Integrating generative AI to the front office

Simon Axon, EMEA Industry Consulting Director, Teradata

There will undoubtedly be more uncertainty and persistent economic challenges over the coming year. High interest rates and poor economic growth will continue to put pressure on consumers and companies alike. As a result, generative artificial intelligence (GenAI) applications are becoming increasingly popular amongst insurers. A recent survey from EY revealed that 75 percent of companies globally have established GenAI teams. Client experience enhancement was the main factor (69 percent) driving the implementation of these teams in the firms.

Hundreds of tech start-ups are competing for insurance companies’ clients and insurers must consider moving GenAI from the back office to the front lines to use its full potential. Rather than automating current processes, insurers should use it to rethink their client relationships, and how they can provide personalised services to their customers.

Transforming customer service

GenAI has the potential to learn natural language interactions to provide tailored proactive services to customers and therefore, strengthening these relationships. High quality, trusted data from various sources is key for GenAI to offer such services.

Simon Axon

For instance, imagine someone, or a group of people, travelling to another country and on arrival find themselves stuck in the city as the departure airport had to be closed for several weeks due to a fire, for example. This will result in them having to rebook all their flights and hotels and changing their entire schedule to accommodate this unexpected situation. But, since they had travel insurance, they would be able to make a claim with all their receipts once they returned home.

However, the situation would be different with an AI-powered travel insurance app available. By having access to a multitube of external resources, they would have been informed about the fire at their departure airport well in advance notifying them of their cancelled flight. The app would then go on to offer recommendations of alternate hotels, and list out additional departure options for the cancelled flight. Once a new schedule has been decided, the app would automatically contact the respective vendors for the new bookings, calculate the costs and put in the claim. AI would do all the admin work which is ready to go once they have returned from their travels. This also benefits the insurance company as they will be able to eliminate any fraud and only pay out what is necessary.

Building trusted data foundations

Even though implementing this level of proactive service may seem unimaginable, but the foundations are already in place. GenAI will have the capability to learn natural interactions and can facilitate this type of service in the future.

However, the main challenge for insurers is data. As GenAI models need to be trained on and use high-quality, unbiased and trusted data from a wide range of sources, insurers getting data right is crucial. Although insurers deal with large amounts of granular data data-to-day for their risk pricing and marketing efforts, this data usually comes from internal sources.

Yet, for GenAI to be successfully moved to the front office, the tool must be able to access external sources. For the aforementioned example, the GenAI tool will need access to hotel listings, flight booking system and global positioning system (GPS) data. This is in addition to accessing internal customer and policy data.

To ensure that the data is trusted, insurers must have connected data platforms. These systems should be able to also read and manage external and internal data sources, whilst also applying the right amount of government and data quality rules across them all. However, it is important to note that the level of trusted AI depends upon the extent to which a business understands and controls the data it uses. Nevertheless, with the implementation of the EU Artificial Intelligence Act (EU AI Act) into law enables trusted, ethical and transparent uses of this technology as it is being brought into the front office.

For insurance companies to bring trusted AI and GenAI to the front office, they require an interconnected data platform that has the ability to apply governance and data quality guidelines across all internal and external sources. This is the backbone for insurers creating personalised customer service, driven by trusted AI.

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