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Getting Started with Insurance Modernization

Rachel Nizinski, Appian
March 29, 2024

The benefits of insurance modernization are well established: faster time to market, less churn and happier customers, a more productive workforce with faster business processes, and reduced IT costs through automation and replacement of core systems.

Yes, as the insurance industry continues to increase its reliance on digital technology, insurers who haven’t identified a clear path to harnessing the benefits of modernization will fall behind those who have. 

In brief, insurance leaders looking to succeed with modernization should:

  • Determine their strategy by asking hard questions about their business.

  • Prioritize real-time and advanced analytics to reduce costs and improve efficiency.

  • Leverage AI to improve decision-making for the claims and underwriting process.

[ Read 5 Ways Appian Drives Insurance Modernization. ]

1. You have three main choices for how to modernize IT.

Here are your options for bringing your insurance processes up to speed with the latest technologies: modernize legacy systems, build a new platform in-house, or purchase existing software. Depending on your business goals, you might end up with a mix of these, but you’ll need to define your strategy, map out potential roadblocks, and set expectations for whatever path you take. One of the best ways to achieve this is with a cost-benefit analysis, looking at the value of each approach and how your organization will capture its modernization benefits.

Modernizing a legacy platform.

If you have a legacy system with customized capabilities and valuable features but nearing end of life, refactoring the system is a potential choice for modernization. Insurance platform modernization usually involves one-to-one code migration, which can often be more costly and time consuming than expected and typically tends to miss some of the integration and data architecture modernization that is foundational for getting the full value of digitization.

Building a new platform.

A proprietary platform gives you the ability to develop an architecture that fits your exact business needs and integrates with your existing technology infrastructure. It can provide a strong foundation for your digital transformation strategy by allowing you to expand and customize for different parts of the business as your needs change. It’s a popular approach for insurtechs, who aren’t burdened with existing platforms that need to be modernized. Building a system in-house can have its drawbacks, such as high costs, lengthy development times, and risk of not getting it right.

Buying software.

Standard software has many advantages, such as faster, cheaper implementation, innovative features and tools with best-practice functionality, more regular updates, and the latest compliance and security certifications. It’s a popular approach used by nine of the top 12 P&C insurers In the United States, according to McKinsey. The biggest hurdles to overcome with this approach are often related to inflexibility, both in the mindsets of developers and users and with the limitations of the software itself. 

Partnering with low-code platform providers can be a good middle-ground approach. These provide you with some guardrails for building a flexible solution that can be changed relatively quickly and easily over time.

[ Learn more about a combined approach to modernization in Transforming Insurance: Creating a Best-of-Breed Model by Combining Low-Code and Core Platforms. ]

2. Real-time data access and advanced analytics are key to realizing the benefits of insurance modernization.

Accurate and complete data is the cornerstone of transformative change for your IT modernization. Quality data is key to improving how work gets done and enabling insights that improve the business and lead to more personalized offerings. 

Prioritizing data access and availability in digital modernization efforts is critical to refining risk assessment and underwriting processes. And by integrating advanced analytics tools with core systems, underwriters can better predict the risks associated with insured assets or individuals, ultimately reducing losses and improving overall profitability. 

Data-driven IT modernization also enhances operational efficiency by streamlining workflows, automating tasks, and optimizing resource allocation. This leads to significant cost reductions and improved scalability, allowing insurers to adapt more swiftly to market changes and customer demands. It also enables insurers to provide personalized products and services, elevating the customer experience and fostering greater loyalty in a competitive landscape.

Insurance leaders should consider several key factors when prioritizing data in their modernization efforts:

  • Data quality and governance to ensure accurate insights and compliance.

  • How data initiatives align with strategic goals to maximize impact and ROI.

  • How customer data will be used to better serve customer needs and increase retention. 

  • Data security and compliance measures to protect sensitive information and mitigate risks.

  • Scalability and flexibility of your data infrastructure for future growth and tech advancements.

3. AI has great potential, but it should be implemented strategically.

AI offers many benefits to insurers: faster customer service, increased efficiency, reduced costs. And it touches nearly every aspect of the business from broker and agent operations to underwriting, risk management, claims processing, and beyond. 

Like all technology, AI implementation is not without risk. But there are steps you can take to prevent it. To reduce risk, insurance leaders prioritizing AI in their modernization efforts should:

  • Look for providers with a private AI philosophy. This helps protect your proprietary data and better train models based on your organization’s unique data. 

  • Check trust centers, privacy policies, and compliance certifications before working with a vendor to help you choose an organization that takes data protection seriously.

  • Review AI models regularly for bias and maintain human oversight over model output.

In addition to reducing risk, getting practical value from your implementation requires some strategy. There are three big components to implementation that leaders need to consider. The AI technology itself, which should enable  you to process information quickly, predict outcomes, and generate new information. Data, which enables you to train, refine, and deploy high-quality AI models to generate meaningful insights that drive decisions and innovations. And process, which brings everything together and operationalizes AI within a wider business environment. Insurance companies must combine all three to truly catalyze a competitive advantage.

AI is the next big driver for insurance modernization. Navigate potential pitfalls with The 2024 AI Handbook for Insurance Leaders.