As the world has gone more online, digital fraud has been on the rise. Bad actors are constantly looking for new ways to commit fraud using techniques such as forging synthetic identities, stealing identity and performing account takeovers. Companies are left having to balance a frictionless customer onboarding journey while trying to minimize fraud and protecting its platform.

FullContact brings harmony to these two equations leveraging the power of Verify Match and its broad, real-time Identity Graph.

The power of Verify Match spans both the digital and terrestrial ecosystems along with providing insight into how, and if, personal and professional identities are linked together.

Verify Match API can accept a wide variety of inputs such as:

  • Name & Address
  • Phone
  • Email
  • Social handle, ID or URL
  • MAID
  • Digital IDs such as Panorama ID and/or Non ID

Based upon provided contact information, you can understand how the information you have provided matches (or does not match) against the FullContact Identity Graph. In addition to the match characteristics there is an associated risk score, which is a proxy for friction that may need to be applied downstream.

All this combined, helps you identify risk on a form field, sign up, onboarding process or application.

The direct output of the provided information (at the contact element level) could potentially represent any of the following categories:


Match Type
Description

Tangled

string
Matches an input belonging to a different individual (no relationship).

This is typically an indication of increased fraud risk; further downstream friction may need to be applied specific to that identifier.

Household

string
Matches an input field belonging to someone else inside the same household (spouse, young adult, etc).

This is typically not an indication of fraud risk, however some friction may need to be applied.

Self

string
Matches an input field directly belonging and pointing to the most likely person requested.

All outputs with ‘self’ must share metadata within our graph as this is the anchor in which all other fields are classified.

Unknown

string
Not enough information to qualify as any of the above classifications.

This may or may not be an indication of fraud risk; further downstream friction may need to be applied.

Risk

double
Indicates the level of risk associated with the given inputs. This current risk score is based upon deterministic email related activity such as, first/last seen timestamps, number of sources and observations along with whether or not an observed linkage to a first party cookie exists.

If the risk score is closer to 1.0, then the individual and associated inputs are deemed to be more risky.

👍

Interpreting Requests in Match

The input provided should follow the multi-field format since it returns indicators on which submitted fields align and which do not.

For example, if an email, phone and name are provided, the response will indicate if the email, phone and name belong to the same person.

If they do not, the response will indicate as much and offer some insights into the mis-matched fields.

curl -X POST \
  https://api.fullcontact.com/v3/verify.match \
  -H 'Authorization: Bearer {Your API Key}' \
  -H "Content-Type: application/json" \
  -d '{
  "email": "[email protected]",
  "phone": "+15552227799",
  "location": {
    "addressLine1": "123 Main Street",
    "city": "Denver",
    "region": "Colorado",
    "postalCode": "80203"
  },
  "name": {
    "given": "Sally",
    "family": "Smith"
  }
  }'
{  
    "addressLine1" : "self",
    "city" : "self",
    "region" : "self",
    "country" : "self",
    "postalCode" : "self",
    "givenName" : "self",
    "familyName": "self",
    "phone" : "tangled",
    "email" : "household",
    "risk" : 0.31
}

Example Explanation

  • Request
    • The request uses Bob's email, but Sally for the Name
    • Bob Smith and Sally Smith live in the same home and thus share the address
    • The phone number is not associated to either of them and rather is connected to somebody different
  • Response
    • The address & name are Sally: self
    • The email is Bob's but Bob and Sally live together: household
    • The phone is not either of theirs: tangled
    • The risk is hence at slightly higher value due to having a tangled phone
  • Actions
    • Friction may be desired on the tangled phone, forcing the phone number to be verified by the consumer, who we hope is actually Sally!
    • Since the email is household, the requestor may choose to accept it as good enough since. Maybe both Bob and Sally share it from time to time.

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Nuances and limitations

  • While the endpoint accepts Multi-Field, it will only accept one input per contact identifier type (i.e. only one clear text email)
  • This endpoint does not accept Record IDs, Person IDs and/or Partner IDs as input
  • If name/address combination is used as input, FullContact will attempt to see if that name/address combination matches to a current, prior or unknown place of residence.