Article

Move generative AI to the front office

Insurers should leverage generative AI to reimagine the entire customer relationship.

Simon Axon
Simon Axon
2 février 2024 3 min de lecture

The coming year promises to be another one of uncertainty and sustained economic headwinds. Meager economic growth plus high interest rates will continue to squeeze both consumers and businesses. In response, many insurers are turning to generative artificial intelligence (AI) implementations.

But to truly embrace the power of generative AI, insurers must move it from the back office to the front lines. Instead of using it to automate existing processes, insurers should leverage it to reimagine the entire customer relationship. What’s more, if insurers don’t take this step, hundreds of tech startups are jostling to take their customers.

Reimagining customer service

But what does that reimagining look like, and how do insurers embrace trusted AI-powered innovation to make the transformation? Let’s use a real-world example to illustrate how insurance works now, and how generative AI could transform it.

This summer, one of my team members planned a vacation in Italy, flying into one airport, touring several cities, and leaving from a second airport. On landing in Italy, they found their departure airport had closed for several weeks, having experienced a sudden, devastating fire. My colleague sadly spent most of their vacation time rearranging flights, hotels, and logistics in response to this disruption, at the cost of time and money.

Of course, they had travel insurance, and dutifully informed the insurer as soon as the situation arose. They kept receipts and all the documents needed to make a claim but could only do this once they returned home. So, the holiday was blighted not only by the struggle to rearrange, rebook, and replan, but by the additional financial outlay and uncertainty.

Back home, the claim was made and paid quickly, no doubt with some clever automation in the back office assisting speedy assessment and decision-making. But let’s imagine how the customer experience could look with generative AI working in the front office.

Your AI-powered travel app

On landing in Palermo, the AI-powered travel insurance app on your phone informs you of a fire at the Catania airport—your chosen departure point in two weeks. It provides an assessment that the airport will not be open and that your flight will be cancelled. Based on your policy, it preapproves a claim for disruption to your vacation.

So far, so good. But what if it then offered to provide a list of alternative routes, hotels, and itineraries, culminating in an alternative return flight from Palermo instead? And, once you approve the new options, it contacts all the necessary vendors to cancel and rebook the new holiday, calculating lost deposits, refunds, and additional expenditures and assessing against the insurance claim? It’s a win-win. You get to enjoy every day of your vacation while the AI takes care of the administration. The insurance company eliminates potential fraud and pays out exactly what’s required (probably with better rates secured), deepening its relationship with you as a customer. An unwanted transaction has become a value-driving relationship.

Data foundations

This may seem like a fantasy, but the building blocks are already in place. Generative AI will certainly have the capability to learn natural language interactions to facilitate this type of service in the very near future. The challenge for insurers is data. High-quality, trusted data from a wide range of sources is the essential fuel for generative AI.

Although they are used to dealing with large amounts of granular data both for marketing and risk pricing, until now, insurers have relied almost exclusively on internal data sources. The providence, governance, and quality of this data is trusted and verifiable. But, to move into the front office and deliver radical innovation, generative AI must have access to external sources—from news feeds to global positioning system (GPS) data, from hotel listings to flight booking systems—in addition to internal customer and policy data.

Trusted AI depends on the level to which an organization controls and understands the data it consumes. Insurers need connected data platforms that can ingest and manage external and internal data sources while applying governance and data quality rules across them all.

Teradata integrates external data into connected data platforms while enforcing governance and data quality standards that deliver trusted AI. With the most resource-efficient and scalable cloud platform, it also accelerates data preparation so multiple external sources can be prepared—ready to for generative AI to use.

Trusted AI-powered innovation and transformation are the customer-centric tools that enhance personalization and service. It all starts with data. Contact us today to learn more about how Teradata enables insurance innovation with generative AI.  

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À propos de Simon Axon

Simon Axon leads the Financial Services Industry Strategy & Business Value Engineering practices across EMEA and APJ. His role is to help our customers drive more commercial value from their data by understanding the impact of integrated data and advanced analytics. Prior to his current role, Simon led the Data Science, Business Analysis, and Industry Consultancy practices in the UK and Ireland, applying his diverse experience across multiple industries to understand customers' needs and identify opportunities to leverage data and analytics to achieve high-impact business outcomes. Before joining Teradata in 2015, Simon worked for Sainsbury's and CACI Limited.

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