Solution for B2C fraud prevention
Identify professional litigants before you process an order
Vigilant cross-checks the litigation history of any CPF in real time. It integrates with your fraud engine or straight into the checkout — preventing habitual litigants from becoming recurring dispute costs.
The habitual-litigant pattern nobody sees
Clean score, 200 claims per year
A CPF filing 200 claims a year against retailers or insurers shows a clean Serasa score. The pattern only surfaces aggregated by small-claims court — something bureaus never query.
Indemnification is now operating cost
Large e-commerce treats disputes and lawsuits as "cost of doing business". But 80% of them come from 20% of CPFs. Identifying that 20% zeroes out most of the cost.
Orchestrated fraud slips through
Rings of habitual litigants use straw-man CPFs and seasonal patterns. Without a cross-reference on court history, every order is analyzed in isolation.
How it plugs into checkout
Buyer CPF at approval
When the user completes an order, your backend calls the Vigilant API with the CPF in parallel to your existing fraud engine.
Structured response in <2s
Vigilant returns the CPF's lawsuit volume over the last 24 months, involved courts, and list of active cases. All in JSON, ready for your engine to consume.
Your engine decides
The litigation signals enter your fraud score as additional features. You define the threshold and the approval / review / decline rule — Vigilant decides nothing, it just delivers the data.
The numbers that matter for prevention
<2s
Average latency
90% cache hit rate
12
State courts + small-claims
Ideal coverage for consumer litigation
R$ 0.10
Per query
Vs average recovered ticket
80/20
Of dispute cost
Concentrated in 20% of CPFs
Vigilant cross-checks the litigation history of any CPF in real time. It integrates with your fraud engine or straight into the checkout — preventing habitual litigants from becoming recurring dispute costs.
Score-based approval vs informed approval
- Serasa score + platform order history
- Habitual litigant approved without a flag
- Indemnification discovered months later
- Every order analyzed in isolation
- Orchestrated fraud skips past the filter
- Judicial history cross-checked at approval
- Habitual-litigant pattern identified
- Risky order flagged at checkout
- Cross-reference between related CPFs
- Direct reduction in dispute volume
Plugs into your fraud engines
REST API standardized on OpenAPI 3.1. Runs in parallel to your existing engine (ClearSale, Konduto) as an additional feature — no replacement required.
If you already consume bureaus or fraud engines via API, integrating Vigilant takes a few hours. Documentation and examples at vigilant.trackjud.com.br/api/docs.
Frequently asked questions
Legitimate interest (art. 7 IX of LGPD) for fraud prevention. Court data comes from public tribunal sources. We keep a per-request audit trail, and your checkout transparency policy covers the processing.
Cache-hit responds in <200ms. Cache-miss (data older than 2 days) returns immediate stale data and schedules an async refresh — your checkout is never blocked. 90% of queries hit cache on average.
No. It complements. You keep calling your current fraud engine and add a parallel call to Vigilant. The litigation signals come in as additional features in your engine's score.
The threshold lives in your engine, not in Vigilant. We only deliver the count and the pattern; you decide at what volume the CPF becomes a red flag. CPFs with 1-2 scattered claims are usually not a signal — the indicator is the aggregated pattern (20+ claims in 12 months, small-claims concentration).
R$ 0.10 per court queried. For an e-commerce with 100k orders/month querying 2 courts = R$ 20,000/month. For enterprise volumes, talk to sales for custom pricing.
Reduce disputes in your checkout today?
Free sandbox with 5 credits. Test with 10 real CPFs (with consent) and see the litigation pattern before integrating.