The insurance industry has a reputation for being a late adopter of new technology. However, that is starting to change, thanks in part to the advent of artificial intelligence (AI). UK insurance companies are beginning to experiment with AI in several ways, from using chatbots to handle customer queries to using machine learning to detect fraud.
There are a number of good reasons why the insurance industry is turning to AI. In the UK alone, the AI insurance market is forecast to grow from £39 million in 2018 to £224 million by 2023, according to Juniper Research.
This reflects a growing awareness of AI’s potential benefits, including:
1 | Faster claims processing
One of the most significant advantages of AI in insurance is that it can help to speed up claims processing. By automating repetitive tasks and using data analytics to identify potential fraud, AI can help reduce the time it takes to settle a claim.
2 | Improved customer service
AI can also be used to improve customer service and engagement. For example, chatbots can provide 24/7 assistance with policy questions or claims inquiries. And by proactively monitoring social media, insurers can quickly address customer concerns before they turn into negative reviews.
3 | Reduced costs
Perhaps the most compelling benefit of AI for insurers is that it can help to reduce costs by
- Automating manual processes, freeing up staff time for more value-added activities
- Identifying fraud and errors, thus reducing losses and improving bottom-line results
These are just a few of the many ways that AI is transforming the insurance industry. As insurers continue to embrace this technology, we can expect even more innovative applications in the years to come.
It’s no surprise that insurers are starting to take notice.
Further reading: What does AI mean in insurance?
Startups making waves within insurance AI
Here at Ai, we’ve fully embraced the future of insuretech and developed an AI platform that makes algorithmic underwriting a reality for insurers, brokers, MGAs and insurance technology platforms.
Through our unique API-connected real-time pricing technology, your pricing strategy is given a true competitive edge as millions of experiments run seamlessly to:
- Optimise insurance pricing
- React to competitor price changes fast
- Protect profitability by reducing the risk of money being left on the table.
Hippo uses machine learning to analyse a customer’s home and compare it to similar homes to determine the replacement cost. This information is then used to calculate premiums.
US startup, Next Insurance, provides on-demand insurance for small businesses.
The company uses AI to evaluate a business’s risks and provide a custom insurance policy tailored to the business’s needs. This gives small businesses access to insurance coverage that is both affordable and comprehensive.
SafetyChain is a Canadian startup that uses AI to improve construction industry safety by analysing data from construction sites to identify potential safety hazards.
This information is then used to create customised safety plans for each construction site. By reducing accidents and injuries, SafetyChain is helping to make the construction industry safer for everyone involved.
Lemonade use AI to streamline the insurance claims process. Customers can file a claim through the Lemonade app, and the company’s chatbot gathers all the necessary information and submit it to the insurer.
The claim will be paid out within a few minutes if everything goes smoothly. And if there’s any dispute, it will be referred to a panel of human experts for a decision.
These are just a few examples of how AI is used in the insurance industry. It’ll be both interesting and exciting to see how these startups fare in the coming years.
Insurance AI governance
As much as the benefits of AI in insurance are undisputable, questions around its implementation have and shouldn’t be ignored.
This need to continue as AI increasingly becomes a part of our lives, meaning insurers must adapt their governance structures and control frameworks to ensure their AI systems do not cross acceptable boundaries.
The European Insurance and Occupational Pensions Authority (EIOPA) published in 2021 its AI guidelines for the insurance sector, where six key principles of effective AI governance were given.
Principle one. Every AI insurer should have a clear and dedicated governing body responsible for developing and overseeing its AI strategy. This governing body should be composed of individuals with a deep understanding of AI technology, business, regulation, and ethics.
Principle two. Every AI insurer should establish a robust and transparent risk management framework to address risks associated with AI applications. This framework should be tailored to the insurer’s specific risks and consider the evolving nature of AI technology.
Principle three. Every AI insurer should have a clear and concise data use policy aligned with its business strategy. This policy should specify which data will be used for what purpose, how it will be collected and stored, and who will have access to it.
Principle four. Every AI insurer should invest in training and education for its employees to ensure they can understand and critically evaluate AI applications. Insurers should also encourage their employees to report any concerns they have about AI applications.
Principle five. Every AI insurer should disclose information about its use of AI in an accessible, understandable, and transparent manner to customers and other stakeholders. This disclosure should explain how AI applications are used and why they are used.
Principle six. Every AI insurer should monitor developments in AI technology and related fields – such as data privacy – on an ongoing basis and update its policies and procedures accordingly.
EIOPA has set a high bar for insurers adopting trustworthy AI practices. The guidelines are a welcome addition to the discussion on how best to govern AI in the insurance sector.
The future looks good for insuretech
As we’ve seen, AI insurance can offer several benefits, from reducing costs to increasing efficiencies.
This should mean that the whole insurance process is more beneficial for everyone involved – from customer to underwriter.
But, as with any new technology, some challenges must be addressed to ensure that AI is used responsibly and effectively.
As the insurance industry continues to evolve, it will be important to keep a close eye on AI developments and ensure that they are incorporated to best serve the needs of policyholders and the industry.