AI & machine learning will transform the customer experience

This article was originally posted on the Insurance Edge.

The insurance industry is undergoing a digital transformation, with technologies such as artificial intelligence (AI) and machine learning (ML) providing companies with the ability to automate, personalize, and even accelerate customer growth. Insurers that embrace these digital tools are able to process larger amounts of data – the lifeblood of insurance – at extraordinary rates, while giving their customers a more streamlined, personalized experience.

The latest research shows that at least 2.5 quintillion bytes of data is produced every day – much of it generated by smartphones, fitness trackers, social media, and the other digitally connected devices that have become part of our daily lives. Combined, these data sources produce the type of information insurance companies need to improve their customer-facing business processes (e.g., details about our habits, our health, and our decision making). And the amount of available data is only going to grow in the future, with predictions showing that more than 1 trillion connected devices will be in use by 2025.

What does this mean for the industry? Insurance companies will have more accurate information regarding the demographics, medical history, and socioeconomic status of their customers. They will have a better understanding of how to offer protection tailored to their customers’ specific needs. And they will be able to develop the products, pricing, and real-time service delivery solutions that their customers want.

Insurance companies increasingly need a unified view of each policyholder, with relevant data available to the various insurance ecosystem stakeholders. However, navigating through so much data, from so many sources, is incredibly complex, making it difficult (and time consuming) to efficiently fulfill even basic activities, e.g., informing underwriters, handling claims, etc.

By leveraging AI and ML to analyze data, automate routine tasks, and assist human decision-making along the entire insurance value chain, providers can harness the power of the data to get a personalized, 360-degree view of their customers. In addition, these technologies can help streamline interactions with customers by offering a well-rounded, digitized experience. This is increasingly important as a growing number of customers prefer more self service and less human interaction.

With a nearly infinite amount of customer data available, recognizing which information will be most useful for identifying customer needs can be difficult. By using predictive analytics and modeling tools, insurance companies can supplement their internal data (e.g., customer claim details, transaction histories, and particulars such as income, age, and occupation) with information from other, external channels, such as social media and online purchase histories.

Machine learning algorithms can be used to analyze this data, looking for patterns and market trends. Then, predictive analysis models can use this information to provide insights into customer behavior that can help improve customer retention rates over time – leading to greater risk analysis, fraud detections, and message targeting.

Policy holders look for a considerable number of services from their insurance providers, including having access to clear policy details, being able to easily file claims, and receiving fast, informative responses from their agents. It used to be enough for an insurance company to offer a user-friendly website. However, that is no longer the case.

Many customers – especially younger customers – expect a digital-first experience when engaging with any company. For an insurance company to successfully attract, engage with, and retain customers, they now need to offer an omni-channel customer experience that allows policy holders to seamlessly connect to their channels of choice.

This means that every insurance company should have an easy-to-navigate platform that provides a centralized view of customer details including quick links to key documents and forms, and a mobile app that allows customers to collect and update their data, as well as provide feedback or file complaints.

The latest insurtech platforms also leverage AI to power virtual assistants that can provide support outside of typical working hours. They supplement the interaction between policyholders and customer service representatives in a variety of ways, directing customers to the right agent or providing them with the information they need at their fingertips.

Every time a customer interacts with a virtual assistant, it stores and processes that data. As a result, it “learns” and provides customers with better, faster, and more relevant answers to their questions – whenever they need them, no matter where they are located.

AI and ML have incredible potential across the entire insurance value chain, from marketing to underwriting to claims management. As more companies rethink how to approach their data – with a focus on ways to increase customer acquisition and retention – the role of these technologies will continue to grow in leaps and bounds.

By leveraging AI and ML to collate, analyze, and automate data from myriad touchpoints, insurance providers can create a powerful, comprehensive, 360-degree customer view that allows them to track all interactions a customer has with the business and create personalized experiences based on those insights. The result: better customer journeys and experiences, as well as greater productivity for insurance companies themselves.