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Consortium Analytics and Machine Learning: A New Frontier in Check Fraud Detection

July 11, 2024 by Colin Parsons

The financial industry has been tackling the issue of check fraud for many years using outdated technology and siloed approaches.

With the increase in check fraud, estimated at over $26 billion in losses globally, we need a new solution that uses the latest in technology and brings together a broad collective of data points in an optimal way – leading to more fraud detected with fewer false positives.

Trained on True Check Fraud

While machine learning is an industry buzz word, to truly succeed in this field requires access to a broad range of quality data to train the algorithms to make accurate predictions.

Unique to Nasdaq Verafin, our consortium network provides a rich source of data to train our check fraud machine learning analytic. With thousands of customers, 575 million profiled counterparties, a library of billions of check image examples with many confirmed check fraud, our solution combines behavioral profiles, image analysis, and insights into the payer and payee for a complete check fraud solution.

Machine Learning Model – Quantity In, Quality Out

The power of machine learning is evident when working in tandem with consortium data providing insights into the deposit-side risk. Nasdaq Verafin offers a single solution to the pervasive and growing problem of check fraud that ranges from simple to complex typologies.

Consortium data gives Nasdaq Verafin’s models the ability to see the full picture of a transaction, as the collective network of 2500 financial institution’s data helps complete the missing picture on the payee side, uncovering hundreds of data points relevant to various fraud typologies. By leveraging this massive set of confirmed examples of check and deposit fraud, our models learn how to effectively harness hundreds of data points seamlessly and accurately identify fraud.

Through our years of experience, we have constantly seen machine learning models optimized for high detection rates and low false positives. Equipped with Nasdaq Verafin’s risk scoring, our financial institution partners control the balance between the number of alerts identified versus caught fraud – a customized solution tuned to the risk profile of your institution.

Multi-Channel: Stop Fraud Across Your Institution

Nasdaq Verafin’s use of machine learning is not limited to check fraud. The combination of our consortium network and progressive machine learning models can be applied across all fraud typologies and channels such as wire, ACH, and instant payments. Fraudsters are effective opportunists, using any payment channel and fraud play at their disposal; by utilizing a holistic fraud approach that leverages data across all channels, our solution provides superior results for any given fraud typology.

The collective power of insights and behaviors captured from across the financial industry amplifies and speeds up fraud detection for financial institutions, reducing pressures on internal resources, lowering false positives, and allowing for greater efficiencies in investigations of high-risk alerts.

Having been an early innovator in machine learning and artificial intelligence, Nasdaq Verafin’s 20 years of technical expertise enables us to develop leading anti-financial crime solutions that remain a step ahead.

About the Author: 

COLIN PARSONS
Associate Vice President — Head of Fraud Product Strategy at Nasdaq Verafin

Colin Parsons spearheads the strategic development of technology solutions to combat fraud at Nasdaq Verafin. Throughout his time with the company, Colin has worked as a development team lead, software developer and in product marketing. Applying the knowledge gained through his roles and experiences, Colin is focused on using technology to solve the hard problems that are persistent within the fraud space.

Nasdaq Verafin provides cloud-based Financial Crime Management Technology solutions for Fraud Detection, AML/CFT Compliance, High-Risk Customer Management, Sanctions Screening and Management, and Information Sharing. More than 2,500 financial institutions globally, representing more than $8T in collective assets, use Nasdaq Verafin to prevent fraud and strengthen AML/CFT efforts. Leveraging our unique consortium data approach in targeted analytics with artificial intelligence and machine learning, Nasdaq Verafin significantly reduces false positive alerts and delivers context-rich insights to fight financial crime more efficiently and effectively. To learn how Nasdaq Verafin can help your institution fight fraud and money laundering, call 1-877-368-9986.