The Imperative to Transform: Why Insurance Firms Must Upgrade Their Legacy Systems

The insurance industry has relied on legacy systems for decades to handle critical functions like underwriting, claims, billing, and more. However, these outdated platforms and infrastructure now pose a significant vulnerability and hinder insurers’ ability to compete in today’s digital economy. Here’s a comprehensive look at why transformation is imperative, the primary obstacles to upgrading, and how leaders can approach legacy system modernization the right way.

The Problem with Legacy Systems

Legacy systems refers to the outdated computing infrastructure and software programs that companies have utilized since the mainframe and client-server eras beginning in the 1960s. They have a reputation for being notoriously difficult and expensive to maintain, insecure, and incapable of meeting modern demands. Unfortunately, these longstanding downsides now make legacy systems wholly unviable in the digital age, which leads to the need to carry out insurance legacy system transformation to improve business.

Security and Compliance Risks

Older programming languages and databases used in legacy systems are more vulnerable to cyber threats and lack robust access controls. Their security holes put insurers at major risk of data breaches, hacking attacks, and failing compliance audits—which can lead to hefty regulatory fines. Outdated legacy systems also prevent insurers from leveraging advanced security tools.

Innovation Obstacles

In today’s highly competitive landscape, insurers must rapidly deliver innovations to attract and retain digitally savvy customers. However, rigid legacy systems don’t interface well with new technologies like AI, cloud, IoT, and analytics. Their outdated coding makes integrating innovative features difficult and expensive. Legacy systems thus create huge obstacles to insurers launching new products, enhancing mobile/web capabilities, and harnessing data.

Spiraling Costs and Inefficiency

Insurers have spent billions over decades to customize and update legacy systems just to keep them functional. According to a PWC report, insurers allocate 70% of their IT expenditures towards the upkeep of insurance legacy systems, despite the fact that IT expenses per policy might be 41% higher on legacy platforms.

On top of frequent system failures and stability issues, legacy platforms also impose productivity lags due to clunky user experiences and data silos.

The Digital Drivers Fueling Pressure to Transform Now

Various pivotal industry trends and changes in customer expectations continue accelerating the need for insurers to modernize through legacy system transformation:

Customer-Centric Digital Experiences

Today’s policyholders expect insurers to offer intuitive self-service options, fast claims fulfillment, and personalized engagement via their channel of choice. Meeting these demands requires data integration and real-time analytics that clunky legacy systems severely impede. Only modern solutions can enable insurers to know customers better and serve them seamlessly anytime, anywhere.

Operational Agility

Volatile market conditions force insurers to develop new products frequently, modify pricing models, and reinvent processes. Legacy systems painfully constrain such strategic agility with change request backlogs and long testing cycles. Yet transformation to cloud-native platforms provides the flexibility and speed needed to refine operations continuously.

Data Monetization

Insurers now recognize rich opportunities to generate new revenue streams by monetizing data assets. However, effectively mining, analyzing, packaging, and selling data requires modern architectures that are absent in legacy systems. Transformation is key to capitalizing on the high value of insurers’ vast stores of proprietary data.

Digital Ecosystem Integration

People and businesses expect to seamlessly exchange data digitally to drive efficiency. However rigid legacy systems prevent insurers from integrating with digital ecosystems like electronic health records, telematics, smart sensors and more. Missing out on huge benefits as digital ecosystems expand will erode insurers’ competitiveness.

Core Components of Insurance Legacy Systems

Before examining transformation best practices, it’s important to understand the foundational elements that comprise legacy system environments:

Mainframe Computers

Mainframes were the norm for core insurance functions before cheaper servers emerged. They run very complex customized code, which is still relied upon today. However, their dated terminal interfaces hamper usage.

Legacy Programming Languages

COBOL, FORTRAN, and ASSEMBLER code power most critical applications on legacy systems. While these languages persist for their stability and security, finding and retaining programmers skilled in dated languages is challenging.

Outmoded Databases

Legacy database systems like VSAM, ADABAS, IDMS and IMS served core functions well enough historically. However their hierarchical structure and navigational complexity severely limit their utility for modern data processing needs.

Spaghetti Architecture

“Spaghetti architecture” refers to legacy systems’ tangled maps of interdependent modules and haphazard integration of custom applications over decades. Attempting changes risks breaking things unpredictably.

Best Practices for Modernizing Legacy Insurance Systems

The failures of past legacy modernization initiatives teach insurers they must take a vastly different approach going forward. Here are five best practices for insurance firms to upgrade legacy environments successfully:

Embrace Hybrid Cloud Infrastructure

Rather than migrating legacy systems wholesale, leading insurers now take an incremental “replatforming” approach. This involves continuing to leverage valuable legacy assets while integrating new cloud-native software components for specific functions. The resulting hybrid infrastructure blends the best of old and new.

Architect Loosely Coupled Microservices

Monolithic legacy systems get replaced by modular microservices running on cloud platforms. Microservices integrate with legacy databases and mainframes using APIs. With small domains of responsibility, microservices avoid interdependency risks. This cloud-native approach maximizes agility.

Prioritize High-Impact Use Cases

Insurers should modernize legacy domains that directly advance top-priority goals like improving customer experience, reducing claims cycle times, or launching real-time risk monitoring capabilities. Big bang projects that boil the ocean often go awry.

Embrace Agile Iterations

Given all the complex integrations, insurers must take an iterative approach to transforming legacy systems—not attempting to do too much at once. Using agile sprints to launch incremental upgrades minimizes disruption while delivering continuous improvements.

Maintain Laser Focus on Data

Since data trapped in legacy systems remains so vital, insurers must apply a data-centric lens while modernizing. Whether adopting data lakes, analytics tools, or AI, the top priority should be liberating data from legacy constraints and harnessing it to create enterprise value.

Critical Capabilities for a Modern Technology Foundation

As insurers modernize legacy environments either incrementally or wholesale, leveraging certain next-generation technologies is vital for laying a future-ready digital foundation:

Internet of Things (IoT)

Connecting with real-world sensors via IoT networks generates invaluable behavioral data for usage-based insurance models, automated claims assessment, risk modeling, loss control and more. However, most legacy systems can’t handle huge data volumes from networked physical objects.

Cloud Computing

Cloud scalability, speed, and cost savings enable insurers to rapidly develop the microservices described earlier. Cloud also supports seamless integration of advanced data analytics tools for extracting insights from legacy systems. Serverless computing options further reduce cloud migration risks for specific use cases.

Robotic Process Automation (RPA)

RPA software “bots” simulate human input to have legacy systems automatically execute routine tasks like policy administration, validating claims forms or compliance checks. RPA provides big efficiency gains while modern cloud-native components get built over time.

AI and Advanced Analytics

Artificial intelligence has the potential to optimize nearly everything insurers do—if fueled by enough data. While most legacy systems can’t handle the mass data processing needed for machine learning, AI accelerators and algorithms integrated with the cloud and data lakes can unlock this transformative technology.

API Economy

Legacy systems severely limit insurers’ ability to exchange data with external digital ecosystems seamlessly. However, modern application programming interfaces (APIs) serve as the universal glue for composable connectivity. Well-designed APIs enable legacy integration with partners and digital innovation.

Conclusion

Migrating from rigid legacy systems may seem like an insurmountable modernization hurdle. But embracing cloud, automation, and data-centric incremental change unshackles insurers from legacy constraints. With careful sequencing priorities and architectures, insurers can thoughtfully transform legacy environments to reclaim their digital future. Those taking the right modernization approach position themselves to leverage new technologies for innovation and growth.