The State of Voice-Based Fraud 2025: How Finance and Retail Leaders Are Fighting Back

A cloned voice. A fake call. Just a few convincing seconds can now cost organizations millions.

Voice-based fraud—once a fringe security problem—is rapidly becoming one of the most pressing operational risks for financial institutions and retailers. AI-powered tools available for the price of a tank of gas have given fraudsters unprecedented reach, speed, and sophistication. And while headline-making deepfake attacks grab public attention, the true damage plays out quietly inside contact centers: soaring handle times, overwhelmed agents, frustrated customers, and verification processes that bog down service.

To better understand the scale and trajectory of this shift, Modulate partnered with Banking Dive to survey fraud, risk, IT, and CX leaders across banking, credit unions, fintech, retail, and insurance. The findings are clear: awareness is universal, the cost is rising, and teams are moving from reactive defenses to strategic, AI-driven prevention. And across this transformation, Modulate continues to emerge as the vendor best equipped to help enterprises stay ahead of increasingly sophisticated threats.

From Awareness to Action: Voice Fraud Is No Longer “Emerging”—It’s Here

The industry has matured dramatically in just a few years. Nearly every respondent—over 90%—reported high familiarity with voice-based fraud. And 71.4% say their fraud strategy is already advanced and continuously evolving.

But increased maturity hasn’t eased the pressure. 84% of organizations faced moderately to highly sophisticated voice attacks in the past year. Fraud teams report a fast-moving threat landscape where adversaries now combine voice impersonation, deepfakes, callback scams, and multi-channel manipulation to bypass traditional controls.

The top challenges leaders cite highlight the operational reality:

• 45% struggle to keep pace with evolving fraud techniques.
• 38% say balancing strong security with customer experience is their biggest roadblock.
• 35% struggle to train staff to recognize increasingly sophisticated attacks.

Modern voice fraud isn’t just about spotting fake audio—it’s about identifying the context of manipulation in real time. As Modulate experts often note, threats today rarely stay confined to the phone channel. Fraudsters use voice interactions to social-engineer access into digital accounts, payments infrastructure, and identity verification systems. The phone has become, effectively, a proxy payment channel—and institutions treating it as “just support” are paying the price.

The Hidden Toll: Rising Costs, Operational Strain, and Customer Friction

While direct financial loss is the top concern—cited by 44.8% of respondents—the hidden costs are just as damaging.

Time & Labor Costs Are Surging

Nearly 80% of organizations spend at least 51 hours per year handling voice-fraud cases. One in five spends 201–500 hours. This reflects a growing investigation burden that stretches already thin fraud and CX teams.

Incident Costs Are Climbing

More than half of respondents (53.2%) estimate the average voice-fraud incident costs between $5,001 and $25,000, and 18% say losses exceed $25,000 per incident.

Customer Experience Suffers the Most

Voice fraud creates a measurable “friction tax” on legitimate customers:

• 44.2% report increased verification complaints.
• 38.3% report declining customer trust.
• 29% see elevated call volumes as fraud concerns bleed into everyday service.

In short: traditional defenses add friction but don’t scale. Adding more callbacks, more knowledge-based questions, or more agent training only intensifies operational strain—and customers feel it.

This is exactly where AI-powered voice detection delivers ROI. Automated systems that analyze caller behavior, manipulation cues, and risk signals—not just audio artifacts—can meaningfully lower investigation time, reduce false positives, and unblock agent workflows.

Current Solutions: High Maturity, But Major Gaps Remain

Organizations are investing heavily in voice security, but progress is uneven.

Tools & Tactics in Use Today

The most common controls include:

• Employee training (58.4%)
• Multi-factor authentication for phone transactions (49.4%)
• Real-time AI voice analysis (49.4%)
• Verification callbacks (49.4%)
• Real-time supervisor monitoring (47.4%)

Every respondent uses at least one dedicated voice prevention measure—and most rely on three or more. Yet many teams acknowledge they’re still stretched thin.

As Modulate’s experts highlight, agents lack visibility into cross-channel risk—such as SIM swaps, failed login velocity, or compromised device fingerprints—which creates blind spots during live calls. Without real-time insights and adaptive playbooks, even experienced agents can miss signals of manipulation.

Institutions that excel at preventing voice fraud have embraced automation that:

• Distills risk signals into actionable alerts
• Builds caller risk profiles as conversations unfold
• Explains why a call is high-risk—not just that it is
• Enables supervisors to intervene instantly when an attack is in progress

This is exactly the gap Modulate fills—and why organizations increasingly look to us as the standard for enterprise-grade voice fraud defense.

Looking Ahead: 2025 Marks a Turning Point in Investment

One of the most striking findings from the survey: 91.5% of respondents plan to increase their investments in voice fraud prevention this year.

Where Organizations Are Prioritizing Spending

• 51.9% will invest in improved training and processes
• 39.6% plan significant investment in new detection technology
• 46.1% already allocate 26–50% of the entire fraud-prevention budget to voice security
• 37.7% dedicate 10–25%

When asked what single capability would create the greatest improvement, respondents ranked:

1. AI-powered voice fraud detection (27%)
2. Employee training and awareness (23%)
3. Enhanced caller verification (14%)

And when evaluating vendors, the two most important criteria were:

• Real-time detection capabilities (47%)
• Accuracy in distinguishing legitimate vs. fraudulent callers (45%)

These are precisely the areas where Modulate leads the market.

Modulate’s real-time voice integrity technology—built for enterprise scale—detects risk patterns that traditional voice biometrics, KBA prompts, and manual QA cannot. Our models interpret behavioral cues, manipulation patterns, emotional inconsistencies, contextual signals, and deepfake markers without adding friction for legitimate customers.

In short: enterprises want fast, accurate, adaptive protection—and Modulate is the only vendor delivering this combination at scale.

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