Topic starter
12/07/2026 12:26 pm
TL;DR: Fraud losses continue to rise, with American businesses losing more than $12.5 billion in 2024 and global losses nearing $50 billion annually, while roughly 80% of that loss came from attempted payment fraud, according to Sift. The real control question is no longer whether to buy a fraud platform, but how to govern identity signals, decision transparency, and friction without weakening customer trust.
Editorial analysis by NHI Mgmt Group, based on content published by Sift: “7 Best Fraud Prevention Software Platforms for Protecting Your Business”.
By the numbers:
- In 2024, American businesses lost more than $12.5 billion to fraud.
- Global fraud losses hit nearly $50 billion per year.
- Around 80% of global fraud losses came from attempted payment fraud.
Key questions
A: Payments teams should treat identity proofing and authentication as continuous infrastructure, not a one-time login step.
Q: Why do identity signals matter in fraud prevention models?
A: Identity signals matter because fraud rarely appears as a single event.
Q: What breaks when fraud systems cannot explain their decisions?
A: When fraud systems cannot explain decisions, teams lose the ability to distinguish genuine fraud from legitimate customer behaviour, tune thresholds responsibly or defend outcomes to customers and regulators.
Practitioner guidance
- Strengthen identity signal ingestion Ingest device, network, behavioural, and account history signals into fraud decisioning so suspicious activity is evaluated in context rather than by static rules alone.
- Tune thresholds by business model Set different friction levels for high-value, low-volume flows versus low-value, high-volume flows so customer experience matches fraud tolerance.
- Require explainable risk scoring Use fraud tooling that can explain why a transaction or account was flagged, then review those explanations during model and rule tuning.
Bottom line: Fraud prevention is moving toward identity-rich decisioning because static rules cannot keep pace with automated abuse and account takeover.
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12/07/2026 12:40 pm
Identity signals are now a governance layer, not a feature set. Fraud controls increasingly make decisions from device, behavioural, and account context, which means identity telemetry has become part of the control plane. That shifts responsibility from simple detection accuracy to decision governance, threshold setting, and explainability. Practitioners should treat fraud decisioning as an identity policy problem with direct business impact.
A few things that frame the scale:
- U.S. fraud losses are projected to reach $40 billion by 2027.
A question worth separating out:
Q: Should fraud, IAM, and platform security teams use the same trust signals?
A: They should use a shared trust model, but not necessarily identical thresholds. IAM, fraud, and security teams need a common view of account ownership, device context, and behavioural legitimacy so that policy, detection, and escalation stay aligned when abuse crosses team boundaries.
👉 Read our full editorial: Fraud prevention software now hinges on identity signals and scale