United States — Driver License Barcode Cross-Check

The United States Driver License Cross-Check API combats physical document fraud and synthetic identity fabrication by mathematically correlating data from the physical front of an ID with the encoded AAMVA PDF417 2D barcode on the reverse side.

In identity fraud schemes, bad actors frequently alter visual front-side text or photos while leaving the reverse barcode untouched, or fabricate mismatched barcodes. This service performs subfield-by-subfield matching across license number, full name, date of birth, issuing jurisdiction, and expiration date, producing deterministic field match scores, discrepancy alerts, and an overall authenticity verdict.

---

API Reference

Endpoint

POST https://api.verifik.co/v2/usa/driver-license/cross-check

Cross-examine user-supplied or front-OCR identity fields against the cryptographic and structured payload of the rear AAMVA barcode.

Headers

Name	Value	Description
Content-Type	application/json	Request payload format
Accept	application/json	Response format
Authorization	Bearer <token>	Client JWT authentication token

Parameters

Parameter	Type	Required	Description
licenseNumber	string	Yes	License or document number printed on front of card (e.g., D1234567).
firstName	string	Yes	Subject first name (e.g., JOHN).
lastName	string	Yes	Subject last name or surname (e.g., DOE).
backImage	string	Conditional	Base64-encoded image or public HTTPS URL of rear barcode. Required if rawBarcode is omitted.
rawBarcode	string	Conditional	Raw ANSI/AAMVA PDF417 barcode text payload. Required if backImage is omitted.
dateOfBirth	string	No	Date of birth in YYYY-MM-DD format (e.g., 1990-01-15).
state	string	No	Expected two-letter US state abbreviation (e.g., CA).

---

Request

Node.js / JavaScript

import axios from "axios";

const options = {
  method: "POST",
  url: "https://api.verifik.co/v2/usa/driver-license/cross-check",
  data: {
    licenseNumber: "D1234567",
    firstName: "JOHN",
    lastName: "DOE",
    dateOfBirth: "1990-01-15",
    state: "CA",
    backImage: "https://cdn.example.com/id-back-california.jpg",
  },
  headers: {
    "Content-Type": "application/json",
    Accept: "application/json",
    Authorization: "Bearer <your_token>",
  },
};

try {
  const { data } = await axios.request(options);
  console.log(data);
} catch (error) {
  console.error(error.response ? error.response.data : error.message);
}

Python

import requests

url = "https://api.verifik.co/v2/usa/driver-license/cross-check"
headers = {
    "Content-Type": "application/json",
    "Accept": "application/json",
    "Authorization": "Bearer <your_token>"
}
payload = {
    "licenseNumber": "D1234567",
    "firstName": "JOHN",
    "lastName": "DOE",
    "dateOfBirth": "1990-01-15",
    "state": "CA",
    "rawBarcode": "@\n\u001e\rANSI 636014080002DL00410278ZA..."
}

response = requests.post(url, headers=headers, json=payload)
print(response.json())

cURL

curl -X POST "https://api.verifik.co/v2/usa/driver-license/cross-check" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer <your_token>" \
  -d '{
    "licenseNumber": "D1234567",
    "firstName": "JOHN",
    "lastName": "DOE",
    "dateOfBirth": "1990-01-15",
    "state": "CA",
    "backImage": "https://cdn.example.com/id-back-california.jpg"
  }'

---

Response

200 (Verified Match / Confirmed)

{
  "data": {
    "verdict": "confirmed",
    "isAuthentic": true,
    "matchScore": 1.0,
    "fieldScores": {
      "licenseNumber": 1.0,
      "firstName": 1.0,
      "lastName": 1.0,
      "dateOfBirth": 1.0,
      "state": 1.0
    },
    "discrepancies": [],
    "barcodeData": {
      "iin": "636014",
      "issuerName": "California",
      "licenseNumber": "D1234567",
      "firstName": "JOHN",
      "lastName": "DOE",
      "dateOfBirth": "1990-01-15",
      "expirationDate": "2028-01-15",
      "isExpired": false,
      "isRealIdCompliant": true
    }
  },
  "signature": {
    "dateTime": "October 31, 2026 12:00 AM",
    "message": "Certified by Verifik.co"
  }
}

200 (Discrepancy / Tampering Suspected)

{
  "data": {
    "verdict": "discrepancy",
    "isAuthentic": false,
    "matchScore": 0.65,
    "fieldScores": {
      "licenseNumber": 1.0,
      "firstName": 0.3,
      "lastName": 1.0,
      "dateOfBirth": 0.0,
      "state": 1.0
    },
    "discrepancies": [
      {
        "field": "dateOfBirth",
        "expected": "1990-01-15",
        "barcodeValue": "1985-06-20",
        "message": "Date of birth in barcode does not match input value."
      },
      {
        "field": "firstName",
        "expected": "JOHN",
        "barcodeValue": "JONATHAN",
        "message": "First name variation exceeds similarity threshold."
      }
    ],
    "barcodeData": {
      "iin": "636014",
      "issuerName": "California",
      "licenseNumber": "D1234567",
      "firstName": "JONATHAN",
      "lastName": "DOE",
      "dateOfBirth": "1985-06-20",
      "expirationDate": "2028-01-15",
      "isExpired": false,
      "isRealIdCompliant": true
    }
  },
  "signature": {
    "dateTime": "October 31, 2026 12:00 AM",
    "message": "Certified by Verifik.co"
  }
}

400 (Bad Request)

{
  "code": "MissingParameter",
  "message": "licenseNumber, firstName, lastName, and either backImage or rawBarcode are required."
}

500 (Internal Server Error)

{
  "code": "InternalServerError",
  "message": "An error occurred while cross-referencing document fields. Please retry."
}

---

Notes

• Fraud & Tampering Defense: Attackers often alter front card details (such as names or birth years to bypass age restrictions) using photo editing software without re-encoding the complex 2D barcode on the reverse side. Cross-checking catches 100% of these front-only alterations.
• Verdict Classifications: The verdict property evaluates to "confirmed" when all critical fields meet high-confidence thresholds, "discrepancy" when one or more key fields diverge, or "invalid_barcode" if the reverse barcode payload is malformed or unreadable.
• Deterministic Field Scoring: fieldScores provides granular confidence values from 0.0 (complete mismatch) to 1.0 (exact canonical match) for each compared identifier.