Financial institutions have long treated customer data as a proprietary asset, but a new PYMNTS report, “Fighting Fraud and Finding Trust Amid Banking’s Data Deluge,” suggests the bigger competitive advantage may come from knowing when to pool information.
In a digital economy where fraud evolves by the week and government datasets are shrinking, banks and credit unions are discovering that collaboration, not just competition, can make the difference between trust gained and trust lost.
The study is part of the PYMNTS “Searching for Reliable Signals in Banking’s New Data Reality” series, which examines how banks, credit unions and FinTechs are rethinking data strategies as artificial intelligence (AI) takes on a larger role.
The report draws on perspectives from executives at Velera, Entersekt and Concora Credit, who warn that financial crime now requires “a team sport” approach.
Their common message: data remains indispensable, but its reliability depends on balance — blending historical records with real-time signals, human oversight with machine intelligence, and institutional rivalry with shared intelligence.
- Fraud is forcing speed onto the system. Entersekt’s Pradheep Sampath said traditional government feeds — from the Fed’s fraud reports to FinCEN filings — are too slow to meet today’s threats. Nearly all respondents in the series pointed to the need for blending historical bureau data with behavioral analytics, device fingerprints and geolocation markers that can detect anomalies in the moment.
- Collaboration is edging out isolation. Velera’s Jeremiah Lotz highlighted how consortium models aggregating data from thousands of credit unions are already producing stronger defenses. A striking 100% of the executives interviewed described fraud management as “competitive-neutral” — one of the few areas where rivals can safely share signals without ceding advantage. Privacy-enhancing tools like encryption and federated data models were cited as the bridge.
- Alternative data is gaining ground. Concora Credit’s Kyle Becker reported that layering in about a dozen new alternative datasets each year improves both underwriting and fraud detection. Cash-flow underwriting in particular was singled out as a tool that both widens credit access and strengthens defenses. The report notes that institutions finding even “one or two” viable new data sources annually can compound improvements in risk management over time.
What emerges from these findings is a shift in mindset. Fraud prevention is no longer seen only as an arms race of better models and faster alerts, but as an ecosystem challenge in which financial institutions rise or fall together.
The executives interviewed by PYMNTS stressed that no single dataset, no single tool, and no single firm can fully address fraud. Instead, they called for “layered intelligence” — a mix of bureau records, first-party transaction histories, commercial datasets and real-time signals, deployed with governance.
In a landscape where consumer expectations for safety and convenience continue to climb, the line between fraud defense and customer trust has blurred. As the report concludes, reliable signals are not found, but built — through cooperation, governance and a willingness to see data not as a walled-off asset but as a shared defense mechanism.
Source: https://www.pymnts.com/