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Beyond the Checkbox: How to Fight Fraud with Automated KYB

The UK’s small and medium-sized enterprises (SME) sector is the backbone of the UK economy. Yet, for banks and fintechs, it also represents a complex and growing frontier for financial crime. As criminals use more sophisticated methods to create fraudulent business accounts for money laundering, the pressure on FinCrime professionals has never been greater. 

The traditional response? Adding more manual checks and hiring more analysts - is no longer sustainable. It’s slow, expensive, and creates a frustrating onboarding experience that turns legitimate customers away. 

How can you effectively fight fraud and stay compliant without overwhelming your team and alienating good customers? The answer lies in moving beyond the manual checkbox approach to a fully automated and orchestrated Know Your Business (KYB) process. 

The Challenge: The Manual Overload of Business Onboarding 

For any institution, onboarding a business is far more complex than onboarding an individual. It requires verifying multiple data points: from company registration details and director information to identifying ultimate beneficial owners (UBOs). 

For FinCrime teams, this process is fraught with challenges: 

  • High Risk of Sophisticated Fraud: Criminals are adept at creating convincing but fake business profiles.
  • Manual Inefficiency: Analysts spend hours cross-referencing data from multiple sources, slowing down business onboarding from days to weeks.
  • Regulatory Pressure: Meeting stringent AML/KYC compliance in the UK is non-negotiable, and the risk of fines for non-compliance is severe. 

This manual overload creates a bottleneck that not only increases operational costs but also allows sophisticated criminals to slip through the cracks. 

 

The Solution: Automation and Orchestration in Action 

To solve this challenge at scale, a new approach is needed. This is where the power of a unified trust orchestration platform comes in—a strategy successfully demonstrated through Signicat's partnership with Visa. 

To help Visa’s financial institution clients streamline the onboarding of SMEs, Signicat developed a single, automated solution. By integrating hundreds of data sources for KYC, KYB, and AML checks into one platform, the process was transformed. 

The results speak for themselves: 

  • 80% Automation Rate: The majority of business onboarding decisions were automated, freeing up analysts to focus only on the highest-risk, most complex cases.
  • Onboarding from Days to Minutes: The entire KYB and AML compliance process was accelerated, creating a seamless experience for legitimate SMB customers. 

Three Pillars of Effective AML, KYC and Fraud Prevention 

The success of this approach is built on three key pillars that any UK fintech or bank can adopt for world-class financial crime prevention: 

  1. Unified Data Sources: Instead of manually querying separate systems for company data, director checks, and PEP/sanctions screening, an orchestrated platform does it all in a single, automated workflow.
  2. Risk-Based Automation: The platform can be configured with a flexible, no-code rule engine. This allows you to define your risk appetite and automate decisions for low-risk applicants while escalating high-risk cases for expert review.
  3. Continuous, Real-Time Monitoring: Fraud and risk are not static. An automated solution provides ongoing monitoring of businesses, alerting you to any changes in status, directorship, or risk profile long after the initial onboarding is complete. 

 See AML/ KYC Orchestration in Action at FFECON 

The fight against financial crime is a critical one, but it doesn’t have to be a choice between security and growth. The principles of automation and orchestration discussed here are powered by Riskflow, Signicat’s trust orchestration platform. 

Want to see how you can build an automated, risk-based KYB workflow in minutes? 

The Signicat team will be at FFECON. Stop by our booth (17) for a live demo of Riskflow orchestration. We’ll show you how to connect data sources, build custom rules, and automate decisions to fight financial crime more effectively while onboarding good customers faster.