Managing AI risks in the insurance industry
There are real concerns and risks with adopting an AI solution too quickly.
Historically known for its cautious approach to technological innovations, the insurance industry is at a crossroads as it grapples with the integration of artificial intelligence with operations. Recent research from Accenture indicates that 12% of customers trust automated web services for claims, with only 7% trusting chatbots. While insurance professionals and policyholders question AI adoption throughout the industry, there’s no denying the transformative value it brings.
From personalized policy offerings to the streamlining of claims processing, AI advancements have the power to enhance policyholder experiences, improve operational efficiency and create a more secure future. Managing AI risks is an important piece to this, ensuring that the potential advantages of AI and digital transformation are achieved while safeguarding policyholders’ privacy, data security and fairness in insurance processes. It is crucial that we evaluate the benefits of AI adoption across the sector, reasons behind skepticism around AI adoption, and how the insurance industry is managing AI risks.
AI adoption benefits for insurance organizations
The potential of AI is truly untapped, and the applications across companies in the insurance industry are increasing every day. First, AI has the potential to enable the customization of insurance policies based on policyholders’ specific needs. As an example, AI-driven auto policies can monitor driving behavior to determine policy discounts, while smart devices and IoT can help mitigate risk to a property. AI can also streamline the claims process, reducing the time it takes to settle claims from weeks to hours. This improvement in efficiency enhances the policyholder experience and reduces operational overhead for insurance carriers.
Second, AI can aid in handling catastrophic events proactively, turning insurance providers into partners and resources for policyholders. Swift and effective responses to catastrophic events, such as natural disasters, accidents or health crises, can make a significant difference in policyholders’ lives. Events such as these often bring immense stress and disruption, and the ability to respond promptly and efficiently can increase policyholder loyalty while offering a competitive edge.
Navigating AI skepticism in the insurance sector
Skepticism surrounding AI in the insurance sector can be attributed to two main factors. AI, in general, has raised concerns about its safe and ethical implementation across a number of industries. People are wary of the potential risks, such as data privacy breaches, security vulnerabilities and algorithmic bias. Additionally, the insurance industry has been traditionally slow in adopting new technologies due to the complex nature of its business operations. This dual challenge sets the stage for AI to prove its worth in a change-resistant environment while addressing concerns related to policyholder privacy, security and bias.
There are real concerns and risks with adopting an AI solution too quickly, especially if it hasn’t been properly vetted. Mishandling of data sent, stored and processed for AI training can lead to privacy and security breaches. Furthermore, introducing bias into AI algorithms can have detrimental effects on coverage and claim determinations. It’s essential to address these concerns proactively in order to gain policyholder trust when implementing AI-powered solutions.
Managing AI risks across insurance operations
Managing AI risks is an imperative part of the digital transformation journey for companies in the insurance industry. Mitigating these risks safeguards the interests of insurance providers and policyholders, while also upholding the industry’s reputation for trustworthiness and fairness.
Addressing bias is a critical consideration when implementing AI in the insurance industry. Building models that base decisions on narrow or biased data could lead to discrepancies, such as those related to economic class, which can conflict with privacy regulations like GDPR. A measured approach to AI solutions is essential to mitigate these risks. For risk-averse companies, adopting advanced analytics and decision-making frameworks can be viable alternatives to address various challenges while maintaining greater control over data usage and bias mitigation.
Companies in the insurance industry are adopting various approaches to manage and mitigate AI risks. Some rely on third-party providers, trusting that these vendors have properly vetted their AI solutions. However, a cautious approach is required to ensure third parties have mitigated the risks associated with AI implementation. On the other hand, some companies remain hesitant to adopt AI until it undergoes more extensive vetting. Striking a balance between innovation and security is crucial, and insurtech solutions like Hubvia have embraced a thoughtful and strategic approach to ensure that AI applications enhance user experiences without compromising privacy and security.
AI has the potential to revolutionize the insurance industry by enhancing policyholder
experiences, streamlining processes and improving risk assessment. There are many trends driving this sector forward — the use of omnichannel interactions and policyholder-facing chatbots, to name a few — but none of these matter without the careful research, development and vetting of AI-powered technologies to ensure companies and policyholders remain safe and secure. Striking a balance between innovation and security is key to unlocking the full potential of AI in the insurance industry and earning the trust of policyholders. With careful planning and the right safeguards in place, AI can become a valuable asset for the insurance sector.
Jennifer Dalton (jen.dalton@brushclaims.com) is the Chief Information Security Officer at Brush Claims.
See also: