New LexisNexis research reveals the growing financial impact of fraud, the rise of AI-generated attacks, and why trusting digital inputs is becoming a critical business decision.

Digital transformation has made financial services faster, more accessible, and increasingly automated. Customers can open accounts, apply for loans, submit documents, and complete transactions without visiting a branch or speaking with a representative.

Unfortunately, fraudsters have embraced those same efficiencies.

According to the 2026 LexisNexis True Cost of Fraud Study, every dollar lost to fraud now costs U.S. financial services firms $5.47, up from $4.00 in 2021. For U.S. lending firms, the total cost is $4.84 per dollar of direct fraud loss.

And with digital channels accounting for 69% of reported fraud losses, the challenge is no longer simply identifying suspicious transactions. It’s ensuring that the information flowing through increasingly automated financial workflows can be trusted.

Fraud Costs Far More Than the Initial Loss

The $5.47 figure deserves attention because it captures something often overlooked in fraud prevention: the original fraudulent transaction is only part of the financial damage.

LexisNexis calculates its fraud multiplier by considering additional expenses such as recovery and reimbursement, fees, interest, replacement costs, customer acquisition, and crisis management.

In practical terms, a $100,000 direct fraud loss could translate to approximately $547,000 in total organizational costs using the study’s U.S. financial-services multiplier.

That’s not a prediction for any individual institution or incident. It’s an illustration of how quickly the broader economic impact can escalate.

The research also found that fraud significantly affects customer trust, compliance workloads, and brand reputation.

For financial institutions, the real cost of fraud extends well beyond the money that disappears. It includes the people, processes, investigations, and customer relationships affected afterward.

Digital Channels Now Account for 69% of Fraud Losses

Perhaps the most revealing finding is where fraud losses are occurring.

According to LexisNexis, websites account for 39% of fraud losses and mobile applications for another 30%. Combined, these digital channels represent 69% of the total.

Additionally, 96% of surveyed financial institutions reported an increase in fraud targeting mobile applications over the previous year.

That creates a difficult balancing act.

Financial institutions are investing heavily in digital experiences designed to eliminate paperwork, accelerate approvals, and reduce manual intervention. Customers increasingly expect financial decisions to happen in minutes rather than days.

Yet those same digital channels create opportunities for attackers to submit fabricated identities, manipulate information, and exploit gaps in automated verification.

The question isn’t whether financial institutions should continue automating.

It’s whether their verification processes are keeping pace with the speed of their decisions.

AI Is Making Fraud More Sophisticated and More Accessible

The study also highlights the growing role of artificial intelligence in financial fraud.

Surveyed organizations estimated that AI-generated techniques were involved in 19% of U.S. fraud losses and 25% of Canadian fraud losses.

AI can make fraudulent activity easier to execute and harder to recognize. Synthetic identities, convincing impersonation attempts, automated scams, and increasingly realistic digital content can challenge conventional verification processes.

For institutions that rely on uploaded information, there is another important consideration: the integrity of the files themselves.

A loan application may include income statements or supporting financial documents. An insurance claim may include photographs and repair estimates. A disputed transaction may be supported by screenshots, invoices, or other digital evidence.

These materials may appear ordinary while containing altered information, inconsistencies, reused content, or AI-generated elements.

The LexisNexis study does not quantify how much fraud originates from manipulated documents or media specifically. But its findings reinforce a broader operational concern: as fraud becomes more digitally sophisticated, verifying the identity of a customer or the legitimacy of a transaction may not be enough.

Organizations must also consider whether the submitted information supporting a decision is reliable.

Faster Decisions Are Only Better When the Inputs Can Be Trusted

Automation has become essential to financial services.

Loan origination, claims processing, underwriting, customer onboarding, and transaction investigations increasingly depend on software interpreting digital information and making decisions with limited human intervention.

The benefits are significant: faster turnaround, reduced operational costs, and better customer experiences.

But automation can also accelerate the consequences of unreliable inputs.

Consider a lending workflow that automatically extracts information from uploaded financial statements. The system may accurately read every number in a document, validate that required fields are present, and process the application exactly as designed.

What happens if the document itself has been manipulated?

Accurate extraction does not establish authenticity.

Likewise, a file that passes formatting checks may still contain fabricated information. A photograph may depict a real object but have been altered. A document may be technically readable while presenting inconsistencies that warrant further investigation.

Processing a file successfully is not the same as validating that it should be trusted.

This is why digital transformation needs more than faster document processing. It needs mechanisms for assessing the integrity, consistency, and context of submitted information before that information drives consequential decisions.

The Case for Layered, Automated Fraud Prevention

The LexisNexis study offers some encouraging findings about automation.

Organizations relying primarily on automated fraud prevention programs reported substantially higher perceived effectiveness than organizations using mainly manual processes: 89% versus 61%.

They also reported stronger improvements in fraud prevention performance and customer retention.

These are survey-reported associations, not proof that automation alone produces better results. Nevertheless, they support the value of integrated, layered approaches to fraud prevention.

Effective fraud prevention increasingly combines multiple capabilities:

• Identity authentication and account security.

• Device, behavioral, and transaction intelligence.

• Detection of suspicious or synthetic content.

• Document and media integrity analysis.

• Business-specific validation rules.

• Targeted human review when additional investigation is warranted.

No single technology can address every fraud scenario.

The opportunity is to connect these controls into workflows that detect suspicious activity without forcing every legitimate customer through a lengthy manual review.

And that matters because the LexisNexis study found that 56% of surveyed organizations reported increased customer churn associated with fraud prevention strategies.

Stronger security should not automatically mean more customer friction.

From Fraud Detection to File Validation

At Attestiv, we believe a critical part of the next generation of fraud prevention is validating the digital information that businesses receive.

Our DeepScan platform helps organizations analyze submitted photos, videos, audio, and documents using a combination of AI-powered detection, forensic analysis, metadata inspection, duplicate and reuse checks, document validation, and configurable business rules.

Rather than treating every anomaly as definitive proof of fraud, file validation provides additional signals that can inform business decisions.

Depending on the organization and workflow, those signals can help determine whether to proceed, request additional information, or escalate a submission for review.

For financial services, that can mean identifying suspicious supporting documents before they influence a lending decision, examining inconsistent evidence during an investigation, or detecting potential manipulation within materials submitted through digital channels.

File validation is not a replacement for identity verification, transaction monitoring, or established fraud controls.

It’s an additional layer of intelligence that can help organizations make better decisions about the information those systems consume.

The Next Frontier: Trustworthy Inputs for Automated Decisions

The 2026 LexisNexis findings make one thing clear: the economics of fraud are becoming increasingly difficult to ignore.

With every dollar of direct fraud loss costing U.S. financial services firms an estimated $5.47, the business case for improving fraud prevention extends far beyond the original transaction.

At the same time, digital channels dominate fraud exposure, AI-generated techniques are becoming more prevalent, and customers continue to demand frictionless experiences.

Financial institutions cannot solve these challenges simply by slowing everything down or reviewing every submission manually.

They need smarter, more selective verification.

That means evaluating not only who is submitting information and what transaction is being requested, but also whether the digital evidence supporting that request can be trusted.

As financial services become more automated, the quality and authenticity of the inputs will become just as important as the speed of the decisions.

Build Greater Trust Into Your Digital Workflows

Attestiv helps financial institutions identify suspicious, manipulated, inconsistent, or unsupported digital files before they influence important business decisions.

Discover how DeepScan can complement your existing fraud prevention and automation workflows.

Request a File Validation Review

Source: LexisNexis Risk Solutions, True Cost of Fraud Study 2026 North America: Financial Services and Lending, October 19, 2026.

The study’s fraud multipliers and AI-related loss estimates reflect the financial-services fraud landscape broadly; they are not measurements of losses specifically attributable to manipulated files or evidence of a particular return on investment from file validation.