Financial crime compliance
How to streamline customer due diligence (CDD) processes
As financial institutions strive to build lasting relationships with high-value clients, an efficient onboarding process becomes a critical differentiator. However, customer due diligence (CDD) requirements often lead to delays that can hamper operational efficiency and diminish client satisfaction. With corporate banking onboarding costs averaging $6,000 and timelines stretching between 30 to 90 days, streamlining CDD processes is essential for accelerating client engagement and maintaining a competitive edge.
Organisations are now reimagining compliance as a growth driver. By embedding automation, artificial intelligence (AI), and agile frameworks into their CDD workflows, these innovators are cutting costs, accelerating growth, and building unshakable customer trust. Here’s how to transform your customer due diligence process from a bottleneck into a strategic asset.
Why customer due diligence is so complex?
CDD is designed to prevent financial crime by helping organisations verify who their customers are, understand the nature of the business relationship, assess risk, and monitor activity for anything suspicious. While the objective is clear, the execution is often complicated.
Different regions follow different regulatory frameworks, and standards set by organisations such as the Financial Action Task Force (FATF), FinCEN, and the European Banking Authority continue to evolve. For global firms, this creates a maze of compliance regimes that can lead to fragmented processes.
Meanwhile, client expectations are also changing. Many now expect the same seamless digital experiences from professional services as they do from consumer platforms. If the onboarding process is slow or disjointed, clients may abandon it altogether or choose to work with a competitor.
Rethinking customer due diligence with technology
To address these challenges, organisations must fundamentally rethink how they approach due diligence. The goal is to build a dynamic, data-driven CDD approach that meets regulatory standards while also improving client experience.
Automate data collection and verification
Manual data entry is rapidly becoming outdated. AI-driven platforms now extract information from IDs, passports, and invoices using optical character recognition (OCR), cross-referencing global databases in real time. Leading solutions even integrate biometric authentication, such as facial recognition and liveness detection, to counter deepfake fraud. These tools accelerate onboarding and reduce human error. A boutique wealth management firm was able to reduce onboarding time by 50%, from 30 days to 15 days, by implementing digital forms and automating data entry and compliance checks.
Prioritise risk-based client due diligence
Not all clients warrant the same scrutiny. A tiered approach aligns due diligence efforts with risk levels – low-risk clients, such as salaried employees, undergo simplified checks, while high-risk entities, including politically exposed persons (PEPs), require enhanced due diligence (EDD). Machine learning algorithms automate risk scoring by analysing factors like geography, transaction history, and industry exposure. A fintech serving crypto startups, for example, might assign higher risk weights than one working with non-profits. This precision ensures that compliance teams focus energy where threats are highest.
Break down silos with centralised systems
Dispersed, inconsistent data continues to be a significant barrier to efficient onboarding. Without centralised access to complete and accurate information, compliance teams often spend valuable time reconciling documents and verifying details multiple times. A centralised CDD or client lifecycle management (CLM) system helps resolve this. When all client data are stored in a single platform, customer due diligence processes become more transparent and manageable. Teams can work more collaboratively, audit trails are easier to generate, and clients are not asked to resubmit the same information repeatedly.
Deploy AI for continuous monitoring
CDD doesn’t end at onboarding. Real-time transaction monitoring tools now use AI to detect anomalies, such as sudden large transfers to high-risk jurisdictions. These systems learn from historical data to refine alerts, resulting in a 40% reduction in fraud losses over two years.[4] For instance, a retail client abruptly moving $100,000 daily is instantly flagged as an anomaly, enabling proactive intervention instead of post-facto audits. This shift from reactive to predictive compliance is a game-changer for risk mitigation.
The future of compliance is adaptive
Regulators are pushing banks and companies to use smarter tech tools to stop financial crime. While tracking suspicious activity with AI isn’t new, rules now require checking things like how users type or speak to catch fake IDs made by computers. Companies must also track crypto transactions instantly. Governments and businesses are testing AI tools together to keep up with criminals using advanced tech.
In an era where compliance is viewed as a revenue driver, streamlined processes offer the ultimate competitive edge. Firms that master adaptive CDD will not only evade fines but also attract clients fleeing slower, riskier competitors.
How can Infosys BPM help turn customer due diligence into a revenue driver?
The cost of compliance is surging, reaching $61 billion annually in the US and Canada alone, highlighting the need for a smarter, more scalable approach. Infosys BPM solutions are tailored for tangible impact by reducing false positives and optimising alerts to deliver up to 40% in cost savings and 30% higher operational efficiency. Backed by Infosys Topaz, our AI-first framework, we empower clients to future-proof their operations with ethical, ready-to-deploy, and innovation-led tools.
