Fintech is evolving faster than we’ve ever seen before. With artificial intelligence now driving everything from customer service to algorithmic trading, the risks are obvious; but the rewards have never been greater.
While AI unlocks huge operational efficiencies, it also leaves behind trails of fragmented, unstructured data. In an industry increasingly defined by regulation (think DORA, the EU AI Act, PCI DSS, ISO 27001, and GDPR) it’s a time bomb for firms that have blindly let automation run rampant.
The truth is that full visibility and control over your data landscape is no longer optional. It’s essential.
When Compliance Can’t Keep Up
This might seem like common sense, but it’s still alarmingly common to see financial institutions scale rapidly without embedding proper data controls.
Take Starling Bank, fined £28.9 million in 2024 for weaknesses in its financial crimes records. Growth had outpaced compliance, leading to 54,000 high-risk accounts being opened with little or no manual inspection. While it wasn’t a deliberate breach, it was a failure of systems, process, and visibility through gross oversight. Some have speculated that the low cost and scalability of AI systems enabled greed.
Another notable instance is TD Bank, hit with a record-breaking $3.09 billion in fines for anti-money laundering (AML) violations. Among the findings:
- Employees accepting bribes
- Thousands of Suspicious Activity Reports (SARs) missed
- Over $1.5 billion in unreported transactions
- More than $670 million laundered from drug trafficking proceeds
It doesn’t take a genius to realise what both cases have in common, which is a total lack of data transparency.
Regulatory Pressure Is Only Increasing
As cases like these make headlines, regulators are responding in kind. The FCA, FCFS, and government watchdogs are tightening expectations around real-time monitoring, automated auditability, and proactive data governance.
Financial firms are under constant regulatory scrutiny, with regulators, prospects and governments fully expecting them to align with frameworks like:
- DORA (Digital Operational Resilience Act)
- PCI DSS (Payment Card Industry Data Security Standard)
- ISO 27001 (Information Security)
- GDPR and SOC 2
- Industry-specific FCA and BoE operational resilience guidelines
The Problem? Most Fixes Are Still Manual
Despite the urgency, most firms still approach compliance the old-fashioned way. Manual reporting, sluggish audits and blind spots across departments.
To make matters worse, many are locked into bloated, overpriced SIEM tools that are either underutilised or so complex they require entire teams just to extract insight.
Others run separate systems for logging, monitoring, reporting, and security. Some dedicate entire departments to stitching together the evidence come audit time.
Given the sheer volume of data and the shortfalls we’ve seen across the industry, automation must be used in a sustainable way. AI will hallucinate and there has to be controls in place, but without automation the competition using it is bound to steal a march.
The Only Way Forward
To stay ahead, compliance must become real-time, automated (in a responsible way), and integrated across a unified platform.
That’s where tools like Elastic come in. Elastic breaks down data silos, brings clarity to chaos, and creates a foundation of trust and transparency that satisfies both regulators and internal teams alike.
This is what harmonised data means to us. To have logs, traces and metrics working in unison to create a tuned model that eases the burden of compliance for complex institutions. Peter Sondergaard once said, ‘Information is the oil of the 21st century, and analytics is the combustion engine’ and he’s not wrong. We’ve moved into an era where the biggest and best got there on good data, good insights and good decisions. To have one without the others is pointless.
The secret is in the targeted use of AI. Many firms I work with on our AI governance services use it to achieve faster growth, sustainably.
Don’t get left behind.
Leave A Comment