Life insurance has entered a new era of structural consolidation. Mergers and acquisitions (M&A) and portfolio carve-outs are now a core mechanism of industry evolution – moving faster, facing greater regulatory scrutiny, and leaving little margin for operational disruption.
At the same time, many insurers remain constrained in their ability to fully capitalise on AI opportunities, as fragmented data models and legacy platforms limit both speed of adoption and confidence in outcomes.
In this evolving landscape, it’s no surprise that many insurers hesitate to transition and that legacy decommissioning or consolidation is deferred. Yet this caution doesn’t eliminate risk. The difference between value creation and value erosion often comes down to one thing: whether customers and data can be migrated safely and cleanly, as part of M&A integrations and legacy consolidation.
Key takeaways
Why traditional data migration often fails in insurance
Life insurance migrations are uniquely complex. Large insurers manage millions of policies with decades of history across layered legacy platforms. Data is commingled, pricing logic has evolved, and customer outcomes depend on absolute precision.
Executives are right to be cautious as:
- a failed migration is immediately visible to regulators and customers
- it can erode customer’s trust in the brand
- a single pricing or benefit error can create systemic remediation risk
- decommissioning a core platform removes the ‘safety net’ many teams rely on.
Traditional migration models do little to minimise these risks. Manual mapping, limited visibility, and late-stage testing force leaders to take risks on trust, often without the evidence needed to be comfortable signing off.
As a result, insurers frequently avoid migrations, delay platform shutdowns and accept growing technical debt as the lesser of two evils.
How AI-powered data migration reduces risk
KPMG’s approach to customer and data migration reframes the problem. Instead of asking leaders to move faster despite the risk, it reduces the risk that causes hesitation in the first place. By combining a deep understanding of the life insurance business complemented by AI, automation and strong governance, this approach delivers:
- predictability: migrations that behave consistently
- transparency: full lineage, traceability, and reconciliation at every step
- early evidence: surfaces issues up-front to enable fact-based decision-making
- explainability: AI-assisted decisions that are governed, validated and auditable with regulatory evidence produced as part of delivery, not bolted on afterwards.
This allows organisations to:
- retire duplicated platforms sooner
- eliminate extended run‑off costs and operational drag
- reduce dependency on increasingly scarce legacy skills
- free up investment capacity for growth and innovation.
Speed, accuracy and reliability are the outcomes, but confidence is the prerequisite to enable these migrations to commence.
Modern migration and automated AI capabilities
How LC/NC platforms accelerate transformation
LC/NC platforms compress timelines by enabling business analysts to implement transformation logic through visual interfaces.
In other contexts, teams can achieve similar benefits using configuration-driven rules engines, parameter files, or structured templates on top of traditional ETL and scripting.
In both cases, actuaries and operations specialists can specify business rules without heavy translation layers, reducing communication overheads and accelerating validation cycles.
How generative AI supports customer and data migration
Generative AI introduces efficiency and automation into traditionally manual activities such as source to target mapping. For migrations involving 500+ data fields, GenAI proposes 60–70% of mappings with high confidence, reducing mapping phase duration by 40–50%. Where GenAI is not yet in use, similar efficiencies can be achieved over time by building reusable mapping libraries and pattern catalogues across successive migrations.
In practice, much of this efficiency comes from starting with preconfigured data models and mapping templates for leading policy administration platforms, such as Life400, LifeAsia and other industry solutions, and then tailoring them to each client’s specific structures and controls.
Additional GenAI capabilities include:
- automated test-case generation based on existing data and process patterns
- data lineage documentation that shows how each key data element moves and transforms across the migration pipeline
- real-time technical documentation and change logs that reduce the typical documentation drift seen in lengthy or multi-wave programs.
When embedded in a governed migration platform and combined with LC/NC tools, these capabilities enable insurers to industrialise migrations, apply consistent controls across batches of funds or investors, and reuse patterns for subsequent transformations.
In global financial services migrations of comparable complexity, this model has enabled organisations to:
- reduce migration timelines by 30–40%
- cut rework and remediation effort by 25–35%
- accelerate mapping phases by up to 50%
- decommission legacy platforms with confidence, not contingency plans.
Once a reusable migration platform and pattern library is in place, each additional insurance book migration benefits from existing mappings, rules and test assets. Anchoring this platform on reference data models (e.g. relationship between product–policy–customer–advisers) for widely used industry solutions further accelerates delivery, as many core entities and relationships are already understood and codified.
KPMG is your customer and data migration partner
KPMG is not just providing migration tooling or delivery capacity. We act as the confidence partner in the moments that matter most.
Our AI-powered customer and data migration capabilities support industry to:
- de-risk the delivery of market-facing migrations and empower business owners with complete transparency
- provide business stakeholders, boards and regulators with clear, evidence-based plans, progress and results, with comprehensive audit trails
- realise the business and commercial benefits of platform consolidation and modernisations
- enable efficient and repeatable platform decommissioning and consolidations, whilst protecting customer experience and service.
By combining deep life insurance domain experience with AI-enabled automation and robust governance, we help our clients move forward with increased certainty and confidence.
Talk to us today about how we can support you to:
- proceed with transactions with a stronger degree of certainty
- accelerate your ability to embed AI
- achieve faster execution without increasing risk
- decommission legacy platforms earlier and realise value faster
- preserve the trust of customers, regulators and investors alike.
Get in touch
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Frequently asked questions
AI‑powered migration reduces risk by providing predictability, full data traceability, early issue identification, and explainable, auditable decision‑making. This enables fact‑based sign‑off and regulatory confidence throughout the migration process.
In an environment of frequent M&A and legacy consolidation, the success of integrations increasingly depends on whether customer and data migrations can be executed cleanly. Poor migration outcomes can lead to value erosion, operational risk and regulatory exposure.
Insurers can retire duplicated platforms sooner, reduce operational drag and dependency on legacy skills, free up investment capacity for innovation, and decommission legacy systems with greater certainty while protecting customer experience and trust.