Easy access to online payments, including money transfers, makes the need for sanction screening and AML compliance critical. Fines for AML/CFT non-compliance can be significant.
For SME’s, credit unions, and Fintech companies, finding efficient and affordable solutions had been out of reach… until now. RegTech innovators are taking advantage of AI, ML (machine learning), and NLP (natural language processing) to deliver compliant screening solutions that are fast, affordable, and low friction for smaller businesses.
The False Positives Challenge
There are a few factors that slow down the timing of approvals during screening. A main one is the volume of false positives exposed. This is a nightmare for companies looking to improve their customer acquisition. They win customers by advertising faster approvals in opening accounts and managing transactions.
When the volume of false positives spirals out of control, unexpected delays extend from a few days to weeks. Moreover, delays in customer onboarding and transaction processing do not just cause frustration for the customer but also for the company.
Online customers are not sticky, and according to a study done by Forbes, customer experience is perhaps the biggest reason why customers switch vendors.
Machine learning and AI
With AI and machine learning becoming an essential part of the compliance world. Companies can now manage the volume of false positives with autonomous clearing of alerts. AI based decision systems use a rule-based approach and built-in learning models to filter out the data.
Once the AI learns of a particular alert that is cleared manually, it will learn the behavior and create new rules to clear false positives automatically.
Decision systems for automated clearing of false positives can be a business savior. However, replacing human intelligence with artificial intelligence does not come without risks. You need to follow best practices to avoid auditor scrutiny and avoid penalties for non-compliance.
For example, one of the system’s most important features is that it must be auditable and provide transparent proof of decision that is easy to read and track. For more on best practices for AI-based decision systems, download this whitepaper from KYC2020.
An ongoing process
Ongoing monitoring of customers is a requirement for most AML compliance regimes since databases and sanction lists update almost daily.
Algorithms are always learning new alerts and rules. Manual processes are no match against AI-based systems for ongoing monitoring of customer lists. Development of AI, Machine Learning (ML), and Natural Language Processing (NLP) in AML compliance applications reduces the need for human reviews of false positives. This seemingly simple addition shortens the time required to get approvals.
The best outcome for smaller companies is to move towards a tech-based compliance approach for their customers. This will help reduce the possibilities of fines for non-compliance and make it cost-effective for companies to carry out compliance.
KYC2020 provides affordable and effective AML compliance solutions that take advantage of latest technologies. KYC2020 is the best in class source for global Sanction, PEP, HIO, and Adverse Media data. We have designed our AI and NLP based screening and ongoing monitoring solutions to eliminate false positives and reduce manual work.