The promise of GenAI is compelling: smarter automation, real-time decisions, and faster go-to-market – but while the potential is real, there is no off-the-shelf blueprint that fits every organization.

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To effectively leverage modern tools and concepts like GenAI and agent-centric architecture, insurers must have a deep understanding of their current system(s), their strategic goals, and their business landscape. This is mission critical if they are to set the right modernization targets, both from technical and business perspectives.

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Without this foundational clarity, even the most advanced technology is at risk of becoming a costly detour. In this paper, we lay out a three-step approach to clarify and de-risk every stage of your core modernization journey, based on numerous successful client projects.

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Whether you are adjusting your approach or trying to get a project off the ground for the first time, devising a capability plan and process map tailored to your business is vital. By doing this you can avoid the one-size-fits-all trap, and instead focus on the key applications first.

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Step 1. Orientation & Setting a Starting Point

Before initiating the transformation, insurers need a clear understanding of their current state. Situation complexity and the need for change have to be determined across key dimensions:

• ‍Organization and cost transparency: Achieving transparency in both organizational setup (e.g. the retirement schedule for legacy skills) and cost structures, as well as contractual dependencies, is fundamental to any core modernization initiative. It provides the factual baseline required to make informed strategic and design decisions later in the transformation‍
• Architecture and E2E process transparency: Mapping the core application landscape is a critical first step in identifying the right modernization measures for each component. It is crucial to understand the functional business coverage of each application and its core processes, as well as the full extent of the modernization scope to define the future architecture‍
• Business and tech pain points: When instigating change, a clear understanding of the deficiencies and challenges that limit the current setup is essential, both at operational and architectural levels. What is the cost, both for business and IT functions, of running on legacy? This needs to be understood beyond simple TCO – slow time-to-market, long cycles to apply tech innovation, demographic issues, and operational instability must be considered‍
• Data flows and dependencies: It is paramount to understand the degree of coupling between different business capabilities and applications. When it comes to IT, it is essential to avoid rabbit holes, this is done by maintaining information flow and clustering applications to keep complexity manageable. Without this, there is a risk that discussions fall prey to guesswork and facts are overlooked
• ‍Technical and infrastructure stack: Understanding tech stack-specific challenges and dependencies across the frontend, core business applications, integration middleware and database requires a good look below the waterline‍
• ‍GenAI Note: this is a step where modern hyper-transparency, and software-assessment tools for extraction of core information from documentation, speed up the process of architecture discovery significantly. However, we recommend maintaining strong expert involvement and workshop-backed alignment in this phase

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Step 2. Signposting Strategic Goals

Completing a 5+ year modernization journey will always be considered a failure if clear strategic success goals are not set at the start. Modernization must not have today’s business goals in mind, but future targets that will matter at point of go-live. This also means that a core modernization journey is clearly not a purely technical exercise, but a future-oriented business transformation that could shift today’s priorities.

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Consider these three dimensions:

1. ‍Strategic business capability goals: Understanding which key business capabilities are not well supported today and – more importantly – are needed in the future, is a fundamental step in charting a path forward. What do we expect a “modernized” core platform to provide from a business perspective, i.e. what “good looks like” from different business stakeholder’s perspectives, several years from now
2. ‍Business line of commonality: Establishing harmonized and simplified capabilities and processes across business domains, lines of business, and regions ahead of time will ease any core modernization. However, specific processes are often considered differentiators, and thus need careful consideration to retain competitive advantage‍
3. Technical guardrails: Understanding how and where to apply modern technology and architecture paradigms is essential when defining proper tech stacks and blueprints. This demands a technical perspective that is both visionary and grounded in what the insurer can and cannot do throughout the core modernization journey.  Key success factors include the application of cloud-aware technologies, and established patterns for things like integration, data processing, or DevSecOps approaches and tooling

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GenAI Note: while GenAI tools are not (yet) considered a game-changer in this specific work package, understanding the impact that GenAI-backed solutions and agentic architecture may have on the target state of a modernization journey is key to getting it right.  This includes acknowledging the novelty and uncertainty.

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Step 3. Charting a Course

Define the core modernization with intent, grounding it in the assessment and aligning it with business and IT strategy. Choices made now will determine whether the core modernization scales and creates real business impact and benefits once completed.

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Transformation approach: Deciding between a greenfield approach (building new systems from scratch) or a legacy modernization (incrementally upgrading existing systems) is key. Greenfield may offer greater innovation but involves greater disruption, while incremental legacy modernization might be perceived as less risky, it is less transformative. For some domains and (non-core) components, maintaining a not-up-to-date solution and rather re-hosting or transforming it into a modern infrastructure might be fully sufficient. The core, however, frequently requires a much more fundamental revamp.‍

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Implementation approach: The new system can be bought as a market solution or developed in-house. The system can be customized (extensively) or existing business processes can be adjusted to accommodate an off-the-shelf solution – both approaches have an impact on innovation potential and market differentiation. Systems can also be delivered at once or gradually brought into the picture.

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Based on our experience, choosing the right approach depends on three fundamental decisions:

1. ‍Prioritization of business impact: A successful transformation increases efficiency, reduces costs, accelerates product launches, and enhances customer experience. Prioritize high-impact areas to secure early wins and maintain (or even increase) momentum
2. ‍Levers to unlock technology potential: Modern technologies such as (Gen)AI boost efficiency along the development value chain, and revolutionize areas like underwriting and claims. Define which technological advancements will be incorporated into the modernization approach and aligned with strategic objectives
3. ‍Risk appetite: Instead of a “big bang” approach, a strategic, phased transformation approach along stable value plateaus mitigates risks, ensures financial sustainability, and creates long-term value. Interim solutions and architectural plateaus should be designed based on priorities, expected impact, and feasibility

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GenAI note: While the impact of GenAI will be fundamental across the vendor, tooling and architecture ecosystem, it also increases uncertainty for laying out long-term plans due to its continuously and rapidly evolving nature. Factoring in approaches to deal with this volatility, implementing risk management, and carrying out effective vendor negotiation will be key differentiators.