The Rise of ‘RegTech’: Can Technology Finally Solve Compliance?

Executive Summary

For the past two decades, compliance has been the single greatest operational burden on international banks. In the post-9/11 and post-2008 financial crisis era, regulatory costs associated with Anti-Money Laundering (AML), Know Your Customer (KYC), and sanctions screening have exploded, forcing banks to hire armies of compliance officers. This manual, human-centric model is slow, wildly expensive, and prone to error. Into this gap has stepped “RegTech” (Regulatory Technology). RegTech is a new breed of fintech solution focused exclusively on automating and enhancing compliance. By leveraging AI, machine learning, and sophisticated data analytics, RegTech is shifting the compliance paradigm from a manual, reactive “box-ticking” exercise to an automated, predictive, and risk-based defense system, promising to make compliance not only cheaper but far more effective.

1. The “Age of Compliance”: A Problem of Volume and Cost

The core challenge of modern bank compliance is not just the complexity of the rules, but the sheer volume of data. A single large bank processes millions (if not billions) of transactions daily. The traditional model required humans to manually review any transaction flagged by an outdated, “rules-based” system.

• The Problem: “False Positives”: These old systems are notoriously “dumb.” A rule like “flag any payment over $10,000 to Country X” might generate 10,000 alerts a day. A human compliance team must then manually clear these, only to find that 99.5% of them are perfectly legitimate (false positives).
• The Cost: This creates a massive, expensive, and demoralizing operational drag. Banks spend billions of dollars on compliance staff who spend their entire day clearing benign alerts, all while sophisticated criminals learn to structure their payments to avoid triggering the simple rules.
• The Risk: The “needle in the hay-stack” problem is real. A critical, illicit transaction can easily be missed amidst the noise of thousands of false positives.

2. The RegTech Solution: From “Rules” to “Behavior”

RegTech solutions are designed to solve this “false positive” problem by being “smarter.” Instead of just basic rules, they use modern technology to analyze patterns, context, and behavior.

1. AI and Machine Learning for AML Modern AML platforms use AI to move beyond “rules” and into “context.”

• Traditional Rule: Flag transaction > $10,000.
• AI/ML Model: The AI platform builds a complex behavioral profile for a customer. It knows their typical suppliers, payment volumes, and business hours. It can then spot true anomalies.
  • Example: A $9,000 payment (which wouldn’t trigger the old rule) is sent at 3:00 AM to a brand-new entity in a jurisdiction the customer has never done business with. The AI flags this as high-risk, while it automatically clears a $50,000 payment to a known, long-term payroll provider. This is “risk-based” compliance.

1. Automating “Know Your Customer” (KYC) KYC and customer due diligence (CDD) are traditionally manual, paper-intensive onboarding processes.

• RegTech Solution: Modern KYC platforms automate this entire workflow. They connect via API to dozens of global data sources (company registries, government watchlists, adverse media reports).
• The New Workflow: A customer uploads their ID. An AI tool performs biometric facial recognition, verifies the ID against global databases, screens the name against all sanctions lists, and scours the web for negative news—all in under 60 seconds. This reduces onboarding time from weeks to minutes.

1. “Perpetual KYC” The “old” model was to re-check a customer’s risk profile once every 1-3 years. RegTech enables “Perpetual KYC,” where AI systems monitor clients in real-time. If a client is suddenly named in a lawsuit or added to a sanctions “warning” list, the compliance team is alerted that day, not two years later at the next review cycle.
2. The ISO 20022 Multiplier Effect

The global migration to ISO 20022 (as detailed in previous reports) is a massive accelerant for RegTech. The “dumb” MT messages of the past gave compliance systems very little data to work with. The “rich, structured” data of ISO 20022 is the perfect fuel for these AI engines.

• Before: A payment arrived with a free-text field: INV 123.
• After: An ISO 20022 payment arrives with structured data fields for the Ultimate Payer, Ultimate Payee, Invoice Number, Product Code, and Country of Origin.

An AI-powered RegTech system can now perform much more sophisticated analysis, such as flagging a payment for electronics that contains product codes for “dual-use” goods being sent to a sanctioned entity. This level of automated diligence was impossible before ISO 20022.

4. The Future: Can Technology “Solve” Compliance?

No, technology will not “solve” compliance entirely. The human element—the experienced investigator who makes a final judgment call on a truly complex case—will always be necessary.

However, RegTech is solving the operational crisis of compliance. It is automating the 99% of “noise” so that expensive human experts can focus their time on the 1% of true, high-stakes risk. The future is a “human-in-the-loop” model, where AI and automation handle the massive volume, and humans provide high-level oversight and investigation.

This frees banks from their current role as “box-tickers” and allows them to become what regulators always wanted: effective, intelligent, and risk-based guardians of the financial system.