A new report from ValidiFI, released earlier this month, reveals compelling data on how consumer banking profiles can significantly impact payment fraud and transaction success rates.
According to ValidiFI’s Q1 2025 Bank Intelligence Quarterly Report, high-risk accounts experience returns on a staggering 62.5% of transactions, compared to just 5% for low-risk accounts. This dramatic difference highlights why financial institutions need to develop a deeper understanding of consumer banking profiles beyond standard verification processes.
“It’s not just about layering more data — it’s about layering in the right data so Financial Institutions and service providers can make smarter ‘yes’ or ‘no’ decisions in less time,” said John Gordon, CEO of ValidiFI. “FIs and service providers need a deeper, real-time understanding of consumer banking profiles to identify high-risk identities, behaviors, and activities before onboarding or sending payments.”
Rising ACH Volumes Create New Risks
The report comes at a critical time for the payments industry, as ACH volumes continue to soar across all categories, with same-day ACH payment volume exceeding $1 billion in 2024. The financial services landscape is processing unprecedented transaction volumes, including 16.38 billion consumer bill payments totaling $10.96 trillion, 8.6 billion direct deposits totaling $15.79 trillion, and 7.35 billion B2B payments totaling $58.24 trillion.
This explosive growth in digital transactions creates new opportunities but also exposes financial institutions to evolving risks that standard verification practices often miss. Traditional yes/no verification methods are becoming increasingly inadequate as fraudsters employ more sophisticated techniques and economic pressures create new consumer behavior patterns.
Bank Types and Risk Profiles
One of the report’s most striking findings involves the distribution of banking relationships among different risk profiles. High-risk consumers are substantially more likely to use neobanks, which make up 32% of their banking relationships, versus only 4% for low-risk consumers. By contrast, top U.S. banks represent 37% of low-risk consumer banking relationships but only 19% for high-risk consumers.
ValidiFI’s analysis also revealed significant performance differences between bank types. Traditional banks typically show higher payment success rates and 26% lower NSF rates. Meanwhile, neobank accounts demonstrate significantly lower payment success rates and 2.5X higher non-sufficient funds (NSF) rates compared to traditional banking institutions.
“Our analysis reveals clear trends in consumer financial institutions or service providers profiles are emerging, which may be related to or directly influenced by today’s rapidly evolving market conditions,” the report states, highlighting how economic turbulence and ever-evolving fraud patterns contribute to these trends.
High-Risk vs. Low-Risk Consumer Profiles
The report provides an in-depth comparison of consumer banking profiles across risk categories:
Low-Risk Consumer Profile:
- 2.4 bank accounts
- 2.25 email addresses
- 2.25 phone numbers
- 8.2 cleared payments
- 1.5 ACH returns
- 1.25 NSF returns
- 5% negative loan performance rate
High-Risk Consumer Profile:
- 4.4 bank accounts
- 3.2 email addresses
- 3.75 phone numbers
- 2 cleared payments
- 3.7 ACH returns
- 3.2 NSF returns
- 35% negative loan performance rate
These detailed profiles paint a concerning picture of how high-risk accounts behave within the banking system. Additional key findings include:
- High-risk accounts are 3.75X more likely to experience NSF returns compared to low-risk accounts
- Accounts with a recent NSF have 2.75X more NSFs than average
- High-risk accounts have 88% fewer successful transactions than low-risk accounts
Fraud Indicators in Banking Profiles
Perhaps most alarming are the clear indicators of potential fraud identified in the report. According to ValidiFI’s data, accounts associated with a high risk of fraud typically have:
- 12 account inquiries within 30 days
- 5 unique SSNs associated with the account holder
- 4 or more emails associated with the account holder
- 6 or more phone numbers associated with the account holder
The report highlights real-world examples of these alarming patterns, noting that some individual account holders at major banks have been associated with as many as 315 phone numbers, 307 email addresses, or 317 unique SSNs — clear indicators of potentially fraudulent activity.
“What if an account holder has 10 addresses, four emails, and five phone numbers linked to their consumer banking profile? That’s not typical and has a high potential of being associated with fraud,” the report notes, emphasizing how standard account verification would miss these red flags.
The Cost of Incomplete Information
ValidiFI’s report makes a compelling case that what financial institutions don’t know can significantly hurt their bottom line. Standard verification processes frequently miss basic account holder details that are readily available, such as:
- Additional bank accounts held by the account holder outside the originating bank
- Inconsistencies across identifiers (e.g., address and phone numbers that don’t match)
- Multiple phone numbers, addresses, emails, and SSNs associated with a single account holder
- High-frequency changes in consumer personally identifiable information (PII)
- Invalid contact information
- History of NSF and payment returns
This lack of comprehensive information leads to increased fraud potential, higher false positives, more payment returns and errors, increased friction through manual reviews, and slower overall processing of payments and disbursements.
Four Steps to Strengthen Account Authentication
The report concludes by offering financial institutions a comprehensive framework to strengthen their account authentication processes. ValidiFI recommends first auditing existing processes by analyzing onboarding and payment decisions to identify gaps and vulnerabilities, including reviewing reasons for failures and benchmarking against industry standards.
From there, institutions should identify areas for improvement by breaking down processes to pinpoint exactly where risk enters, especially considering additional insights for decision-making where standard validation falls short.
The third step involves taking a broader perspective by considering factors like customer friction and data quality, with financial institutions encouraged to ask detailed questions about how potential solutions are derived, delivered, and implemented.
Finally, the report advocates for adopting emerging best practices through a layered approach to account authentication and fraud mitigation, incorporating new and differentiated data with automated steps that are carefully adjusted for controlled friction.
“As you rethink the process, take a step back to consider other factors. Customer friction and data quality can impact everything from the customer experience to decision-making accuracy and, ultimately, the bottom line,” the report advises financial professionals.
