The insurance industry is undergoing one of the most profound shifts in its history. Competition is no longer defined by products or pricing alone but by how intelligent systems can think, connect, and evolve. Modernization has become inevitable; what remains uncertain is how insurers choose to achieve it.

Some carriers are rebuilding their digital core from within, investing in bespoke architectures that mirror their legacy workflows and preserve institutional knowledge. Others are adopting ready-made platforms that offer scalability, regulatory compliance, and faster deployment cycles. Each route leads toward modernization but demands a fundamentally different philosophy of control, ownership, and pace.

This divergence has created a defining question for the modern insurer: Should the intelligence that drives the business be owned or outsourced? Building modern insurance solutions internally offers complete sovereignty over data, integration, and differentiation. Buying, on the other hand, accelerates innovation but introduces new dependencies and limits flexibility.

Artificial intelligence and automation have intensified this decision. Claims can now be processed in minutes, underwriting models to adapt in real time, and predictive analytics to redefine how policies are priced. However, beneath these advances lies a deeper strategic dilemma. According to McKinsey, insurers that align technology investment with long-term business outcomes—rather than reacting to platform trends, achieve up to 20% higher revenue growth than their peers.

The path forward is not about adopting technology for its own sake. It is about understanding what to build, what to buy, and how to orchestrate both without losing strategic intent.

What’s fueling the Build vs Buy Debate in Insurance?

The “build versus buy” dilemma isn’t new in insurance. What’s changed is the urgency and complexity driving that decision. The industry no longer moves at an annual policy cycle pace, it moves at the speed of algorithms.

Legacy systems, once the operational backbone, are now the biggest constraint. They struggle to support real-time analytics, omnichannel claims, and regulatory agility. Meanwhile, new compliance mandates, digital-native competitors, and customer expectations are reshaping what modernization truly means for insurers.

Consider the contrast across segments. In Property & Casualty (P&C), predictive models and claims automation are now baseline capabilities. Mid-sized carriers that once relied on manual workflows are competing against popular wholesalers, and MGAs transitioned to Insurtech for near-instant settlements.

In Life and Annuities, AI-driven underwriting models assess risk within seconds, learning continuously from contextual data — a sophistication most legacy architectures cannot emulate.

To visualize these mounting pressures, Exhibit 1 highlights the dominant forces influencing insurers’ modernization paths. Legacy constraints and regulatory velocity emerge as the most critical pressures, while AI, automation, and talent shortages exert moderate yet persistent influence.

Exhibit 1 – Forces Driving the Build vs Buy Decision

Ultimately, this debate extends beyond procurement or technology preference. It represents a strategic identity choice — whether insurers view technology as an asset to own or an intelligence layer to orchestrate. How they answer that question will define their competitiveness in the decade ahead.

The Build Approach — Creating Insurance Solutions In-House

Three years into a modernization program, a European P&C carrier found its custom-built underwriting engine only half complete. The intent was right, to own the algorithm that powered its core differentiation, but execution proved costly. Fragmented legacy data, changing compliance mandates, and the shortage of AI engineers stalled progress. The carrier eventually retained its proprietary risk model but embedded it into a vendor platform to recover speed.

This example reflects a common reality: insurers build when they want control, but control alone rarely ensures agility. Building modern insurance solutions internally requires not just capital but also a sustained operating model that aligns technology, governance, and talent.

Why Insurers Choose to Build and How It Works in Practice

1. Workflow Fidelity through Custom Design
   Internal teams map underwriting, claims, and policy lifecycles before writing code. Every module is designed to preserve established workflows and avoid business disruption — a key priority for mature insurers that cannot afford downtime.
2. End-to-End Data Governance
   Building in-house lets data teams define how information flows across systems. Encryption, storage, and lineage controls are architected internally to ensure compliance across jurisdictions. This is critical when dealing with multi-market operations where data residency laws differ.
3. Embedded Differentiation
   When pricing engines or fraud-detection algorithms are part of a carrier’s IP, internal development enables tighter coupling between business logic and technology. It’s how large multiline insurers convert underwriting expertise into a digital advantage.
4. Integration Control
   Proprietary architectures allow direct connection to CRMs, finance systems, and analytics layers. This flexibility helps avoid vendor roadmap delays — a frequent pain point for carriers that evolve faster than their software partners.

Where the Model Breaks Down: The ‘How’ Behind the Gaps

1. Engineering Bandwidth and Cost Overruns
   Each new compliance update or feature request goes through internal backlog cycles. This slows release velocity and stretches IT budgets, particularly when teams depend on external contractors for specialized modules.
2. Complexity of System Interlinkages
   Integrating new builds with policy admin, claims, and reinsurance modules often leads to dependency loops. Even minor code changes require full regression testing, increasing both risk and time-to-market.
3. Talent and Knowledge Continuity
   When key engineers leave, institutional knowledge walks out with them. Few insurers have versioning discipline or documentation maturity equal to tech firms, resulting in rebuilds that start from scratch every few years.
4. Operational Debt
   Over-customization eventually limits flexibility. Each local tweak becomes a long-term maintenance commitment, making modernization efforts heavier, not leaner.

Building in-house, therefore, is less about coding software and more about building capability ecosystems. It suits insurers that can operate like technology firms with continuous release pipelines, product ownership culture, and governance that anticipates rather than reacts. Without these foundations, the build approach often transforms a strategic advantage into a structural constraint.

The Buy Approach: Leveraging Existing Insurance Solutions

In 2022, a mid-tier life insurer in Southeast Asia replaced its legacy policy administration system with a modular SaaS platform. Within eight months, the company had digitized new policy onboarding, automated claims validations, and integrated compliance reporting. What once required 60 manual touchpoints now took 10? Yet, six months later, the insurer’s CIO raised a new challenge — data portability and customization limits. The platform scaled beautifully, but its rigidity left little room for product innovation.

This experience captures both the promise and the paradox of buying insurance solutions. For many carriers, adopting third-party or SaaS systems is the fastest route to modernization. Vendors deliver pre-built modules, tested compliance frameworks, and continuous upgrades that align with evolving regulatory landscapes. However, outsourcing core system intelligence also means accepting new dependencies and shared control over the pace of innovation.

Why Insurers Choose to Buy and How It Works in Practice

1. Speed of Deployment
   SaaS and cloud-native solutions allow go-live timelines within months rather than years. Insurers typically follow a phased rollout — beginning with non-core modules like claims intake or billing — to minimize risk before scaling enterprise-wide.
2. Predictable Cost and Scalability
   Subscription-based pricing models convert capital expenditure into operating costs. CFOs can forecast IT budgets with precision, and scalability is often achieved instantly through vendor-managed infrastructure.
3. Continuous Upgrades and Regulatory Alignment
   Vendors automatically release compliance and security updates, ensuring readiness for IFRS 17, Solvency II, and data protection mandates. This reduces the internal monitoring burden and audit overhead.
4. Ecosystem Integration
   Modern SaaS platforms are API-first. They integrate easily with third-party analytics, payment gateways, and reinsurance networks — enabling insurers to assemble connected ecosystems rather than monolithic systems.

Why It Often Falters: The Operational Reality Behind the Trade-offs

1. 1. Limited Customization Flexibility
      SaaS systems are designed for broad market applicability. Carriers seeking product-level differentiation often hit configuration ceilings, where deeper customization incurs additional costs or delays in vendor approval.

1. Vendor Dependency and Contractual Rigidity
   Service-level agreements dictate release schedules and data access rights. Insurers may face “vendor lock-in,” in which exiting the ecosystem requires rebuilding integrations from scratch.
2. Data Portability and Ownership
   transferring historical data or merging datasets for analytics can be constrained by proprietary schemas. This complicates migration to alternate platforms later.
3. Integration Gaps and Legacy Coexistence
   During hybrid transitions, legacy modules often continue to coexist with SaaS layers. Without meticulous integration, governance, data reconciliation, and process alignment become recurring pain points.
4. Hidden Change Management Costs
   User training, workflow redesign, and stakeholder adoption require as much investment as the platform itself. Many insurers underestimate this human-operations layer, leading to slow utilization and project fatigue.

The buy approach is therefore most effective for insurers who prioritize speed, compliance, and scalability over deep architectural control. It enables modernization without heavy internal engineering investment — but also introduces a dependency rhythm that must be actively governed, not passively accepted. Successful adopters treat vendor management as a strategic discipline, ensuring agility is not achieved at the expense of autonomy. Let’s see an overview of build vs buy in exhibit 2:

Exhibit 2: Build vs Buy Comparison Matrix

The Hybrid Middle Path

For many insurers, the choice between building and buying has evolved into something more nuanced — a hybrid operating model. Instead of anchoring entirely on in-house or external solutions, insurers now design architectures where proprietary systems coexist with vendor platforms. The result is a balance between control and speed, building what defines them and buying what accelerates them.

In 2023, a global composite insurer adopted this hybrid philosophy while modernizing its claims and policy administration systems. It retained its proprietary risk and pricing engine but integrated it with a cloud-based claims platform. The insurer now owns the logic that differentiates its products while leveraging the vendor’s ready-made automation and compliance modules. This mix reduced development effort by 45 percent and cut claim turnaround times by nearly 30 percent within a year.

How the Hybrid Model Works

1. Modular Architecture Design
   Core intelligence layers, pricing, underwriting rules, fraud detection are built in-house, while peripheral layers such as claims intake, billing, and document management are sourced externally.
2. API-Driven Interoperability
   Integration through API gateways allows seamless communication between internal and external systems. This ensures data integrity while keeping technology stacks loosely coupled and easier to scale.
3. Selective Ownership of IP
   Insurers identify which parts of their technology stack directly contribute to market advantage and retain ownership there, outsourcing non-differentiating functions.
4. Adaptive Governance Frameworks
   Hybrid models require stronger vendor oversight, joint release calendars, and clear accountability structures to prevent dependency sprawl.

Before deciding which layers to build or buy, insurers often map their technology stack against ownership value and operational agility.

Exhibit 3 illustrates a typical distribution in a hybrid model and the rationale behind each decision.

Exhibit 3: The Hybrid Model in Action

The hybrid model reflects a pragmatic maturity. Insurers no longer see modernization as a binary choice but as a portfolio of ownership decisions. What matters most is not who builds the technology, but whether every system — built or bought — advances a unified business objective.

The Decision Framework: Questions That Matter

Choosing whether to build, buy, or blend insurance solutions is ultimately a strategic design decision — not a technical one. The most successful insurers approach it through a structured diagnostic lens, asking a few non-negotiable questions before committing capital or capability.

The framework below helps insurers evaluate which path aligns best with their goals, resources, and risk appetite.

1. What Problem Are You Trying to Solve?

Every modernization initiative begins with a business pain point — not a technology gap.
If the challenge lies in slow claims turnaround, the solution may rest in workflow automation or in document processing tools that can be easily bought off the shelf.
If the issue is inaccurate risk assessment, the answer may involve proprietary analytics models that must be built internally to preserve a competitive edge.

Framing the problem correctly helps avoid the common trap of adopting technology for its novelty rather than its relevance.

2. Which Path Solves the Problem Without Adding Risk or Complexity?

Modernization often introduces hidden dependencies — compliance exposure, third-party integrations, or resource strain.
Insurers should assess each route for operational friction:

• Will the new system comply with data sovereignty norms across all markets?
• Can it integrate seamlessly with existing claims, policy, and finance platforms?
• What level of people changing management will it require?

A simple rule of thumb: the right path reduces risk faster than it adds features.
According to PwC’s 2024 Digital Insurance Outlook, nearly 60 percent of modernization failures stem from underestimated integration complexity — not software limitations.

3. What Is the Cost Difference Between Building and Buying?

The total cost of ownership extends far beyond initial investment.

• Build: Upfront engineering and infrastructure costs are high, but operating costs stabilize over time if managed efficiently.
• Buy: Initial costs are low, but recurring subscription and customization fees can accumulate quickly.

The table below illustrates how insurers typically evaluate financial implications across both models.

Exhibit 4: Comparative Cost Considerations

4. Do You Have the Internal Expertise to Sustain What You Build?

Even the most sophisticated platform fails without capable stewardship.
Building in-house requires sustained engineering talent, architecture governance, and iterative release cycles. Many insurers underestimate the cultural shift required to operate like a software company.

In contrast, buying transfers some of that responsibility to vendors — but it also means ceding direct control over innovation velocity.

The right approach depends on whether the insurer’s core strength lies in technology execution or in product and market strategy.

A mature insurer’s modernization of roadmap is rarely defined by a single answer. It’s a balance of these four diagnostic dimensions — business need, risk profile, financial model, and capability depth.
The objective is not merely to pick between build or buy, but to design an ecosystem that scales intelligently without compromising strategic control.

Future Outlook — Flexibility as the Ultimate Solution

The insurance industry’s modernization journey no longer revolves around a binary choice. The future belongs to insurers who can adapt their technology to posture as markets, risks, and regulations evolve. Flexibility — not architecture — will define resilience.

In the coming years, AI, automation, and data ecosystems will continue to blur the lines between building and buying. Insurers may build today and outsource tomorrow or integrate vendor modules now and reclaim ownership later through customization. The real differentiator will not be the system itself but the fluidity with which insurers reconfigure it to match emerging realities.

Global research has already reflected this shift. McKinsey’s 2024 Digital Insurance Study notes that over 70 percent of top-performing insurers now operate within modular, API-first architectures — combining in-house intelligence with vendor-driven scalability. This model enables them to swap components without disrupting the enterprise core.

To stay ahead, insurers must view modernization as an ongoing design discipline, not a one-time project. Governance teams will need to make continual decisions about what to own, what to rent, and what to retire — ensuring that technology evolves in lockstep with business ambition.

Ultimately, whether built or bought, the strength of any insurance solution lies in how seamlessly it aligns with the organization’s purpose. The winners will be those who see technology not as an endpoint but as a living ecosystem — one that learns, scales, and transforms along with their enterprise vision.

Whichever path you choose, the strength of your insurance solution will always depend on how seamlessly it serves your core business goals.