As the insurance sector competes to win market share, Henry Jinman at EBI. AI discusses three ways companies can benefit from the power of Artificial Intelligence.
The UK general insurance market continues to be fiercely competitive. While the battle for repeat business keeps downward pressure on pricing, a constantly changing regulatory agenda increases costs. Whatever the industry, successful companies know that building a business based on price alone is not sustainable. Customer service is what matters most. It’s a sentiment that is reflected in the latest findings of multinational professional services company Ernst & Young (EY). It claims that non-life insurance companies in particular should “invest to create innovative and satisfying end-to-end customer experiences” with optimised technology that helps them become “data-driven and insight-enabled” in everything they do.”
It’s time to consider the benefits of Artificial Intelligence (AI). Through its ability to capture, analyse and learn from massive amounts of data, AI should be at the centre of every enterprise serious about creating amazing customer experiences. AI tools should also support everyone, employees, managers and customers, to ask and receive the information they need, whenever and wherever they need it, quickly and using engaging, natural language.
3 ways to boost CX and win market share using AI
In EBI.AI’s experience, companies that introduce AI solutions such as AI assistants are rewarded with multiple benefits. By reducing the number of repetitive calls in the contact centre or customer service departments and frontline staff are better equipped to handle more complex and rewarding tasks. Meanwhile, scaling today’s virtual AI solutions is easy, enabling managers to adapt to unexpected events and emergencies as they happen such as the Covid-19 pandemic. Data-driven AI solutions also make formidable weapons against the common problems facing insurance managers such as highlighting fraudulent claims and mitigating claims leakage.
Here are 3 ways AI can help the insurance industry in key areas:
1.Front-end sales – train the latest AI tools to answer the most common questions quickly then maximise their ability to use critical customer data to offer personalised recommendations on policies and pricing. Integrate AI with sophisticated telematics in-car sensors or health analytics platforms to identify your most careful drivers or health-conscious clients to reward them with lower premiums so they keep coming back.
2.Product and marketing – deliver customers an exceptional experience with AI tools that are welcoming, efficient and secure. Use AI’s image, video and natural language capabilities to assess and analyse claims and issue fast, accurate pay-out decisions in seconds. Then build confidence and loyalty with AI’s ability to flag up potential threats from scammers and hackers to keep customers’ sensitive details safe. Once these important foundations are in place, make AI an intrinsic part of your marketing toolkit. AI can propose personalised offerings based on customer needs and then swiftly identify opportunities for intelligent lead generation.
3. Customer management – AI tools guarantee round-the-clock customer service – they never sleep, go off sick or need a holiday! Virtual Customer Assistants (VCAs) for example, are a bonus to customer service departments through their ability to cross-sell, upsell and prevent agent churn. AI tools can match customers with the most qualified available agents to handle their queries or, when applied over large data sets, provide analysis of general customer sentiment over time. Maximise machine learning to add feedback functionality to insurance bots. That way, you’ll better understand client needs, improve services and deliver a highly personalised experience.
Don’t rush in!
To make AI a success, follow a few golden rules. First of all, involve the right people in the company including budget holders, the IT department and everyday users from the very beginning. Set and manage expectations by educating your organisation about what AI can and cannot do. Be realistic when sharing timeframes for results – machine-learning takes time to perfect! Also remember that AI tools thrive on good data so build a bank of reliable data that is up-to-date and above all, relevant. Finally, test AI in a real-world environment while maintaining business as usual.
