The threat is already
inside your systems

Insider payment fraud is the hardest financial crime to catch — because the person committing it already has legitimate internal access. Vyntra gives financial institutions the cross-layer visibility to detect every vector of internal fraud, before funds leave.

Book a demo
See the three threat vectors →
Insider
Threat
Compromised
Credentials
External actor using employee access
Unauthorised
Payments
Employee bypassing controls
Payment
Tampering
Altering or suppressing payments

of financial fraud losses are insider-driven

0 %

Source: Association of Certified Fraud Examiners

median time before detection

0 months

Source: ACFE Report to the Nations 2024

median loss per insider fraud case

$ 0 M

Source: ACFE Report to the Nations 2024

Why it's different

Insider fraud doesn't look like fraud.
Until it's too late.

Traditional fraud prevention controls stop external threats. Malicious insiders already know how to avoid them. They use real credentials, follow legitimate processes, and act within systems they control. Standard monitoring sees nothing unusual. Whether the risk stems from negligence, conflicts of interest, or deliberate embezzlement, catching them requires a different kind of intelligence — one that correlates employee behavior, payment flow integrity, and internal control bypass signals simultaneously.

Compromised employee credentials

Stolen or shared credentials give hackers or external actors a legitimate identity. Malware can silently exfiltrate login details without the employee’s knowledge. The system sees a valid login. Access controls raise no flag. The data breach is invisible — until it isn’t.

How Vyntra detects it

  • Unusual login location, device, or access time triggers immediate behavioral review
  • Channel fingerprinting flags deviations from the employee's typical application usage sequence
  • Machine learning models analyze employee behavior patterns and catch transactions that don't fit the employee's history — even with valid credentials

Unauthorized payments by employees

Some employees initiate payments they have no authority to make — a form of employee fraud that standard controls rarely surface. To stay undetected, they act at unusual hours, use non-standard terminals, or inject payments directly — skipping upstream approval steps entirely.

How Vyntra detects it

  • Activity anomaly detection flags payments outside normal hours, from atypical terminals, or under unusual workload patterns
  • Payment pattern deviation compares the transaction against the employee's and peer group's baseline behavior
  • Control bypass detection identifies payments injected downstream of standard approval checkpoints

Tampering with existing payments

The most sophisticated malicious insiders don’t create new payments — they alter existing ones. A changed beneficiary account. A modified amount. A suppressed transaction to erase a trail. Each edit looks routine. Only the audit trail knows otherwise.

How Vyntra detects it

  • End-to-end integrity check captures field-level values at every interception point and flags any deviation from the original instruction
  • Full data lineage records who changed what, when, and from which system — with tamper-proof export
  • Policy-based alerting fires immediately when critical fields such as beneficiary account or amount are changed mid-flow

FAQs​

What's the difference between insider threats and external threats?

External threats — like hackers deploying malware — attempt to breach your systems from outside. Insider threats originate from people who already have internal access: employees, contractors, or third-party users. Both can result in data theft, data breaches, and financial fraud, but insiders are significantly harder to detect because they operate within normal system parameters.

Motivation varies. Financial pressure, negligence are the most common drivers. The Association of Certified Fraud Examiners identifies three consistent risk factors — pressure, opportunity, and rationalization. Vyntra focuses on the opportunity layer: making it impossible for malicious insiders to act undetected, regardless of motivation.

Machine learning builds baseline employee behavior profiles across login patterns, transaction volumes, and approval workflows. Any deviation triggers a review — including the slow escalations typical of embezzlement cases. This catches anomalies that static, rule-based fraud detection systems miss entirely.

GET IN TOUCH

The threat is already inside.
Don't let it go undetected.

See how Vyntra detects all three insider fraud vectors — in real time, across every system, without disrupting your operations.

Book a demo
Talk to an expert