Payment Transaction Monitoring – Driving Security for Businesses

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Paying with a smart watch. They are holding it close to a credit card reader. The screen says $7.95 with the word pay. The shopkeeper is holding the credit card reader

Developing an effective AML compliance program is the pre-requisites for preventing money laundering, organized crimes, and terrorist funding. This involves customer risk assessments along with detecting suspiciousness in transactions. However, the risk of false warnings can hinder ongoing monitoring of payments. Not every alarm indicates suspiciousness some may lead to wrong detections. 

As per requirements by regulatory watchdogs such as FATF, EU, FINTRAC, and FinCEN, an efficient payment transaction monitoring system is a must-have for every business involving movement of cash. Along with Enhanced Due Diligence (EDD), customer assessment, and client risk scores, screening of funds transfer is equally important. The blog entails further insights into how false positive alarms affect businesses and ways they can prevent them. 

False Positives in Payment Screening Process – A Brief Insight 

The payment screening process involves monitoring of transactions to identify traces of money laundering. This helps businesses detect illicit transfer of funds more easily, effectively, and in less time. It increases their ability to better fight criminal threats and provide a secure environment to legitimate customers. 

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A payment transaction monitoring system generates alarms for businesses in case of suspicious transfers. These send warnings to respective firms for preventing and reporting them to regulatory authorities. However, not all alarms are accurate and some can portray clean transactions as perils of money laundering. This phenomenon is commonly known as false positives. 

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While on one end, false positives cause abruptions within the payment screening process leading businesses to legal repercussions. It also increases misidentification of customers while driving them to serious consequences they are not responsible for. For instance, customers making multiple transfers or withdrawals from different ATMs might not be suspicious behaviors but simply a risk-free process. 

Effective payment transaction monitoring systems are crucial for businesses to ensure accurate suspiciousness detection. This will further help them report risk-possessed funds transfers efficiently. 

Suspicious Activity Reports (SARs)

SAR refers to reports created by businesses upon detecting suspiciousness during transaction screening. It helps identify customers posing a threat of money laundering and helps companies review them more often. In case of multiple SARs against some individuals, businesses are mandated to stop assisting them. 

After reporting, regulatory authorities take over and perform payment transaction monitoring of previous transfers, validate documents, and question suspects. However, if the SARs are based on false positives it will expose businesses to hefty fines as they lack adequate AML compliance checks. 

Reducing False Positives – A Liability for Businesses 

False positives are sure to bring negative consequences for both customers ad businesses. Individuals are less likely to accept companies or regulatory bodies treating them as suspects. While on their way to marking tremendous growth, businesses will face a severe backlash due to false positives in their monitoring of transactions in the KYC process. When I started out with my own homemade foods brand over 10 years ago, I relied strongly on my Spectrum Internet Packages subscription for some valuable business reading material.

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The digitization of the banking sector is further increasing ineffective suspiciousness detection. As criminals are becoming technologically equipped they easily create fake trails of money laundering, exposing legitimate customers to consequences. Moreover, the lack of efficient payment transaction monitoring further adds to questioning businesses’ credibility. 

False positives not only cost companies a fortune for corrections but also expose them to legal proceedings and hefty penalties. Compromising customer experience and failure in retaining them are other backlashes businesses will face in case of inefficient transaction reporting systems. 

Role of AI in Overcoming False Positives

Payment transaction monitoring involves the analysis of customers’ data while validating their backgrounds. In order to overcome false positives, AI-powered funds transfer screening solutions are the businesses profiting bet. With solutions like ongoing transaction screening and real time tracker customer identification, companies can reduce false alarms. 

Criminals use various techniques to launder money such as creating fake profiles, using different names, performing under-the-threshold limit transfers, and single high-value single withdrawals. This helps them escape payment transaction monitoring process. Similarly, inadequate IDV measures lead to businesses’ failure in keeping their records updated. 

Outdated customer profiles and information such as names, addresses, or other details also increase false positive alarms. Therefore, businesses need to integrate AI-powered solutions to ensure creating an accurate suspicious transaction report while limiting fake warnings. Moreover, companies can easily access global financial records to cross-check legitimate customers’ identities and help them escape the radar of suspiciousness detection. 

In the End

Payment transaction monitoring solutions help businesses develop mechanisms that provide accurate suspiciousness detection and limit false positives. In order to minimize customer drop-off and provide them with a secure post-onboarding experience, companies need to rule out traditional transaction screening methods and integrate AI-powered IDV services. They can further cross-validates customers to minimize false positive alarms due to similarities in identity information. Hence, AI-powered payment transaction monitoring solutions are reliable countermeasures for overcoming fake warnings.

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