and hearing are no longer believing, the insurance sector must remain at the forefront of innovation and resilience.
Future Outlook
In the AI age, insurance brokers are likely to leverage technology to enhance their efficiency, improve customer service, and streamline operations. They may use AI tools for data analysis, customer relationship management, and process automation, allowing them to focus more on high-value tasks that require human judgment and empathy.
Overall, while the role of insurance brokers may evolve in response to advancements in AI, there is still a strong need for brokers to provide personalized service, expert advice, and a human touch in an industry that revolves around managing risk and protecting individuals and businesses.
The future of insurance brokers in the age of AI is likely to involve a significant evolution in their roles and responsibilities rather than complete obsolescence.
A big question is whether insurance brokers will need to keep up with the changes in AI at the agency/broker level to keep up with the insurer's advances in this space. What happens if an insurer decides to remove brokers from their value chain because of AI?
How brokers stay relevant with updates in AI can be considered similar to changes in computing, cell phone technology, email, social media, and video and will merely be a piece of a broader puzzle that is still held together by brokers.
Duncan Ekasi Otiti | Chief Broking Officer | Minet Lesotho
References:
- https://paifgx.medium.com/a-2023-snapshot-how-far-has-artificial-intelligence-come-610d0375dab2
- https://www.technologyreview.com/2024/05/29/1092235/ai-readiness-for-c-suite-leaders/
- https://sloanreview.mit.edu/article/mit-smrs-10-ai-must-reads-for-2023/)
- https://kpmg.com/xx/en/home/insights/2024/03/ai-in-insurance-a-catalyst-for-change.html
- https://www.linkedin.com/pulse/navigating-storm-rise-deep-fake-fraud-insurance-industry-goode-gmsme
- https://www.propertycasualty360.com/2024/05/08/fraudsters-using-ai-to-manipulate-images-for-false-claims/?slreturn=2024060741946
- https://stories.simplyioa.com/the-rise-of-deepfake-ai-fraud-for-insurance
- https://www.aon.com/en/insights/articles/how-is-the-insurance-market-responding-to-generative-ai
- https://www2.deloitte.com/us/en/pages/financial-services/articles/generative-ai-in-insurance.html
- https://riskandinsurance.com/generative-ai-set-to-transform-insurance-distribution-sector/
- https://www.quora.com/What-is-the-future-of-insurance-agents-or-brokers-in-AI-age
- https://www.boltinsurance.com/insights/blogs/predictive-analytics-insurance
- https://www.duckcreek.com/blog/predictive-analytics-reshaping-insurance-industry/
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