Technology
How data and AI can help the insurance industry in the post-pandemic recovery
Global Banking & Finance Review®
Company
By Sachin Bagla, Associate Vice President, Head of Business Intelligence, Big Data and Analytics, Europe, Infosys
The insurance industry has emerged as a critical pillar of the global economy. For context, European insurers pay out claims worth approximately €1 trillion every year and have invested more than €10.4 trillion in the economy. The COVID-19 pandemic has had an unprecedented impact on the insurance industry. According to estimates by Insurance Europe, the global COVID-19-induced insurance losses range between €41and 82 billion.
The pandemic created a major shift to remote working for the industry, followed by a massive spike in customer queries, claims, and complaints. Attempts on fraudulent claims were high too. All these led to an uptick in demand for digital-first services. To deliver this demand, the ability of insurance companies to leverage data could very well determine their success.
Let us consider how data and analytics can be leveraged in post-pandemic recovery.
Understanding customer needs to design offerings
For an industry dependent on forecasting risks, the ability to access and analyse trustworthy data is crucial for insurance companies. More so when changes in preferences and behaviours impact the expectations of customers. As more businesses get uberized, insurance companies are looking to share, analyse data and use AI to draw insights and intelligence to develop new digital products and services and address consumers’ needs.
Here is an example of data-driven product innovation – Pricing an insurance product is challenging because companies typically do not know how much it will cost them at the time of selling. Traditionally, pricing is based on the details of the person being insured. Allstate, the US-based insurance company, wanted to accurately measure the risk profile of a driver. The company offered discounts to people who were willing to share data collected through telemetry devices provided by Allstate. This gave the insurer a unique competitive advantage to identify and quantify risky driving and thereby helping them identify risk premiums in a more granular way.
Building a Customer Intelligence Platform to drive hyper-personalization
In a digital-first world where customers prefer contactless engagement, customer experience becomes significant. A recent Infosys white paper revealed that 55% of the insurance CEOs surveyed indicated “optimizing customer experience and satisfaction” as their top priority for the second half of 2021.
A “Customer Intelligence Platform” enables insights via systems of engagement to provide recommendations to customers, suggest appropriate marketing messages, and prescribe the next best actions relevant to the customer. Together, these provide rich customer experiences that helps improve conversion, loyalty, and revenue in the long run.
Automating processes and decision-making using AI
Insurance companies can use AI effectively to solve many of their challenges, such as creating risk profiles or expediting insurance purchases. Insurers can underwrite faster with more accuracy through automation and deep learning models. They can process claims accurately with advanced algorithms.
Let’s look at claims processing as an example. When claiming for a car accident, a car owner can notify the insurance company about the incident via an assistant app on his phone. The incident details can be recorded via voice or text and images of the damage uploaded via the app. The damage is assessed, and the claim is analysed for fraud using AI, before a draft estimate is created. The automation of these steps helps the claims management team to be more efficient, accurate and improve the customer experience. The app can also assist the driver find the nearest repair shops or notify the breakdown cover provider for recovery assistance.
Addressing the people challenge
People play a vital role in the functioning of the insurance sector, ranging from actuarial functions to product design, marketing, and customer service to claims and fraud adjustors. The improved access to insurance and a manifold increase in queries and claims in recent months have resulted in additional workload for insurance employees.
The lack of physical interactions due to social distancing has impaired effective communication. Hence, insurance companies are investing in technology to facilitate better remote communication. From digital tools for conferencing to training employees in data privacy, insurers are likely to double down on this soon. Democratizing data across the human resource value chain and the customers’ buying journey allows for better servicing of customer requests and well-informed decision-making, both by customers and employees.
In summary, as insurance companies address the challenges and opportunities present in the ever-evolving new normal post-pandemic, they want to divert their capital and talent to initiatives that can help them become data driven and become more resilient. Consequently, digitization has become a priority. The future will see the industry using more AI, and data analytics helping improve customer experiences thru hyper personalization, running more efficient operations as well as building consumer-influenced products and offerings.
AUTHOR:
Sachin Bagla, Associate Vice President, Head of Business Intelligence, Big Data and Analytics, Europe, Infosys
Sachin Bagla leads the data and analytics practice in Europe for Infosys where he is responsible for helping organisations deliver business value from their data-driven digital transformation initiatives.
Sachin specializes in leveraging cloud analytics and AI capabilities effectively and at scale for enterprises with special focus on data quality management.
Data analytics involves examining data sets to draw conclusions about the information they contain. It helps businesses make informed decisions based on trends and patterns.
AI in finance refers to the use of artificial intelligence technologies to automate processes, analyze data, and improve decision-making in financial services.
Customer experience encompasses all interactions a customer has with a company, including service quality, product satisfaction, and overall engagement.
A customer intelligence platform is a system that collects and analyzes customer data to provide insights for personalized marketing and improved customer engagement.
Automation in insurance refers to the use of technology to streamline processes such as claims handling and underwriting, improving efficiency and accuracy.
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