The Need for Speed: How to Mitigate Fraud in Real-Time Payments
To prevent fraud in real-time payments, banks and financial service providers will have to move from a post-transaction batch-based analysis and reporting model to a contextual, early warning-based preventive framework supported by advance analytics and data intelligence.
Real-time payments have been described as the biggest change to the payments landscape since the 1970s. Financial institutions and disruptive FinTech players are racing to gain an advantage by meeting increased consumer demand for fast, seamless payments anytime, anywhere. But while real-time payments promise a more streamlined customer experience, they also offer opportunities for fraudsters to rapidly move funds and escape detection.
The challenge for banks is to meet rising customer expectations while spotting and blocking malicious activity without impacting the payments experience. To do this, they must move to an advanced analytics-based solution that flags fraudulent attempts in real time.
To meet consumer demand for real-time transactions, businesses are gravitating towards digital and mobile payment methods such as mobile wallets, P2P payment platforms, and crypto-currency. The variety of online tools offered around the world is helping drive global commerce and reduce firms’ reliance on expensive payment methods like cash and checks. In addition, real-time payments have opened up a wealth of new possibilities for consumers, enabling them to instantly pay friends, reduce the risk of late payments and overdraft fees, buy digital content instantly, make emergency purchases, and much more.
When Fraud Goes Real Time
For all the convenience that real-time payments bring to consumers, they also introduce new risks for providers. Scammers can hijack digital accounts and trick users into making irrevocable payments and then take funds before the victim knows what happened. The speed with which stolen funds can then be transferred through mule accounts also makes investigations difficult.
Consider the following:
Authorized push payment (APP) fraud: A fraudster tricks a user into making a payment to what they believe is a legitimate company, such as buying goods on an e-commerce marketplace. The real-time transfer of funds means that there is less time for the customer to reflect on their payment and for banking systems to spot the scam.
Account takeover fraud: The increased use of digital payment platforms results in exposure to specific tactics for furthering identity fraud. These can include the use of stolen or breached identity data, phishing attempts, and the installation of malware on end-user devices to crack existing accounts and hijack sessions. Nearly $17 billion was stolen via identity fraud in the US in 2017 – an all-time high, according to Javelin Strategy & Research.1 Traditional fraud systems which rely on batch-based analysis are poorly equipped to spot these real-time scams until it’s too late.
Account creation fraud: Scammers have also become adept at using data obtained from breaches and phishing to open new accounts using either stolen or synthetic identities. The latter can be particularly hard to spot and has been described by the FTC as the “fastest-growing form of identity theft.”2 With faster payments, money can be moved rapidly from and through these accounts to throw investigators off the scent.
Money laundering: A key part of the payments fraud and cybercrime lifecycle is being able to move stolen funds quickly, to confound attempts by bank teams and law enforcement to trace the trail back to the perpetrator. Real-time payments make things difficult for investigators, especially given the growing number of individuals knowingly or unknowingly conscripted into this kind of money laundering.
Moreover, the cross-border nature of many real-time payments makes it challenging to detect fraud when it happens. Without a global regulatory body, cybercrime groups are exploiting less rigorous approaches to fraud management in emerging countries to commit big heists.
A Better Approach
Banks and financial services providers still using batch-based analysis and reporting to combat fraud need a new approach. These systems are no longer fit-for-purpose in the modern era of real-time payments. The focus instead should be on finding systems to intelligently spot suspicious activity in real time without adding the kind of extra friction that would negate the benefits of instant transfers.
Simility combines self-optimizing machine learning models and flexible data ingestion to offer real-time fraud intelligence. The result is a highly effective fraud detection platform to help block fraud and allow legitimate activity to flow unhindered, preserving the customer experience and all the benefits of instantaneous digital payments.
1. 2018 Identity Fraud Study, Javelin Strategy & Research, https://www.javelinstrategy.com/press-release/identity-fraud-hits-all-time-high-167-million-us-victims-2017-according-new-javelin
2. The Changing Face of Identity Theft, FTC, https://www.ftc.gov/sites/default/files/documents/public_comments/credit-report-freezes-534030-00033/534030-00033.pdf
Latest posts by Hassan van de Riet (see all)
- Patching Problems Perpetuate Fraud Challenges - November 1, 2019
- The Need for Speed: How to Mitigate Fraud in Real-Time Payments - April 2, 2019