People literally trust their lives to insurance. In this sense, trust is non-negotiable for the insurance industry. Insurers that do not establish or maintain trust with their customers, governing bodies and regulators simply will not survive.

As the capabilities of artificial intelligence expand rapidly, insurers – like all businesses – are responsible for managing the technology effectively. They must ensure that their use of AI is governed and that their data is not biased. At the same time, they’ll need to embrace ethical approaches that adhere to multiple layers of guidelines and regulations, such as those that protect privacy.

To be clear, many insurers are already using AI. A private passenger auto (PPA) survey published by the National Association of Insurance Commissioners revealed that of the 193 insurers who responded, almost 90% were currently using, planning to use or exploring the use of AI/machine learning.

And as Reggie Townsend (Vice President of the Data Ethics Practice at SAS) puts it: “Trust in AI has to start before the first line of code is written.”

A high-level focus on AI and technology issues

With so much emphasis on using AI across the business, insurance boards are changing their approach to IT issues. Over time, they will shift to an expectation for senior managers (CEOs, COOs, CROs, etc.) to own IT issues rather than handing them off to back-office experts.

Due to the risk of misusing technology – heightened by generative AI (GenAI) tools like large language models – boards will insist on addressing bias, control and trust at a granular level. The reasons? If data is biased, analytic results will be biased. Lacking controls, some will use AI improperly. And without an emphasis on trust, insurers will lose customers’ confidence.

Read more in: AI bias, control and trust: A roadmap for insurance

A risk-based approach to GenAI

GenAI can affect virtually every aspect of the insurance business, from customers to claims. Evaluating this transformative technology from a risk management perspective is crucial for anticipating and mitigating potential consequences.

For claims and underwriting, as well as investments and all other functions of the business, insurers should do a thorough risk assessment to understand the risks of GenAI. This approach will preserve the integrity of the company’s data, reputation and profitability. A proactive, risk-based approach will also safeguard operations, help maintain trust with policyholders, and position insurers to stay in step with ethical and regulatory standards.

Learn more from: Exploring the risks and opportunities of generative AI for insurance

The value of novel data sources for AI

When it comes to underwriting, insurers increasingly rely on new data sources to make their risk analyses more robust. Many insurers now collect data from telematics, aerial imagery, IoT devices and social media and use it with AI to help them evaluate underwriting parameters.

Having richer data sets can certainly make analyses more robust. But accessing and using this data requires added diligence around data protection and privacy. A best practice involves keeping a human in the loop to ensure guidelines are followed and trust is maintained.

Underwriting using telematics provides more of an accurate risk assessment. Most tier-one carriers are already using it.

Franklin Manchester, SAS Global Insurance Advisor, quoted in Insurance NewsNet

The next new employee: AI?

Insurers understand the need to consistently apply standards to their AI tools. But with the expanding role of AI for insurance, it’s becoming important to ensure these AI tools are “onboarded” to the company in the same way a human would be when starting a new job.

The concept is especially relevant for GenAI tools. Such tools learn from existing data (video, audio, computer code, text, etc.) to generate new content that resembles the real-world data from which it learned.

Traditional human resources techniques can help govern AI tools. The key to making it work involves connecting the knowledge of IT and HR to identify intersections where an advanced AI development plan could be helpful.

Read the article in Carrier Management: Meet Your New Employee: Advanced AI

Get in the GenAI race, or lose out

The potential value for insurers that adopt GenAI is huge, reflected by the fact that the technology is a high priority for CEOs. In a Fortune/Deloitte CEO survey, 79% of CEOs surveyed said that accelerating innovation is one of their top use cases for implementing GenAI.

To take advantage of this opportunity, the traditionally slow-moving insurance industry will need to embrace GenAI technology quickly. At the same time, investing in the technology necessitates careful consideration. After risk-based evaluations, insurers should quickly determine which GenAI techniques will truly be impactful for their business – then move ahead.

See how insurers can transform from a focus on indemnification to a focus on prevention


About Author

Cindy Turner

Sr Communications Specialist

Cindy researches, writes and edits content about the company’s technology – from fraud and risk to data management, analytics and IoT. She focuses on several industries, including banking, public sector and insurance. A long-time marketing communicator, Cindy has published content in many formats, but she specializes in long-form content like articles and blog posts, brochures, e-books and white papers.

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