The PYMNTS Intelligence report “2025 State of Fraud and Financial Crime in the United States,” commissioned by Block, found that financial institutions are recognizing that fraud itself is a networked phenomenon.
Criminal groups share tools, mule accounts, compromised credentials and customer service scripts. They test defenses collaboratively, iterating on what works and abandoning what does not. In many cases, the same infrastructure is used to target multiple firms across industries.
This reality undermines the assumption that fraud can be contained within organizational boundaries, the report revealed. A weakness in one company can become an entry point into an entire sector. Synthetic identities created at a FinTech, for example, may later be used to exploit retailers, lenders or marketplaces. Phishing campaigns that succeed against one brand can often spill over to others, using shared consumer behaviors and expectations.
What makes these threats especially daunting is their adaptiveness. Fraudsters are running sophisticated operations, often using the same advanced analytics and automation tools as their targets. In response, financial institutions must deploy multilayered, intelligence-driven defenses that are capable of not just detecting but predicting and pre-empting attacks.
The arms race is increasingly evolving into a contest of network effects and learning algorithms.
Collaboration as a Resilience Multiplier
When fraud operates as a network, defense must do the same. Information sharing, coordinated response and collective learning become essential. This does not require full transparency or the abandonment of competitive advantage. It does entail a willingness to acknowledge that some threats are pre-competitive and that addressing them collectively can benefit all participants.
Early warning is one of the most powerful tools available, according to the report. Knowing what attacks are emerging, which vectors are being tested, and where defenses are failing can shorten response times.
Technology providers play a central role. By aggregating signals across clients, they can identify anomalies and trends that no single organization could see alone. When these insights are fed back into customer environments, they create a virtuous cycle of learning and adaptation.
The emphasis on collaboration is driven in part by the reality that fraudsters do not need to breach the strongest defenses if they can exploit the weakest link. As supply chains, platforms and digital ecosystems become more interconnected, vulnerabilities propagate more easily. A compromised partner, vendor or customer account can serve as a launchpad for broader attacks.
Read the report: Banks Face a Fraud Spike as Attacks Outpace Legacy Systems
Machine learning systems are now integral to fraud prevention, with 70% of institutions reporting active use of behavioral analytics and 61% using machine learning in their defenses. The combination enables a new breed of adaptive, real-time detection capable of surfacing anomalous behaviors that rules-based systems would miss.
But therein lies the report’s most troubling revelation. Nearly 1 in 5 financial institutions, especially small and regional banks, still operate without these advanced technologies.
A new playbook is emerging that prioritizes diversification and collaboration over monolithic in-house solutions, the report found.
About half of all financial institutions plan to expand the outsourcing of fraud prevention to third parties and increase their use of cloud-based fraud platforms. Others are investing in deep learning, improved customer communications, and the development of hybrid, adaptive systems.
Ultimately, modern fraud is a systemic challenge, not a siloed one, according to the report. The modernization divide can be a vulnerability for all, not just the laggards. Resilience is no longer a back-office metric; it is becoming the foundation of long-term value in a digital-first economy.
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