Catch more fraud, block fewer legitimate customers.
Analysis, detection, decisions, and monitoring in one platform.
Built by a team with deep experience leading fraud prevention at fintechs and payment companies
Fragmented tools, complex configurations, and overwhelmed teams. Fraud prevention needs a new approach.
Global card fraud losses in 2024
E-commerce fraud projected for 2029 — 141% growth
True cost per $1 of fraud for merchants (chargebacks, fees, operations)
Annual fraud losses in the region — most goes undetected
True cost per $1 of fraud for businesses in LATAM
Of total fraud now happens in digital channels — surpassing physical fraud
Stop jumping between systems. Every module works together to give you full visibility into fraud across your business.
Assessments, approvals, declines, and chargebacks. Temporal activity, active rules, and list impact — all in one view.
Create complex rules in minutes without developers and manage blocklists and allowlists with millions of records. Simulate on historical data before going live.
CoreChoose how much risk to tolerate for your business. Protective, optimized, or permissive strategy — backed by data.
Detect organized fraud rings you can't see by analyzing transactions individually. Automatic groups and risk levels.
Automatically detect patterns and unusual behavior in your data — with zero configuration.
Velocity rules with configurable time windows. Minutes, hours, days — tailored to your business.
Look up any customer and get their full profile: risk score, assessment history, entity connections, and anomaly patterns. All in one view.
Chargebacks and bank outcomes feed your models and rules automatically. Your system learns from every result.
Versioned snapshots of your configuration. Restore any version with a single click.
Every business has different challenges. Here's how Frauddi solves them.
Every chargeback connects to the original transaction, the rule that approved it, and the model score.
You see exactly what failed and the system adjusts automatically with each result.
Automatically connect entities to uncover organized rings that go unnoticed when you analyze transactions one by one.
Find suspicious concentrations and patterns in your data without configuring anything. Built into the platform and ready to use.
Monitor patterns across multiple time windows with peak metrics and custom rules.
An assistant trained in the context of your operation. Create rules, analyze patterns, explain decisions — in natural language.
Frauddi's anomaly engine, available as an open source Python library. Find concentration patterns in any dataset.
# Install Dataspot
pip install dataspot
# Auto-discover patterns
from dataspot import AutoDiscovery
discovery = AutoDiscovery(df)
patterns = discovery.find_patterns()
# View results
for p in patterns:
print(f"{p.severity}: {p.description}")
# → CRITICAL: 100% — 32 records share
# the same device_id, Comision and BINBook a personalized demo and we'll show you how to reduce chargebacks, approve more good sales, and get full visibility into your operations — all from a single platform.
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