Since the COVID-19 pandemic, insurance claims costs have risen dramatically. Many factors, including the global pandemic, climate change, inflation, and the increase in the price of repairs or replacement items, are driving the cost increase. While there is enormous pressure to reduce insurance claims costs, insurers face a difficult challenge: get out of the industry now or find ways to reduce the costs of tackling claims.
According to Congressional testimony from the American Property Casualty Insurance Association last year, “insurers absorbed the worst underwriting losses in over a decade, contributing to a contraction of more than $73 billion in insurers’ capital. In the first half of 2023, insurers spent 104.3 cents in claims and expenses for 100 cents of premium collected—and that’s before the Maui wildfire and Hurricane Idalia catastrophes this fall.” Similarly, the average family health insurance premium has increased 22% since 2018 and 47% since 2013, according to KFF.
The good news is there are numerous technologies to help insurers reduce claims costs. The current focus is AI and cloud computing, offering tangible options that can dramatically impact. For insurers, leveraging the power of AI and cloud computing and combining them with rich data sets and low-code/no-code platforms provides a roadmap to reduce costs and the time it takes to service claims. The hidden bonus is these technologies reduce costs and significantly improve the customer experience, bringing relief and optimism to the industry.
Utilizing these technologies to develop and deploy a comprehensive multiyear strategy with agile, incremental capability delivery—what we call the “perform while transforming” journey—is key.
Be Aware of Cost Overruns
However, embarking on a claims transformation and cloud adoption voyage can often lead to cost and schedule overruns. Migrating from legacy platforms to newer solutions is fraught with issues, including tackling complex business processes, manual, time-consuming tasks and challenging integration issues. In addition, shuttering legacy systems, saving valuable records and coming up with ways to address integration issues across multiple claims platforms can be taxing. Doing any or all of these can impact current costs, although those costs are reduced over time.
Other internal processes that raise costs include the increased complexity of new platforms, which often run parallel to existing platforms, ongoing testing of new platforms and the shuttering of legacy systems, and the loss of institutional knowledge that occurs when employees retire or leave their jobs.
Transformation: Good and Bad
Digital transformation has been a buzzword for many years, and with good reason. The potential improvements and savings associated with modernizing entire systems are tremendous. Yet, shifting to cloud-based technologies involves transitioning to license/cost models based on usage or volume.
For large insurers, these newer consumption-based cost models can lead to an uptick in operating costs. The good news is that additional costs can be offset through increased automation and improved customer experience and quality of service. It’s also quite common for large-scale digital transformations to run into delays, hindering growth.
Understanding the potential issues is critical when heading down this path. Insurers must take a strategic approach to claims transformation to ensure short- and long-term success. Experience shows that utilizing a modular plug-and-play architecture simplifies the transition. One strategy is to map a series of micro-transformations in three- to six-month increments to complete the transformation in one to two years. Taking a “bite-sized approach” to transformation leads to better results in both productivity gains and creating a better customer experience. This strategic approach should reassure insurers and instill confidence in the transformation process.
In the short term, one key to improving customer experience is sourcing the correct data across platforms to ensure it matches what claims servicing agents see when fielding customer calls versus self-service portals or documents received via physical channels. The same is true for claim payouts—receiving payments in digital apps in real-time instead of waiting for days for the checks to arrive by mail leads to a better customer experience and improved customer retention.
Build a Better Data Hub
The path of claims transformation begins with a journey toward creating a solid data hub that democratizes valuable data. All departments benefit from using a single data source throughout the company. However, it’s essential to establish access and control guidelines to ensure the data generates positive results. IT leaders must design and implement data governance and access controls.
A key strategy is to adopt a data Lakehouse architecture to create a single scalable platform deployed on lower-cost cloud-based storage that can effectively manage the growing volumes of raw unstructured data used for machine learning and the structured data for claims reporting and analytics. A single platform approach provides better returns on investments than building a data warehouse for structured data and a data lake for raw unstructured data.
We are seeing an increased adoption of new data sources (fire/smoke detectors, vehicle telematics, videos, images) for claims and risk management. The unstructured data can also be used to train machine learning models with wide-ranging applications, including fraud detection, automated pay-outs, reducing risks and improving the customer experience and faster turn-around times to process claims.
Over time, data hubs can deliver impactful training data for customer-facing AI solutions.
In addition to training machine learning solutions, data hubs coupled with GenAI synthetic data generators can eliminate the need to use customer data for testing. Synthetic test data will improve the test coverage and reduce defect leakage while eliminating the data security risks of using customer data in non-production environments.
Another key benefit of investing in a data hub is that IT departments don’t have to tackle the data access challenges of complex legacy applications while building new applications faster using low-code/no-code tools on top of the data hub.
Keys to Success
While claims aren’t the most exciting part of the insurance sector, and typically, claims don’t get the lion’s share of budgets, claims are a critical part of the overall success of any insurer.
In today’s highly competitive insurance industry, company leaders focusing on designing and implementing a claims transformation increase their odds of financial success. Modernizing claims platforms, designed with incremental improvements to highlight benefits to stakeholders, will put insurers on a better path.
While large-scale cloud reinvention and digital transformation may take a few years, this agile approach significantly improves the claims ecosystem. It reduces costs, spurs innovation, streamlines operations and leads to superior customer experience.
Mukherjee is the U.S. region Consulting Head, Insurance, for Wipro. He has more than 25 years of consulting advisory experience driving complex transformation initiatives with Fortune 500 clients globally.
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