Elastic and AWS deepen finance tech alliance as banks race to fix siloed data and scale AI securely

Legacy systems, fragmented customer records and rising fraud risks are pushing financial institutions to rethink how they use data. At ElasticON London 2026, executives from Elastic and Amazon Web Services outlined how their partnership is helping banks modernise operations, strengthen security and accelerate artificial intelligence adoption.

Speaking during the event, Sal Gauri, Director for EMEA at Elastic, and Lisa Lewison, Head of Partnerships for Global Financial Services at AWS, said many banks still face structural problems built over decades. Those challenges include disconnected databases, duplicated customer identities, costly compliance processes and outdated infrastructure that slows innovation.

Their message was clear: financial institutions that fail to unify data and deploy AI responsibly risk falling behind faster moving rivals.

Many of the world’s largest banks were built long before cloud computing, real time analytics and AI became central to business strategy. As a result, customer data is often stored across separate departments such as loans, insurance, payments and wealth management.

That can create multiple records for the same person inside one institution. A customer may appear as a borrower in one system, an insurance user in another and a payments client somewhere else.

According to AWS executive Lisa Lewison, this fragmentation damages service quality and slows response times. If staff cannot quickly access a complete customer profile, tasks that should take seconds may take far longer.

For modern consumers used to instant digital experiences, delays can quickly become a trust issue.

The problem is no longer limited to operational inefficiency. Data silos can now affect revenue growth, customer loyalty and regulatory readiness.

Banks are under pressure to deliver personalised services, detect suspicious transactions quickly and comply with evolving data rules. None of that works smoothly when information is spread across disconnected systems.

Executives at the conference said institutions increasingly recognise that unified data is no longer optional. It has become a commercial necessity.

That shift is especially important as fintech challengers and digital first banks continue to raise expectations around speed, pricing and convenience.

Despite major investment in AI pilots, many organisations still struggle to move projects into full production.

Sal Gauri said companies often complete proof of concept exercises that generate promising results, but fail to scale them because the underlying data environment is not ready.

In simple terms, AI models are only as useful as the systems feeding them. If data is incomplete, duplicated, delayed or trapped in separate tools, even strong AI solutions can disappoint.

He also argued that adoption improves when AI is embedded directly into products teams already use, rather than treated as a separate experimental project.

That approach can make it easier for executives to justify spending because benefits become visible through productivity gains, faster decisions and lower operational costs.

To address the issue, Elastic described its platform as a move away from isolated data lakes and warehouses toward what it calls a search lake.

The concept is built around bringing structured and unstructured data into a common searchable layer, allowing institutions to query information quickly regardless of where it originated.

Using the Elastic Common Schema, organisations can connect logs, transactions, alerts, documents and operational records into one environment.

For banks, that could mean faster fraud checks, stronger monitoring and quicker access to customer insights.

The value proposition is straightforward: reduce complexity, lower storage inefficiencies and help teams find critical information rapidly.

Financial crime is becoming more sophisticated as criminals also adopt automation and AI tools.

That has increased the amount of data banks must analyse in real time. Every payment, login, account change and identity signal may matter.

Elastic executives said this is where search driven analytics can create immediate returns. Know Your Customer processes that once relied on external vendors and lengthy response times can increasingly be handled internally at much faster speeds.

In competitive markets, response time matters. Institutions that can verify identities or flag suspicious behaviour within seconds may reduce losses while improving customer experience.

One case highlighted at the event involved Electron, a South African payment processor.

According to speakers, the company handles around 150 transactions per second using Elastic and AWS technology. It also built a real time fraud alerting system on top of the platform.

That capability reportedly became valuable enough to offer to retail banking partners, turning an internal operational tool into a commercial product.

The example reflects a broader industry trend: technology investments that begin as cost saving measures can later become new revenue opportunities.

The partnership between Elastic and AWS is designed to combine cloud scale with enterprise search, security and AI tools.

AWS provides the infrastructure, governance controls and industry frameworks needed by highly regulated financial institutions. Elastic adds analytics, observability, cybersecurity and search capabilities.

Executives said this combination allows banks to innovate without sacrificing compliance.

That balance is crucial because regulators expect institutions to maintain strong controls even as they modernise systems and adopt generative AI.

The companies also pointed to deep integration with Amazon Bedrock, which offers access to multiple foundation models.

For financial institutions, model choice can be useful, but governance is often the bigger issue. Banks need audit trails, access controls, privacy protections and clear operational boundaries.

Conference speakers said large scale adoption depends on having a secure foundation rather than simply chasing the newest AI model.

That view reflects how enterprise AI is evolving. Early excitement around experimentation is now giving way to tougher questions about risk management, return on investment and operational resilience.

For institutions operating in Europe, data residency and sovereignty have become increasingly important topics.

AWS said its European Sovereign Cloud initiative responds to regulatory demands around where data is stored, processed and controlled.

This matters because many financial groups operate across borders while facing strict national and regional rules.

Cloud vendors that can address these concerns may gain an edge as more banks shift sensitive workloads away from on premises systems.

Another theme from the event was reuse.

Once a bank ingests logs and operational data for observability purposes, the same information can also help security teams investigate incidents or help business teams identify inefficiencies.

Instead of funding separate systems for monitoring, security and analytics, firms may gain more value from one integrated data foundation.

The discussion at ElasticON London highlighted a broader truth across finance: data architecture is now strategy.

Banks once competed primarily on branch networks, balance sheets and pricing. Increasingly, they compete on speed, intelligence, trust and digital experience.

Institutions that can unify data, automate decisions and deploy AI safely may improve customer satisfaction while reducing fraud and operational drag.

Those that remain tied to fragmented legacy estates could face rising costs and slower growth.

The Elastic and AWS alliance shows how enterprise technology vendors are positioning themselves for the next phase of financial services transformation.

The first era of digitisation focused on moving services online. The next era appears centered on making every system searchable, every workflow intelligent and every decision faster.

For banks under pressure from regulators, fintech rivals and changing customer expectations, that transition may no longer be optional.