Guides

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.

Fideo brings harmony to these two equations leveraging the power of Verifyand its broad, real-time Identity Graph.

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

API Reference

curl -X POST \
  https://api.fideo.ai/verify \
  -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"
  },
  "organization": "FullContact",
  "title": "CEO"
  }'
  "ipAddress": "74.125.20.113",
  "profiles": [{
  "service": "twitter",
    "username": "bartlorang"
  },
  {
    "service": "twitter",
    "userid": "123456"
    }, 
    {
    "service": "linkedin",
    "url": "https://www.linkedin.com/in/sallysmi"
    }
  ]
  }
{  
    "addressLine1" : "self",
    "city" : "self",
    "region" : "self",
    "country" : "self",
    "postalCode" : "self",
    "givenName" : "self",
    "familyName": "self",
    "phone" : "tangled",
    "email" : "household",
    "title": "unknown",
    "organization": "unknown",
	  "risk" : 0.52
}

๐Ÿšง

For social profiles, you can only submit one - the above code example has 3, but only to show you how to input either "userid", "url", or "username" as an input. Only choose one when you make your Verify.Match API call

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

  • Name & Address
  • Phone
  • Email
  • Social handle, ID or URL
  • Employer/Job Title

๐Ÿšง

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)
  • If name/address combination is used as input, Fideo will attempt to see if that name/address combination matches to a current, prior or unknown place of residence.

Based upon provided contact information, you can understand how the information you have provided matches (or does not match) against the Fideo 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 โ€˜selfโ€™ 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.

What is the Risk Score?

The Fideo Risk Score is a value between 0 (less risky) and 1 (more risky) which reflects how well known and connected the input query is to Fideo. The more input you can provide (name + address + email + phone) as opposed to just name + email the better and more accurate your risk score can be.

What Feeds In to the Risk Score?

To create the Fideo Risk Score we look at various aspects of your input: we look at whether the data is valid, how well the input query is connected to each other in our graph, how much of the data is known to our graph, is connected to a single person, and is made up of correct, legitimate identifiers.

Score Value Guidance

Note: These are only general guidelines. Certain use cases may require more or less friction. Example: Higher risk scores may be allowed for general use case where there are low levels of loss, product, or revenue. Transactions which are associated to higher potential loss, our guidance would be to require a lower risk score.

ScoreBucket NameDescriptionWeather
0.0-0.2LowData is well connected and known, belonging to one person.๐ŸŒž
>0.2-0.4Medium-LowData is connected for the most part. There are some data misalignments, but may be due to different household members, or the person is new to an address.โ›…
>0.4-0.6MediumSome data in the input query is correlated, however there is evidence of data not correlating.โ˜”
>0.6-0.8ElevatedData is not well connected or not legitimate, and may be combining multiple people. Suggesting to not let the customer/signup continue or do additional validationโ›ˆ๏ธ
>0.8-1.0HighData Considered not well connected, not belonging to the same person, or not legitimate.๐ŸŒช๏ธ

๐Ÿ‘

Interpreting Requests in Verify

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.

Only input fields will return.