FintechRisk

Risk Scoring

Raise risk scores for identities with prior breach exposure before approving transactions.

Start with 500 free creditsDocumentation

Email breaches · 1 credit per lookup · no monthly fee

Identity risk

78/100
4 prior breaches · manual review

The problem

An identity with four prior breaches behind it is statistically riskier than a clean one, leaked credentials feed account takeover and synthetic identity fraud. Most risk engines can't see this signal at all.

With Encrata

Add breach exposure as a feature in your risk model. One credit per check returns breach count, recency and exposed data classes, a high-signal input for step-up verification on risky transactions without adding friction for clean identities.

How it works

1

Send the address

Call the breach endpoint with an email address, one-off for a signup check, or on a schedule for monitoring.

2

We check known breaches

Encrata searches disclosed breach data and returns every breach the address appears in, when it happened, and what leaked.

3

Respond to exposure

Alert the user, raise a risk score, force a reset or require MFA, the full breach history is one credit away.

One call, structured answer

Risk Scoring runs on the email breaches lookup at 1 credit per lookup. Same API key, same JSON shape as every other Encrata lookup.

  • Full breach history, names, dates and exposed data classes per breach
  • 1 credit per check, so continuous monitoring stays affordable
  • New-breach detection turns a public leak into a same-day security response
  • Works for one address or your whole domain
Terminal
curl -X POST "https://encrata.com/api/agent/breaches" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"email": "sam@corp.com"}'
response.json
{
  "email": "sam@corp.com",
  "breached": true,
  "breach_info": {
    "breach_count": 2,
    "services": [
      { "name": "LinkedIn", "breach_date": "2012-05-05",
        "data_types": ["Email addresses", "Passwords"] }
    ],
    "exposed_data": ["Email addresses", "Passwords"]
  },
  "credits": 1
}

Three features for the model

Feed three features into the model: breach count, recency of the newest breach, and whether passwords were among the exposed data classes. A five-year-old username leak and a last-month password dump are different risks and should score differently. Run the check at account creation and at high-value transaction time, identity risk isn't static.

Step-up only where it is earned

The operational win is precision in step-up: instead of adding friction for everyone, you challenge the identities whose credentials are demonstrably circulating. Fraud teams typically find breach exposure correlates strongly with account-takeover attempts, making it one of the cheapest high-signal features you can add to an existing model.

More email breaches use cases

View all

New breach: DataCo

Your email was exposed · just now

Secure account

Breach Alerts

Warn users the moment their email address shows up in a newly disclosed data breach

CybersecurityMonitoring
Breach affects 3 users
Password resets sent

Password Reset

Trigger targeted password resets when a breach relevant to your users becomes public

SaaSSecurity
sam@corp.comBreached
MFA now required
•••

MFA Enforcement

Require stronger authentication for accounts whose emails appear in known breaches

BankingAuthentication
Start with 500 free credits
$curl https://encrata.com/api/agent/lookup -H "Authorization: Bearer YOUR_API_KEY" -d '{"e": "satya@microsoft.com"}'