On 16th March 2026, Aker Systems will be attending and sponsoring the - Data, AI and the Future of Financial Services Summit 2026 in London

Across UK financial services, AI adoption is accelerating rapidly. AI is no longer experimental. It is embedded in core operational workflows including underwriting, fraud detection, claims automation and customer experience. But as adoption scales, one question becomes critical:

Are your data foundations ready for AI at scale?_‍

_{Why AI in Financial Services Depends on Trusted Data Foundations}

AI in financial services is moving from experimentation to operational decision-making.

Today’s deployments increasingly involve:

• Automated underwriting
• Real-time fraud detection
• Claims automation
• Dynamic pricing
• Intelligent customer journeys

When AI systems influence financial outcomes, firms must demonstrate:

• data lineage
• Explainability
• Governance
• Accountability
• Operational resilience

This is where many institutions encounter friction. AI performance, compliance and defensibility are entirely dependent on the strength of the underlying data foundations.

The Hidden Constraint: Legacy and Fragmented Data Estates

Many financial services organisations operate within legacy, fragmented data environments shaped by years of acquisitions and system evolution.

Common challenges include:

• Siloed data across multiple platforms
• Limited traceability and lineage
• Difficulty meeting FCA and PRA evidence requirements
• Challenges integrating structured and  unstructured data
• Weak interoperability across ecosystems

AI deployed on weak foundation soften operates in isolated pockets. It may appear successful in controlled pilots but scaling it across regulated environments becomes difficult - particularly under board and regulatory scrutiny. To scale AI responsibly, firms must invest in data modernisation and secure, AI-ready data architecture.

Real-Time, Event-Driven Data Platforms Are Now Foundational

Modern AI use cases require live operational data - not static batch feeds.

Fraud detection, underwriting,claims management and customer experience depend on:

• Real-time data pipelines
• Event-driven data platforms
• Automated lineage and audit capabilities
• Evidence-by-design governance
• Secure, sovereign cloud environments

AI initiatives frequently stall when organisations discover their real-time data infrastructure is insufficient. To operate safely at scale,financial institutions must build secure, AI-ready data platforms that combine governance, resilience and performance by design.

Data Sovereignty, Security and Operational Resilience

In today’s geopolitical climate,data sovereignty and resilience are strategic concerns.

Financial services firms must maintain confidence in:

• Where data resides
• Who controls it
• Who has access
• How platforms perform under stress

Security, governance and operational resilience must be architected into platforms - not retrofitted later. This is particularly critical for regulated sectors such as financial services, insurance and critical national infrastructure.

Looking Ahead to 2030: Data as the Strategic Differentiator

Looking ahead, especially in insurance, one theme is clear:

Data becomes the differentiator.

Future financial services models will be:

• Real-time
• Contextual
• Ecosystem-driven
• Interoperable

We expect to see:

• Faster claims journeys

• Proactive risk prevention
• Dynamic pricing based on live signals
• Enhanced fraud detection through     cross-ecosystem data

But these capabilities depend on secure data sharing, strong governance and trusted interoperability. The opportunity is not simply more AI. It is trusted, secure data movement across multiple parties at operational speed - supported by robust,governed, AI-ready data infrastructure.

Building Secure, AI-Ready Data Foundations

At Aker Systems, we describe ourselves as The Data Modernisation Company.

We design, build and operate:

• Secure-by-design cloud architectures
• Real-time, event-driven data platforms
• Governed, resilient, AI-ready data     infrastructure

We operate in mission-critical,highly regulated environments - including financial services, insurance,government and critical national infrastructure.

We are not an AI vendor.

We build the secure data foundations that enable regulated firms to adopt AI safely, confidently and at scale - without increasing operational or regulatory risk.

As AI adoption accelerates, the firms that succeed will not be those that experiment fastest. They will be those that modernise their data architecture most effectively.

Frequently Asked Questions

What is an AI-ready data platform in financial services?

An AI-ready data platform provides secure, governed, real-time, interoperable data with full lineage and auditability, enabling safe AI deployment at scale.

Why does data modernisation matter for AI in insurance?

AI in Insurance use cases —underwriting, fraud detection, claims automation - require real-time,high-quality, governed data across multiple systems and partners.

How does data sovereignty impact AI adoption?

Data sovereignty ensures organisations maintain control over data location, access and resilience - critical in regulated sectors such as financial services.

Join the Conversation

We look forward to discussing secure data modernisation and AI-ready infrastructure at the Data, AI and the Future of Financial Services Summit on 16th March in London.

If you are attending and would like to explore how secure, real-time data platforms can unlock safe AI adoption in financial services, we welcome the conversation.

Chris Huggett
Chief Commercial Officer, Aker Systems

Tim Cassidy
Chief Technology Officer, Aker Systems

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