By: Andre Gagne, CEO of GFT Canada
The AI revolution has jumpstarted technological advances and innovations across the financial industry as a whole over the past few years, including everything from personal finance agents to automated fraud alerts. This appetite for innovation is now making its way into the insurance industry as well, where the majority of executives (77%) are eager to adopt generative AI before their competitors.
However, AI implementation does not happen overnight. While consumers’ rapidly developing digital expectations are increasing the pressure to push out AI offerings, before insurers can develop externally-facing AI use cases, they first need to lay the foundation for these use cases by transforming their internal operations.
Here are three key areas in which insurers’ internal investments in AI can disproportionately impact their operations from the inside out.
- Shifting From Reactive to Proactive Risk Management
In 2024, Canadian insurers experienced a record high of weather destruction. As a result, many insurers are now facing losses 12 times higher than the annual average due to catastrophic events like Toronto’s flash flooding and wildfires in the Canadian Rockies.
As events like these become more frequent, insurers have increasingly relied on broad, general parameters to determine insurance costs — adjusting when necessary after the fact. But while weather will never be entirely predictable, more precise risk forecasts are possible with AI tools.
AI predictive modeling can help insurers better prepare amid escalating conditions, allowing them to anticipate natural disasters and their potential impact at a level of accuracy that has not been possible previously.
For example, with generative AI, insurance companies can enhance the accuracy of loss-reserve estimates and future liabilities through analyses of historical claims data, pattern identification and simulation of future claim scenarios.
From there, predictive analytics tools can be used to refine pricing strategies and enhance the accuracy of coverage assessments based on the more accurate estimations of claim volumes and potential losses — mitigating overall risk.
- Enhancing Fraud Detection and Prevention
Climate disasters aren’t the only rising risk to insurers. As fraudulent claims in the insurance sector continue to climb, AI can add an additional layer of security in helping insurers proactively prevent these scams.
One of the ways it’s doing this is by transforming claims management. AI algorithms can be applied to flag suspicious, or even just more complex, claims for further investigation. For instance, one of Canada’s largest multi-line insurers is detecting fraudulent claims by deploying a custom AI algorithm that identifies unusual patterns and anomalies in customer data. With the sheer amount of claims that come in daily — and the massive amount of data to sort through for each one — these types of AI tools can pick up on discrepancies in a fraction of the time that an employee could manually.
This not only provides additional security oversight, but by automating the claims monitoring process, employees are freed up to focus on bigger picture tasks such as resolving fraudulent claims.
Although it is possible to build these AI tools in-house, insurers who are still in the early stages of AI adoption may benefit from a more direct path to AI implementation by working with fintechs to build them on their behalf. By collaborating with a technology partner, insurers can introduce solutions that have already been proven to work in the market.
- Accelerating Critical — But Heavily Manual — Internal Processes with Automation
In addition to being responsible for massive amounts of customer data, insurers have a seemingly-unending amount of documents that need to be completed and passed along across the insurance lifecycle — from policies to claims to loss adjustments. This results in numerous time-consuming, manual tasks that need to be ticked off from the time of underwriting to issuance, as well as during any claims along the way.
With AI, insurers can automate these repetitive administrative tasks. For instance, internal creation, delivery and review of documents becomes much more efficient with AI, and reduces processing times significantly.
With the ability to simplify these complex workflows and improve operational efficiency, insurers can concentrate more of their time on innovation while their customers benefit from quicker responses and shorter wait times. This internal automation will additionally set insurers up for further automation in their customer-facing interactions, such as self-service portals for managing policies and claims and AI-powered customer service chatbots.
The financial market will continue to trend towards an AI-driven future. Insurers who make automation and AI central to their internal operations now will not only see short-term efficiency gains, but will also be set up for long-term market success.
