Explainable AIscam detection builtfor platforms and compliance teams.

Turn vague AI alerts into clear, actionable insights. Stay compliant, protect your users, and scale your trust infrastructure.

Why use Riskor?

Built for transparency and scale — explainable decisions, policy alignment, and real-time performance.

Aligned with global policies

BoostLayer mapped to global policies — audit-ready and defensible.

Reasoning without LLM

Industry-leading clarity, powered by deterministic rules.

Real-time API

average 100ms responses for moderation at production scale.

Compliance-ready, designed from documented patterns

Riskor’s fraud-language framework is designed from publicly documented scam patterns by regulators (FTC, SEC, FCA) and the EU DSA, plus major platform guidelines. Each decision produces explainable, audit-ready rationale — without black boxes.

  • Traceable: each flag includes category, highlighted cues, and public source references (pattern-level).
  • Defensible: white-box reasoning your compliance and legal teams can audit.
  • Operational: exportable reports and event logs for review workflows.
FTC
Federal Trade Commission
US
SEC
Securities and Exchange Commission
US
EU DSA
Digital Services Act
EU
FCA
Financial Conduct Authority
UK
IC3
FBI Internet Crime Complaint Center
US
FINRA
Financial Industry Regulatory Authority
US
ACCC
Australian Competition & Consumer Commission
AU
Meta
Community Standards
Global
DISB
Department of Insurance, Securities and Banking
US-DC
References from publicly documented patterns • Updated periodically
Audit-ready
INDUSTRY SCENARIOS

LLM-free moderation for high-risk platforms

Deterministic, audit-ready outcomes across fintech, marketplaces, social, and messaging.

Fintech

Investment scams, fake dashboards, payment manipulation.

  • Mapped to SEC / FTC
  • Deterministic flags (LLM-free)
  • Review-friendly exports

Marketplaces

Fake listings, impersonation, refund/chargeback abuse.

  • Real-time API <300ms
  • Audit-ready reasoning
  • Works with trust pipelines

Dating & social

Romance scams, grooming, crypto baiting.

  • Policy-mapped outputs
  • Human-readable rationales
  • Early-risk signals

Messaging

Spam rings, multi-turn persuasion patterns.

  • Conversation-level signals
  • Scales to high throughput
  • LLM-free at runtime

Riskor vs. Generic LLM

Deterministic clarity for high-risk content moderation. Compare two enterprise-critical dimensions: policy mapping and static reasoning.

Compliance Accuracy
Riskor
0%
Generic LLM
0%
Static Reasoning Ability
Riskor
0%
Generic LLM
0%
Benchmark: “Generic LLM” = prompt-only evaluation without domain-specific constraints. Performance values shown in %. Riskor metrics are set via props.
MEASURABLE OUTCOMES

Cut compliance costs while increasing review speed and accuracy

Riskor’s explainable fraud-language detection reduces manual hours, prevents costly false positives, and aligns with international regulations — without scaling headcount.


Lower Review Costs

Automate repetitive checks so cost per review drops 30–50% as volumes grow.

Less Manual Review Time

BoostLayer highlights cues and rationale instantly, enabling your team to make faster, informed decisions — without removing your final review control.

Reduce Regulatory Risk

Produce explainable, audit-ready outputs mapped to publicly documented patterns (FTC, SEC, FCA, EU DSA), so your compliance team can confidently decide whether to approve, flag, or block content.

Secure your platform with BoostLayer

Mapped to enforceable policies. <300ms at edge. Exportable reasoning.