Author

Maxime Vermeir

Published

18 May 2026

Estimated Read time

6Mins

Maxime Vermeir, Vice President of AI Strategy at ABBYY, on how organisations can build a faster and more resilient approach to KYC compliance

“Know Your Customer” (KYC) used to feel as painfully slow as dial-up internet, but it doesn’t have to be that way any more.

KYC is the process organisations use to verify the identity of their customers, assess risk, and ensure compliance with regulations such as AML (Anti-Money Laundering) and counter-terrorist financing laws.

Today, it’s about more than compliance. It’s a critical trust and customer-experience driver. Financial institutions, insurers, and fintechs use KYC to build confidence, protect their brand, and deliver frictionless onboarding experiences that feel more like Apple Store checkout than DMV purgatory.

However, organisations face an increasingly challenging landscape.

Regulatory pressure is intensifying. The July 2027 EU AML Regulation, for example, will harmonise standards across all member states, introducing stricter requirements for beneficial ownership data and ongoing due diligence.

At the same time, customer expectations have shifted dramatically. People expect to open accounts or complete onboarding in minutes, not days. Fraud and identity theft are growing. Deepfakes, synthetic IDs, and digital manipulation make verification more complex and costly than ever.

Against this backdrop, many organisations struggle to keep pace. Inefficient processes, fragmented systems, and manual checks create delays, increase risk, and damage the customer experience. We examine the six deadly sins of KYC compliance and how organisations can address them to build a faster and more resilient approach.

Fragmented, Siloed KYC Workflows

    KYC processes often span multiple systems, from CRM to AML, to onboarding portals and case management. A lack of integration between these different areas creates more work, with data capture often duplicated, and SLAs missed. Teams have no unified view of onboarding performance.

    Disconnected databases, inconsistent standards, and repetitive customer documentation cause onboarding friction, high operational costs, and gaps that fraudsters can exploit with alarming speed.

    To combat these risks, organisations need to implement end-to-end visibility across fragmented workflows. The easiest way to achieve this is through AI-powered Process Intelligence tools. These tools can reveal bottlenecks, improve communication between teams, and avoid the risk of repeating time-consuming work.

    Manual Document Handling and Validation Bottlenecks

    Most onboarding delays occur during document intake and validation. Human review teams spend hours checking IDs, proof of address, and corporate records, often working across multiple systems and formats. This introduces inconsistencies, with decisions likely varying between reviewers, and increases the likelihood of errors or missed details.

    The process is also resource-intensive and difficult to scale. As volumes increase, manual reviewers either become bottlenecks or require additional headcount, pushing up operational costs. Long cycle times mean customers wait, which can lead to drop-off, frustration, and reputational risk to the organisation.

    Automating document classification, extraction, and validation can mean the difference between success and failure, even for complex, multi-page corporate KYC packs. These systems leverage intelligent workflows and advanced data processing to accurately sort documents, extract critical information, and standardise it in real time.

    This not only reduces manual effort but also significantly minimises human error, identifying missing fields and inconsistencies before submission. AI tools for regulatory automation and fraud checks enable higher rates of first-pass compliance and faster document processing. This means less time spent on manual reviews and a faster overall process.

    Lack of Process Visibility and Control

    Compliance and operations teams at financial services organisations often lack real-time visibility into where a customer’s onboarding file sits in the process or how long it has been at each stage. Information typically spreads across systems, inboxes, and manual trackers, making it difficult to build a clear view of progress.

    As a result, it’s difficult to pinpoint the problem when delays happen. This lack of transparency makes it harder to meet SLAs or prepare for audits. Teams may only realise there’s an issue once deadlines are missed or escalations occur.

    Process Intelligence provides real-time monitoring of onboarding KPIs, including time per stage, rework rates, and failure points, and allows teams to simulate process improvements. It creates a complete digital audit trail of every step, supporting both operational management and regulatory compliance.

    Better visibility makes it easier for organisations to maintain control, prove compliance, and deliver a predictable customer experience.

    Inconsistent Execution Across Regions and Business Lines

    In many businesses, each branch or business unit follows slightly different onboarding procedures, often shaped by local practices, legacy systems, or different interpretations of compliance requirements. While these variations may seem small individually, together they increase fragmentation across the organisation.

    This can lead to inconsistent customer experiences and non-uniform compliance documentation. One customer may be onboarded quickly, while another similar customer faces delays or repeats because a different team or location handles them. Over time, this erodes trust and makes the organisation look disjointed and unpredictable.

    Best-practice workflows must be standardised enterprise-wide, and all data and documentation should adhere to consistent formats and validation rules across jurisdictions. This is where Process Intelligence excels, benchmarking and comparing process execution across teams, countries, and products, and highlighting deviations from policy.

    Slow Remediation and Periodic Review Cycles

    When periodic reviews or remediation campaigns begin, teams struggle to find and validate the information they need. Customer records may be spread across multiple systems or stored in inconsistent formats, making it difficult to quickly identify what is missing.

    Manual checks only make things worse. Reviewing large volumes of records is time-consuming and repetitive, increasing the likelihood of human error. As workloads increase during remediation campaigns, these risks multiply.

    A better approach is event-driven (pKYC) automation. Instead of relying on periodic reviews, it detects changes in customer data and automatically triggers the right review workflows. Intelligent document processing (IDP) can quickly revalidate and update documents, while process intelligence tools track progress, flag exceptions, and ensure tasks are completed on time.

    Proving Compliance and Audit Readiness

    Regulators increasingly expect organisations to demonstrate full transparency across their KYC processes, including clear data lineage, time-stamped actions, and explainable decision-making. This is particularly true where AI or automation is involved.

    It is no longer sufficient to show that checks were completed. Firms must be able to evidence exactly how data was collected, transformed, verified, and used at every stage of the customer lifecycle. However, many organisations lack this end-to-end audit view. KYC processes are often fragmented across multiple systems, and as a result, audit trails are incomplete or difficult to reconstruct.

    Process Intelligence maintains a comprehensive record of every process step, decision, and exception, while IDP provides field-level traceability, showing where each data point came from and how it was verified.

    Using AI-powered tools that combine process intelligence with document processing makes KYC faster, easier, and more accurate. It means customers can be onboarded more quickly and mistakes are reduced, making the whole KYC process easier to track and audit. Organisations can trust that they comply with regulations while building trust among customers and giving them a smoother, better experience.

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    • Cybersecurity in FinTech
    • Digital Payments

    Author

    Husnain Bajwa

    Published

    30 April 2025

    Estimated Read time

    5Mins

    Husnain Bajwa, SVP Product – Risk Solutions at SEON, on KYC detection and verification to combat fraud in financial services

    Many fraudsters today are no longer just criminals – they’re technologists wielding powerful artificial intelligence (AI) as their primary weapon. As fraud techniques evolve, businesses are becoming increasingly vulnerable to sophisticated adversaries. With the rising wave of AI-powered fraud, traditional fraud prevention methods, which heavily emphasise Know-Your-Customer (KYC) processes, are struggling to keep pace.

    Fraudsters have learned to exploit the inherent delays in standard KYC processes. They use AI to generate synthetic identities and automate infiltration techniques at an unprecedented scale. By the time most verification processes kick in, significant resources have already been spent, and potential damage has been incurred. To gain the upper hand, companies must move beyond isolated identity checks and adopt a more integrated approach. This combines pre-KYC detection with advanced KYC verification. A dual-layered defence system that’s both proactive and agile enough to adapt to the evolving threat landscape.

    Introducing Pre-KYC fraud detection

    Since KYC processes are essential for businesses to meet regulatory requirements and maintain compliance, the solution isn’t to abandon KYC but to transform it. Organisations must adopt a pre-KYC detection layer that detects fraud before it reaches verification processes.

    What does this look like in practice? It starts by analysing a user’s digital footprint. This includes key data points, such as the age of an email address, phone number history, IP address patterns and social media activity. These indicators help assess the authenticity of a user’s identity. For example, a newly created email or an IP address associated with a known VPN service can be red flags, signalling possible fraudulent intentions and enabling businesses to proactively intervene before harm occurs.

    Device intelligence further strengthens the initial stages of pre-KYC user verification. This technology detects discrepancies in device integrity, such as emulators, proxies or device spoofing techniques. These are common tactics fraudsters employ to conceal their true identities. Advanced device fingerprinting tools are critical in identifying when a device’s profile does not match its user’s provided details or shows unusual behaviour, adding an extra layer of security.

    Adding to this framework, behavioural analytics play a pivotal role by monitoring how users interact with platforms. Analysing navigation patterns, session durations and behaviours during account setup can expose irregularities that suggest fraudulent activities. Indicators such as repetitive account creation attempts with varied data points or abnormally quick typing and navigation speeds often point to bot-driven fraud. This provides businesses with opportunities to intervene early in the user engagement process.

    Combining Pre-KYC Technology with traditional methods

    While pre-KYC tools can identify potential threats early, KYC verification remains essential for ensuring that the users who pass initial screening are legitimate. Once a user reaches this stage, robust identity verification methods must be in place to confirm the authenticity of the individual’s information.

    Modern KYC processes must combine several features: document verification, biometric checks and address verification. The first, document verification, involves using optical character recognition (OCR) and machine learning to scan government-issued IDs and detect forgeries in real time. Additional security in this realm can be attained via facial comparisons – matching a user’s selfie with the photo on their ID – to ensure that the person behind the camera is the same as the one in the presented documentation.

    Next, advanced liveness detection aids in combating both deepfake technology and image-based fraud – two fraud vectors on the rise. By requiring users to perform specific actions or gestures during verification processes, liveness detection ensures that fraudsters can’t simply upload a static image or video to impersonate someone. Lastly, address verification provides further protection, confirming a user’s address against authoritative databases or recent utility bills. These checks are crucial for businesses in regulated industries, where proof of residency is often a compliance requirement.

    The growing threat of AI-powered fraud

    Now that fraudsters can access AI tools, the fraud game has entirely changed. Bad actors can generate synthetic identities, manipulate biometric data and even create deepfake videos to pass KYC processes. Additionally, AI enables fraudsters to test security systems at scale, quickly iterating and adapting methods based on system responses.

    In light of these new threats, businesses need dynamic solutions that can learn and evolve in real time. Ironically, the same technology serving sophisticated fraud can be our most potent defence. Using AI to enhance both pre-KYC and KYC processes delivers the capability to identify complex fraud patterns, adapting faster than human-driven systems ever could. These AI-powered tools don’t just detect fraud – they predict and prevent it by continuously learning from each attempted breach.

    At the pre-KYC stage, machine learning (ML) algorithms can identify patterns and anomalies across vast amounts of user data, providing more accurate and faster risk assessments. As fraudsters evolve, these systems can recognise emerging fraud patterns, preventing bad actors from bypassing security.

    Similarly, AI-driven verification methods can detect increasingly sophisticated forgeries and manipulations in the KYC phase. At the same time, adaptive authentication systems can increase or decrease the level of verification required based on the user’s risk profile. This flexibility strengthens security and enhances the user experience by reducing friction for legitimate users.

    The stakes are set to climb

    The battle against AI-empowered fraud isn’t just about preventing financial losses. It’s about maintaining customer trust in an increasingly sceptical digital marketplace. Every fraudulent transaction erodes confidence, and that’s a cost too high to bear in today’s competitive landscape.

    Businesses that take a multi-layered approach, integrating pre-KYC and KYC processes in a unified fraud prevention strategy, can stake one step ahead of fraudsters. The key is ensuring that fraud prevention tools – data-rich, AI-driven and flexible – are as adaptive as the threats they are designed to stop. The future of fraud prevention isn’t about building higher walls; it’s about creating smarter, more adaptive and intelligent systems to anticipate and neutralise threats before they materialise.

    • Cybersecurity in FinTech

    Author

    Henry Balani

    Published

    18 September 2024

    Estimated Read time

    4Mins

    Henry Balani, Global Head of Industry & Regulatory Affairs at Encompass Corporation, on meeting the demand for improved risk management, operational efficiency, and customer service with pKYC

    The traditional banking and finance industry is evolving. Processes are experiencing a digital transformation as a result of perpetual Know Your Customer (pKYC). The pKYC approach enables modern banks to continuously update and verify customer information in real time. Banks are moving away from the reliance on periodic reviews. This change is driven by technological advancements. And the increasing demand for dynamic and responsive regulatory compliance mechanisms.

    Perpetual KYC

    Conventional KYC processes commonly involve periodic reviews of customer information at fixed intervals. These reviews are typically conducted every one, three, or five years. While these reviews are thorough and comprehensive, they are also static. This can result in outdated information, potentially overlooking changes in customer risk profiles or new compliance requirements.

    On the other hand, perpetual KYC is dynamic and event driven. Through its continuous and automated approach, pKYC enables financial institutions to address risks and compliance needs in real-time. These risks can be determined by continuously monitoring customer activities. Furthermore, automatically updating profiles in response to specific triggers, including changes in personal information, significant transactions, or alterations in beneficial ownership.

    Gaining a competitive advantage with pKYC

    By leveraging pKYC, banks, and other regulated financial institutions can take advantage of a range of benefits. These are crucial in the modern digital era to gain a competitive edge. Through continuous monitoring, pKYC enables financial institutions to identify and address potential risks promptly. This real-time approach helps mitigate risks associated with financial crimes. Moreover, it ensures compliance with the latest regulatory standards.

    pKYC will lead to operational efficiency and cost reduction. By automating many of the manual processes involved in KYC, pKYC significantly reduces the time and resources needed for compliance. This allows financial institutions to focus their efforts on high-risk cases, rather than conducting blanket reviews for all customers, resulting in substantial cost savings.

    This process also enables many banks to improve their customer service and management. It also enhances the customer’s experience. With pKYC, customers are not subjected to frequent, intrusive reviews if their profiles remain stable. This results in a smoother and more positive customer experience, potentially increasing overall customer satisfaction and loyalty. Additionally, automated systems minimise human error and ensure consistency in applying KYC policies. This enhances overall regulatory compliance and reduces the risk of non-compliance penalties.

    Perpetual KYC implementation: Challenges and considerations

    Implementing a pKYC operating model is not straightforward. It requires the right blend of infrastructure and operating process. Every firm’s pKYC journey and ecosystem will be unique and cut across people, processes and technologies.

    Data is central to the success of pKYC as reviews based on event changes (aka event driven triggers) will not be effective if client information is outdated, missing or incorrect. Without consistent access to relevant and accurate client information, pKYC is impossible. Corporate Digital Identity (CDI) is fast emerging as a foundation for ensuring valid customer information is collected for successful pKYC operations.

    Being able to leverage this data requires an ecosystem of technology, which may be developed in house, utilising third-party RegTech providers, or a combination of both. This technology should drive how data is stored, structured and accessed so that pKYC triggers can be comprehensively managed. Customer lifecycle management systems (CLMs) are particularly relevant to pKYC as they connect all components along the workflow processes.

    Importantly, overarching executive sponsorship is needed to ensure a successful outcome in transformation initiatives. Recognising the structural and cross departmental challenge, influential sponsors will align the multiple stakeholders involved in driving this change and will champion a firm’s pKYC strategy and approach to regulators and other key stakeholders.

    Ultimately, pKYC must be future-proof and scalable, ready to adapt in line with business strategy and regulation to keep firms competitive.

    The future of pKYC

    The adoption of pKYC is growing, driven by regulatory pressures and the increasing complexity of financial crimes. Financial institutions are recognising the benefits of a proactive, real-time approach to compliance and risk management. The move towards pKYC is seen as a necessary evolution to stay ahead in a highly regulated and competitive financial environment.

    As the technological landscape continues to evolve, integrating advanced technologies such as blockchain and further developments in AI and ML will likely enhance pKYC systems’ capabilities. Ensuring higher levels of compliance and risk mitigation, these technologies are able to provide more robust and secure mechanisms for customer verification and monitoring.

    Blockchain technology can be utilised to further improve the initial customer authentication and validation process. As a result, we can expect improvements and advancements in the quality of customer data collected during initial customer onboarding processes. Financial institutions can then leverage AI-enhanced tools that can identify and collect the necessary attributes during document processing stages. This ensures that pKYC will utilise relevant, accurate, and up-to-date data. Perpetual KYC represents a significant departure from traditional, periodic KYC, as it offers a wide range of benefits in real-time risk management, operational efficiency, and customer experience. Although the implementation of pKYC poses certain challenges, it also provides numerous advantages, making it an increasingly attractive solution for financial institutions aiming to enhance their compliance and risk management frameworks and maintain a competitive edge in a rapidly evolving regulator landscape.

    • Cybersecurity in FinTech