Leveraging new technology focusing on data and machine learning can help reduce fraud and friction.
Consumers and businesses increasingly expect payments to move quickly and securely, anywhere in the world. As the speed of payments increases and settlement happens in real time, fraud and risk management practices must be adapted to protect credit unions and members.
Consider these statistics:
- Faster and real-time payments could double in transaction volume by 2023, according to the 2021 Mercator U.S. Faster Payments Forecast.
- Seventy-four percent of organizations were targets of an attempted or actual payments fraud attack in 2020, according to the 2021 AFP Payments Fraud and Control Survey Report.
- Consumers reported losing more than $5.8 billion to fraud in 2021, a 70% increase over the prior year, according to the Federal Trade Commission.
Clearly, credit unions must protect themselves and their members from the threat of real-time fraud risk. This requires a fraud risk management approach designed for real time, employing up-to-date processes and technologies to meet increasing customer expectations while managing financial crime risk effectively.
Keep Pace With Members and Regulations
Members expect quick and seamless transactions. They want to initiate real-time payments whenever and wherever they choose with immediate confirmation that the payment is complete. If there is an issue, they want immediate resolution.
The move to real-time payments requires credit unions to make support and fraud teams available 24/7, both to assist members with their needs as well as detect and protect them from threats that emerge outside of traditional business hours—a growing consideration in an increasingly global economy.
In this dynamic business and risk environment, credit unions need a fraud solution to help them make timely decisions that significantly improve fraud detection rates, reduce false positives, optimize operational costs and drive efficiency and customer satisfaction.
Employ a Holistic Approach
With real-time payments, the risk of loss is different than with other types of transactions. Once a real-time payment has been accepted by the payee’s financial institution, the transaction is often considered irrevocable.
While real-time payments are applicable across a broad range of transactions, fraud detection systems have historically been designed for a specific type of transaction. This siloed approach can limit fraud detection and is not necessarily the best approach for real-time payments monitoring. Effective real-time payment fraud prevention requires solutions able to detect many possible types of fraud across all electronic funds transfer channels and payment origination mechanisms.
These solutions must be fully connected and able to utilize data across payment types and channels to help analyze, detect and prevent fraud. Threats continue to evolve and increase in number, and credit unions cannot afford to implement fraud prevention tools in a piecemeal fashion.
So what works? Leveraging new technologies focusing on data and analytics using machine learning can help manage risk and reduce false alerts. This assists credit unions in balancing risk management obligations with the delivery of a better member experience, which is critical in the highly competitive financial services environment.
Consider These 3 Innovative Risk Strategies
1. Get smarter with data. With ISO 20022 being adopted as the industry standard for electronic data exchange between financial institutions, real-time payments can carry much more data. While this additional data can help determine if a real-time transaction is fraudulent, the analysis can take time using traditional fraud detection systems that aren’t equipped to process all the incoming data and utilize it to tackle fraud.
The ability to quickly consume and analyze huge amounts of data covering all channels, transactions and multiple convergence points—and to respond effectively—is critical to managing fraud risk.
In addition, sharing information about fraud incidents across the broader community of financial institutions will provide the volume of data needed to effectively fight real-time payment fraud. Technology providers can help facilitate this sharing and create consortium-based models that enable financial institutions to learn from collectively shared data. Approaching the fight against financial crime as a community issue helps protect all credit unions and their members.
2. (Machine) learn over time. Credit unions can leverage these broader data sets to their advantage by adopting machine learning technologies. These technologies can perform millions of fraud checks within seconds and continuously learn from the data to become more accurate and effective over time.
By implementing solutions that incorporate machine learning, credit unions will be in a strong position to combat emerging threats while continuing to provide the seamless interactions that members want.
3. Adapt to changing landscapes. Given the increasingly sophisticated and continually evolving nature of the threats impacting financial services providers, it is impossible to predict the patterns and types of fraud that can affect real-time payments. However, credit unions can prepare for whatever comes their way by adopting solutions that offer protection for current risks with the flexibility to adapt as the threat landscape changes.
Behavioral analytics add a unique layer of protection over traditional techniques by focusing on typical activity to create a baseline of what should be allowed or challenged. Anomalous deviations from this baseline are used to identify new fraud attacks as they emerge.
The combination of the ability to analyze huge data sets in real-time and the application of behavioral analytics enables institutions to make more accurate and timely decisions, detecting and preventing fraud and reducing friction while continually adapting to the changing behavior of members and financial criminals.
As credit unions assess new solutions for combatting fraud in real-time, they may benefit from the experience of innovative technology providers. With deep expertise in technology, data science, analytics and integration, these providers can become valued and trusted partners to navigate fraud prevention in a real-time world.
Dharm Patel is VP/general manager/fraud & financial crime for CUES Supplier member Fiserv, Brookfield, Wisconsin.