Data Can Make Digital Transformation a Reality for P&C Insurers
COVID-19, as one insurance industry executive puts it, is "the biggest insured loss event in history." The estimated 2020 underwriting losses covered by the insurance sector are approximately $107 billion as a result of this global pandemic. By the end of the year, the industry is expected to suffer a $96 billion decline in portfolio investments.
In this complex and uncertain post-COVID environment, building a competitive advantage is a strategic imperative. For property and casualty (P&C) insurers, this comes down to two key factors: speeding up digital initiatives designed to improve customer experience and fueling profitable growth through pricing innovation.
Data is critical for powering both of these efforts. Cutting edge technologies such as artificial intelligence and machine learning will also be vital as they transform data into actionable insight.
Accelerating Digitization to Transform Customer Experience
From Amazon to Netflix, today’s top businesses have created digital experiences that consumers now expect from every company. In P&C insurance, customers want personalized recommendations, a seamless and simple claims management process, and real-time responses. In fact, a study from Deloitte revealed that prospects are 20% more likely to purchase a policy when the underwriting and application processes are completed in real time using built in automation and workflows as well as tools, such as eSignatures.
Delivering these offerings require robust data capabilities. Fast access to compliant, lightweight data allows development teams to update core insurance software such as Guidewire faster and more often, accelerate adjudication and claims processing, enable faster risk analysis and reporting, and expand product offerings through an insurtech ecosystem.
Leveraging Modern Data Operations to Deliver Pricing Innovation
Pricing is another focus area for insurers—and data has a central role to play here, too. P&C insurers must improve the accuracy of pricing in order to compete and keep hard-earned customers. When pricing is too high or too low and doesn’t align with market conditions, the result is lost revenue and narrowing margins.
AI-based modeling enables the development of risk and pricing models that drive dynamic pricing. Data science teams need access to data from any point in time in history to train and validate AI models in order to generate competitive, dynamic price quotes without risking their profits.
“Sophisticated insurance carriers evaluate more than 30 new external data sources and then select two to four sources each year that they use to develop new features to embed in their pricing and rating models,” McKinsey found.
Sourcing and wrangling data (think: petabytes) spread across disparate systems and locations is only the beginning. A data platform like Delphix combines data compliance with on-demand data delivery to efficiently bring together the most critical data from all enterprise applications and dynamically move the data to any location, on-premises or across multiple clouds.
Adding agility to a traditionally slow process, AI can help insurance companies better predict trends and manage risk to rapidly respond to the market changes and pressures.
Insuring During a Pandemic Is Hard—But Not Impossible
Analysts predict that 500 million new applications will be created by 2023. Companies need to speed up, simplify, and automate their data operations to ensure their initiative is the fastest out to market. For insurance providers, it’s about automating as much as possible for a faster customer response. Real-time access and delivery of pricing data to applications and analytics tools ensures a pricing competitive advantage. By accelerating data-driven innovation, insurers can gain a competitive advantage—even in the midst of a pandemic.