Claims Transformation in Insurance

In the post-pandemic economy, the cost of insurance claims has risen exponentially. Several macro factors, including inflation, climate change, higher repair or replacement costs, and changes in customer expectations, are driving these costs. In this environment, the pressure to control the cost of claims is intense, and insurers are faced with a difficult choice between exiting the market or reducing the cost of servicing claims.

Fortunately, the insurance industry also has an emerging set of technology tools well positioned to target the cost of claims. Innovations such as AI and cloud computing, combined with richer data sets, low code/no code platforms, and the rapidly evolving insure tech ecosystem, give insurers unique opportunities to reduce the cost and time required to service claims while improving the customer experience. Brilliant “quick win” projects to drive productivity and support critical business and operational needs to be prioritized alongside more significant re-platforming initiatives. This “perform while transforming” journey will combine a comprehensive multiyear strategy with the agile, incremental delivery of capabilities.

The Challenges of Multi-year Claims Transformation Programs

Multi-year claims transformation and cloud adoption journeys are prone to cost and schedule overruns. Insurers attempting to transition away from legacy platforms rife with complex integration architectures, fragmented business processes, and manual tasks encounter numerous blockers, including:

1. Emerging technology solutions are only sometimes mature enough to address the complex regulatory landscape and the unique needs of insurance claims.
2. Firms are also hesitant to fully decommission old systems of record because they need the information from those systems to address legal and regulatory asks for years to come.
3. Most firms are products of mergers and consolidation and have multiple claims platforms tightly integrated with other core systems. These claims platforms are a mix of home-grown solutions and vendor platforms, each offering unique challenges.
4. Vendor platforms often face complex upgrade paths due to customizations and may need a complete re-implementation.
5. Home-grown systems are frequently poorly documented and were built using software platforms that are at end-of-life or unsupported.

Given the complexities of the task, it’s important to approach claims transformation with a strategic mindset. Insurers should not expect to quickly merge all their systems of record into a single unified cloud environment. Instead, a careful orchestration of the transformation journey is needed. By adopting a modular plug-and-play architecture, insurers can deliver numerous micro-transformations in an agile, iterative fashion parallel to the long-term transformation. This dual strategy not only ensures a steady return on investment but also provides insurers with the benefits of multiple micro-transformations in increments of 3 to 6 months, even as they wait for the more extensive transformation to take effect in 1-2 years.

These micro-transformations can be designed to deliver both customer experience improvements and productivity gains. Adding a claims tracker to a customer-facing application, for example, provides customers with real-time updates on their claim status and reduces the number of manual phone calls required to service the claim. Implementation is far less complicated than a core upgrade, and the only requirement is to source the correct data from the underlying platforms and ensure that it is in sync with what the claims service agents access while answering calls. The same goes for payments: Enabling payment through a digital app in near-real time rather than by mailed check is a relatively standard technology enablement yet yields a significant customer experience uplift that will drive customer retention.

What Incremental Transformation Looks Like

As a part of this program, we prioritized the digital transformation of the First Notice of Loss (FNOL) process through web portals and mobile channels across four different brands. We brought claims tracking to settlement with digitally re-imagined claims journeys. Simultaneously, we created an activity-based cost model for servicing claims. This model, which assigns costs to activities based on their use of resources, helps improve the baselining of unit costs and identifies sources of leakage to drive efficiency.

Within the 1st year of the transformation program, we delivered dynamic workflows that drive effective triaging, next-best actions, faster settlement, and optimized fulfillment covering 16 claims journeys across FNOL; assessment; settlement for simple, hybrid, and complex claims; vulnerable customers; and surge events.

The related micro-transformations included tactical claim routing solutions to triage claims and push to settlement early, RPA to automate manual steps, interactive chatbots with intelligent search capabilities for customer conversations, and real-time automated scanning of submissions for fraud using machine learning. To further drive productivity, we implemented an Intelligent Claims Workbench with a persona-based claims workflow manager and smart analytics that puts all the correct information in the right person’s hands at the right time.

The value unlocked through our data-driven and outcome-based approach included:

• 70% adoption of the digital self-service channels for submissions, tracking, and answering questions, resulting in improved NPS and customer experience and reduced customer churn
• 80% digital straight-through settlement of straightforward claims with 100% automated scans for frauds
• 50% productivity gains in complex claims processing through automation and analytics enablement of claims operations

We also built a strong technology foundation by creating the base instance of a cloud-native data hub for claims, with modern data architecture and processes designed with next-generation data control and analytics capabilities.

In addition, at a leading insurer in the US, we successfully delivered a multi-year claims transformation program involving the roll-out of a modern claims platform across multiple business lines. Our modular and flexible approach enabled the team to integrate an acquired fintech platform for usage-based insurance into the new claims platform in two months. We added incremental capabilities like real-time capture of claims events and a messaging solution that distributes information to other platforms (e.g., underwriting and pricing) while integrating claims capabilities for the newly acquired product portfolio.

The Importance of the Data Hub

Insurers are increasingly harnessing a data-driven transformation strategy for claims. This approach, which requires investments in building on their underlying data and analytics capabilities, can promote faster resolution, reduced leakage, and improved customer satisfaction scores while migrating to cloud-based platforms. By leveraging data and analytics, insurers can gain deeper insights into their claims processes, identify areas for improvement, and make more informed decisions, ultimately leading to better customer experiences and operational efficiency.

A cloud-native data hub with strict access controls and data protection can be a game-changer for claims transformation. For regulatory reasons previously discussed, insurers cannot quickly lift and shift their data assets to the public cloud. A data hub allows for a more incremental approach. Isolated datasets can be catalogued and pulled into a data hub to drive specific micro-transformations. As these efforts scale, the amount of data subject to best-in-class data quality and data governance grows, and the resulting capabilities of the data hub become more robust.

A robust data hub also democratizes data, making trusted data available across the enterprise, which can lead to previously unrealized capabilities. New applications can be built specifically to plug into the data hub. Clear access and control protocols can also prevent this data from being misused — and the data hub’s data governance and access control often make it more secure than the legacy system that feeds it data. A multi-tenant architecture, for example, can separate the data from the insurer’s claims from the claims of other insurers where it acts as a third-party administrator (TPA). Similarly, the data hub can be segregated into domains with specific purposes for staging, transforming, testing, and providing data to the claims applications.

Data hubs can also be leveraged to reduce the complexity of legacy applications by removing reporting and analysis workloads from the core systems. The reduced complexity speeds up the modernization of the claims platforms as these reporting requirements were often built as “mods” or customizations to the vendor product. These are difficult to upgrade and are usually not supported in cloud-native/SaaS versions of the vendor platforms.

At a leading workers' benefit provider in North America, we created an innovative solution using adaptive data mapping techniques to harmonize the data required for reporting across legacy on-prem and the cloud-native claims platform. This solution enabled seamless upgrades of the claims platform in phases without disrupting the critical regulatory and financial reporting needs.

With one of our other clients, we leveraged the data hub to bring together multiple sources of customer feedback and case management information and train a Generative AI sentiment analysis solution to assist the agents in proactively identifying best-fit solution pathways. This allows for swift action assignment to the proper parties, ensuring prompt resolution of customer issues.

We are also leveraging the data hubs to train Generative AI solutions to create synthetic test data, providing excellent coverage of the test scenarios while avoiding the risks of using actual customer data.

In the long run, these data hubs may evolve to deliver powerful training data for customer-facing AI solutions, particularly if regulations evolve to provide clarity on acceptable AI usage and if safeguards are built in to protect customer interests.

Insurers will deploy automated yet personalized messaging targeted by matching products to specific customer segments. Later, GenAI can be looped into social media strategy, further refining the approach to B2C customer segmentation. Quick AI-based fraud checks, such as examining uploaded photographs for staged accidents/damages, will enable automated partial claim payments in a matter of minutes with lower risks and increased customer satisfaction.

Incremental Change: The Claims Transformation Imperative

The claims side of the business rarely takes center stage in the insurance sector. Leaders charged with claims transformation often find themselves tasked with ambitious goals yet provided with limited budgets.

Given the realities facing insurance companies, the optimal claims transformation strategy will create an intentional architecture for the modernized claims platform and focus on delivering incremental wins early on. These micro-transformations will build momentum for driving the adoption of the claims transformation program across the enterprise. For many insurers, full-scale cloud reinvention will take a few years. But that shouldn’t entail a pause in progress. By taking an agile approach that welcomes quick wins wherever the claims process is most ripe for transformation, insurers can rapidly improve their claims ecosystem to impress customers, reduce costs, and power forward-thinking innovation.

About the Authors

Pankaj Gupta
Global Consulting Head, Capital Markets and Insurance

Pankaj brings three decades of experience across business transformation, corporate finance, and boardroom advisory primarily within BFSI. He has a proven track record of working with clients to shape and deliver transformation programs to enhance corporate topline, deliver cost and operating efficiencies, manage risk and compliance themes, and set up sustainable innovation models.

Saptarshi Mukherjee (Rishi)
US Region Consulting Head, Insurance

Saptarshi has more than 25 years of consulting advisory experience in driving complex transformation initiatives with Fortune 500 clients globally. He is a technology enthusiast, keen on adapting the emerging trends and innovations into real-world business applications to drive competitive differentiation and productivity gains.