Digital Insurance: How Data Technology is Transforming the Insurance Industry
Also known as insurtech, digital insurance uses big data technologies to transform the way insurers underwrite policies, manage risk, and provide customer support. By taking a data-driven approach, insurers can create innovative and personalized insurance products and services to meet the evolving needs of customers. In this article, we’ll explore what digital insurance is, explain how it’s impacting the traditional insurance market, and share examples of how data technology is shaping the future of insurance.
What Is Digital Insurance?
Digital insurance is the use of data-driven technologies to provide insurance products and services. Machine learning (ML), artificial intelligence (AI), and advanced data analytics are creating opportunities to more accurately price risk, incentivize risk reduction, and develop innovative insurance products that better meet the needs of customers in an increasingly digital world. The same technologies are also being used to streamline and automate underwriting, eliminating costly and time-consuming manual processes utilizing open, connected software platforms. Through the use of mobile apps, websites, and other digital platforms, digital insurance embraces a customer-centric approach to provide a more convenient, accessible way to purchase insurance, manage policies, and process claims.
Digital Insurance Benefits
As digital insurance transforms the way products and services are delivered, insurers benefit in a variety of ways. Here are six ways data technologies are being used in the insurance industry.
Cost reduction and increased profitability
Insurers that invest in a more data-driven digital insurance model typically realize significant financial gains. More accurately predicting risk, automating underwriting and claims processing, and creating more highly targeted marketing campaigns can reduce costs and boost profitability.
Improved employee productivity
Automation saves time, allowing companies to leverage their human capital more effectively. With fewer manual processes involved in policy underwriting and claims processing, staff can be reallocated to higher-value projects such as developing systems that expand policy self-service options.
Claim settlement cycle time is crucial from both a customer experience and loss control standpoint. Digital technologies can reduce the average amount of time required to settle and close claims.
Better customer experience
Digital insurance technologies provide insurers with new opportunities to deliver a superior customer experience. Examples include the use of AI-enabled chatbots to provide quick, personalized support, near-instant price quotes, and advanced self-service options including purchasing a new policy or modifying coverage on an existing one.
More accurate fraud detection and response
Predictive analytics allow insurers to more easily spot fraudulent policy applications and claims. Data technologies can flag applications for manual review that may contain misleading information or claims that may be inflated or fabricated.
Product development insights
Insurers that have invested in the infrastructure required to work with data at scale can offer innovative new products that meet the needs of today’s digital consumers. Digital insurance products take into account individualized usage and behavioral data to offer customers more attractive rates for risk-reducing behaviors.
Digital Insurance Examples
When digital technologies meet real-world problems, everyone benefits. Here are five use cases where technology is modernizing insurance practices.
Some traditional insurance policies leave gaps in coverage. On-demand insurance fills those gaps, providing coverage for specific events such as travel or recreation. Examples of this type of insurance include international rental car coverage and short-term policies that protect expensive equipment such as sports gear, computers, or cameras for a set period.
Microinsurance claims assessment
Microinsurance provides loss protection for low-income customers, often located in emerging economies, such as crop, livestock, or property casualty insurance. Manually assessing these claims in difficult-to-reach areas isn’t feasible. To compensate, insurers analyze various types of data, including weather data, to predict the likelihood and severity of the claimed loss.
For insurance products such as life and auto, individual customers can present very different risk profiles. Using health data gathered from wearable devices or car usage habits gathered from telemetric devices, insurers can offer customized pricing based on personalized risk profiles.
Improved customer self-service options
Today’s time-strapped consumers value the ability to complete insurance-related tasks quickly and conveniently. Digital technologies can increase self-service options such as signing up for a new policy, submitting a claim, and managing existing policies
Future use of remote sensors (IoT) for assessing health and property risks
Remote sensors—such as wearable devices, and in-home IoT devices such as smart leak detectors and video doorbells—can help insurers refine their general insurance models. Data from these technologies make it possible to provide more competitive life insurance rates for individuals who have favorable health metrics, and lower property insurance rates for families who’ve invested in a network of smart sensors that actively monitor risks such as water damage and theft.
Capabilities That Help Organizations Realize the Promise of Digital Insurance
To enjoy the benefits offered by digital insurance, insurers must have the right infrastructure and technology in place. Here are the most important requirements for implementing an effective digital insurance initiative.
Enterprise data platform
Insurers have access to enormous quantities of internal data. But that data is often siloed, locked away in a patchwork of systems, applications, and storage solutions. A centralized, cloud data platform brings these disparate sources together to provide clear visibility across the entire data ecosystem. With all relevant data accessible, organizations can avoid data blind spots.
Integrated access to third-party data sets
Augmenting internal data with third-party data adds additional context, allowing companies to more accurately assess risk, create higher-performing marketing campaigns, and improve the quality of their customer service. Third-party data purchased via a data marketplace may include weather, demographic, and media data.
Cross-organizational data collaboration
Cross-organizational data collaboration opens up a variety of opportunities for the insurance industry. When organizations share relevant data using a framework that supports robust data governance standards, all parties benefit. For example, an insurer and reinsurer may agree to exchange risk data. An enterprise data platform enables this type of data collaboration, making it possible to achieve privacy-preserving collaboration with targeted discovery, revocable access, and use case-level auditing.
ML-augmented business workflows
Machine learning allows insurers to sift through massive amounts of data quickly, making connections that would be virtually impossible for a human analyst to spot. This technology has applications for improving a variety of business processes, including pricing and risk selection, underwriting, claims management, sales/distribution, and customer experience.
Snowflake for Financial Services
With the power of the Financial Services Data Cloud, insurers are leveraging data technology to better assess risk, optimize pricing and policies, and launch new products with data science and ML-enabled automation. Snowflake enables insurers to automate routine tasks in underwriting workflows, monitor portfolios, and provide teams with easy access to additional data sources. With a single data platform for scaling multiple workloads, the insurance industry is well positioned for future innovation.