By Catherine Loftus / Head of Growth Marketing, Nuon AI
From market pricing optimisation to enhancing customer service capabilities, it’s clear that artificial intelligence (AI) technology offers huge potential for insurance organisations. However, challenges can arise in implementing AI solutions effectively.
In this blog we will explore those potential blockers and how insurers can avoid them in order to successfully harness the power of AI.
Challenge 1: Data quality and availability
AI algorithms can require large quantities of high-quality data to make accurate predictions and decisions. While the insurance industry has made significant strides in modernising its capabilities, the availability and quality of data needed to train AI models effectively can often be a challenge.
How to overcome: Before embarking on an AI transformation project, it may first be prudent to invest in a data management system. This can ensure data integrity, consistency, and accessibility.
Of course, it depends on the type of AI you are looking to implement – and with which partner. To produce a Pre-Flight Simulation with Nuon AI, which will analyse the structure of the product and data to ensure compatibility, requires only an anonymised extract of quote data, going back 1-3+ months. This will provide an indication of how the AI will perform in terms of speed and response, in line with simulated market conditions.
Read more: How does Nuon AI work with my data?
Challenge 2: Busy I.T. teams, working on legacy systems
One of the key blockers we often hear when talking to insurance customers is that while they are keen to begin their AI transformation journey, IT teams are busy. This is particularly the case when working with complex legacy systems, created long before the proliferation of AI solutions. This brings an additional concern that these systems may not be able to adapt to support AI technology.
How to overcome: While system upgrades may be on the long-term roadmap, that shouldn’t hold you back. Not all AI solution providers require a rip and replace of current IT infrastructure, including Nuon AI – our real-time market pricing solution plugs seamlessly into existing systems via an industry standard API call.
Find out more: Is real-time AI pricing right for my insurance product?
Challenge 3: Internal resistance to change
By its very nature, the insurance industry is risk-averse. As a result, team members may be resistant to the adoption of AI due to fear of job displacement or the need to learn new skills. Plus, when other business priorities such as negotiating new capacity or working with a new provider are a focus, it can often not feel like the right time to also venture into new technologies.
How to overcome: Ultimately, the performance uplifts that can be driven by AI are significant, so to delay exploring AI solutions is to delay potential growth. Promoting a culture of continuous learning and employee up-skilling can help teams embrace AI and discover how it can complement, not replace, their work.
Form fostering a culture of learning, encouraging experimentation and partnering with carefully selected innovation partners, read our blog on how to create a culture of innovation within an insurance organisation
Challenge 4: Bias in AI models
AI models can be susceptible to biases present in historical data, potentially leading to unfair outcomes, discrimination, or skewed predictions. At Nuon AI, this is a topic we have actively worked on to put in place strategies to eliminate bias from our own AI.
How to overcome: We have implemented three strategies for overcoming AI bias.
- Don’t add discriminatory data, such as gender and ethnicity, in the first place
- Deal only in ‘hashed’ data
- Perform counterfactual checking tests
When working with any AI solution provider, ask them about their AI bias reduction strategy to ensure there is a plan in place. You can find out more about the Nuon AI approach to reducing AI bias here.
While implementing AI in insurance comes with its challenges, the potential benefits are substantial. Insurance companies that proactively address these challenges and strategically adopt AI solutions can gain a competitive advantage, enhance customer experience, and streamline operations.
For more on how to successfully introduce AI technology to your insurance product, read our AI Adoption Playbook.
