Andrew Pery, AI Ethics Evangelist at intelligent automation company ABBYY
Fraud and identity theft are rising at an alarming rate, creating significant operational and financial risk for institutions worldwide. UK Finance reports that confirmed fraud cases exceeded 2.09m in the first half of 2025, a 17% increase year over year, with criminals stealing £629.3m during the same period.
The growing sophistication of financial crime is compounding the challenge. Digital fraud schemes such as synthetic identities, phishing attacks, deepfakes, and manipulated documentation are becoming more prevalent, making verification more complex and costly. Human reviewers can no longer reliably detect forged or altered documents, meaning manual processes are no longer just inefficient; they are insufficient to protect institutions from financial crime and regulatory exposure.
For financial institutions, falling behind on compliance has become an incredibly costly risk in recent years. Analysis by Kyckr found that of 22 Final Notices by the FCA between 2020 and 2025, data deficiencies featured in 68% of enforcement cases for AML non-compliance. The penalties covered by those notices totalled more than £430 million.
To meet AML obligations, financial institutions must demonstrate that they can identify customers, continuously monitor transactions, and act on suspicious activity across automated processes. This requires reliable data, effective systems, and clear audit trails.
However, many financial institutions still rely on fragmented compliance processes built on manual reviews, legacy systems, and inconsistent data validation. These inefficiencies don’t just slow down onboarding; they create gaps that regulators penalise and auditors detect.
A new era of AML enforcement
The July 2027 EU AML Regulation represents one of the most consequential shifts in Europe’s financial crime framework. By creating a single, directly applicable rulebook across all member states, the regulation aims to strengthen the EU’s collective defences against money laundering and terrorist financing while reducing regulatory fragmentation.
The AMLR significantly expands the scope of “obliged entities,” bringing crypto-asset service providers, mortgage and consumer credit intermediaries, and traders of high-value goods such as luxury vehicles, yachts, and precious metals firmly within the regulatory perimeter. These organisations must adopt more rigorous customer due diligence processes, including deeper verification of ownership structures and risk profiles.
Against this regulatory backdrop, Know Your Customer (KYC) is evolving from a compliance obligation into a strategic capability. Effective KYC programs now underpin not only regulatory adherence but also institutional trust, fraud prevention, and customer experience.
Firms are increasingly expected to move beyond periodic checks toward dynamic, lifecycle-based monitoring that leverages automation, digital identity verification, and real-time risk assessment. As regulatory expectations rise, organisations that modernise their KYC frameworks will be better positioned to manage risk while delivering faster, more seamless onboarding.
As regulatory expectations tighten, financial institutions face a delicate balancing act between strengthening controls and improving data accuracy, while avoiding intrusive procedures that frustrate customers.
Why AI Is becoming a compliance imperative
As regulatory requirements evolve, technology is rapidly reshaping how compliance is managed.
Most financial institutions have systems to store structured data, but critical customer and transaction information often sits within documents that move through the organisation with limited visibility. When this happens, the connection between the data, the review process, and the final decision can easily be lost.
Reliance on manual reviews further compounds the challenge. Onboarding processes tend to be slow and disjointed, and verifying customer identities and flagging suspicious activity for KYC compliance can be expensive and inaccurate, increasing operational expense and heightening regulatory risk.
At the same time, fragmented databases and repetitive documentation requirements continue to create onboarding friction, drive up operational costs, and leave exploitable gaps for fraudsters. The reliance on manual document review and redundant data entry creates substantial friction. Nearly 70% of workers spend over 20 hours a week managing fragmented systems, resulting in high operational costs.
When applicants are required to upload the same documents multiple times, it results in high drop-off rates and, consequently, lower conversion rates for businesses. Fragmented data sources and siloed information slow down the onboarding process, making it hard to achieve a real-time, 360-degree view of a user’s risk profile.
AI is reshaping the compliance model
Advances in AI-driven technology offer a more resilient path forward. For example, Document AI enables automated data extraction, validation, and monitoring, replacing disjointed workflows with consistent, auditable processes. Instead of reacting to compliance gaps, institutions can proactively manage risk at scale.
AI can automate the most manual and error-prone parts of compliance. Instead of relying on human teams to review IDs and cross-check data, AI can extract and validate information at scale to spot anomalies in real time. This reduces operational costs, accelerates customer onboarding, and, critically, lowers the risk of missed red flags. It also enables institutions to adapt more quickly to regulatory change.
In the evolving landscape of financial compliance, the integration of advanced technologies has become essential to address the complexities of AML and KYC regulations.
An example of how advanced technologies are strengthening compliance is the collaboration between FinTrU (https://www.fintru.com/) and Resistant AI (https://resistant.ai/) , both ABBYY partners whose complementary capabilities enhance the integrity and efficiency of regulatory processes.
FinTrU has developed an AI-driven document insight platform that automates the processing of complex, unstructured financial documents. Powered by ABBYY’s Intelligent Document Processing technology, it enables precise document classification, high-quality data extraction, human-in-the-loop validation, and the creation of audit-ready records. The results are significant: a 99% first-time pass rate in compliance reviews, 96% classification accuracy, a 40% increase in processing efficiency, and a 15% reduction in operational costs.
Resistant AI adds another critical layer by detecting fake, tampered, and AI-generated documents, allowing institutions to accept, escalate, or reject documents with greater confidence and speed. Integrated, intelligence-driven solutions can help financial institutions modernise AML and KYC programs while strengthening resilience against increasingly sophisticated financial crime.
The path forward
Financial institutions must now balance robust compliance with seamless customer experiences while preparing for more frequent and demanding regulatory scrutiny. AI-powered solutions, particularly Document AI make this achievable by automating data capture, strengthening verification, and enabling continuous monitoring.
By embedding intelligent automation into KYC workflows, institutions can reduce risk, control costs, and build greater trust. Those that modernise now will be best positioned to meet rising regulatory expectations and remain competitive in an increasingly complex financial landscape.
