Anomaly Detection
Anomaly Detection is a core product of Trulioo’s Risk Insights service and taps into Trulioo’s platform to detect suspicious activity across our entire transaction base. The product is built to help our customers protect themselves from fraudulent onboarding on their platform by detecting similar activity across Trulioo. Anomaly Detection calculates the risk of a user based on the likelihood of them being a synthetic or stolen identity.
Anomaly Detection ties closely with Trulioo’s Person Match capabilities to create an effortless integration. It uses the following information, most of which our customers already use for our IDV product:
- Name
- Address
- Telephone
- Date of Birth
- National ID
Trulioo has a large and diverse customer base across numerous sectors such as Crypto, Fintech, Banking, Payments, and Marketplaces. Based on incoming transactions from our customers, Trulioo extracts the metadata and de-identified information to build models on how authentic individuals behave at the point of onboarding. The large number of transactions across Trulioo’s platform help to alert customers about suspicious transactions almost instantly.
Anomaly Detection Request
Request Fields
Parameter | Parameter Description |
---|---|
Name | Name |
Address | Address |
Mobile | Phone number |
DateofBirth | Date of Birth |
NationalID | National ID (Social Security/ Passport Number) |
Email Address |
Sample API Request
{
"DataFields": {
"PersonInfo": {
"FirstGivenName": "Tom",
"MiddleName": "Marvolo",
"FirstSurName": "Riddle",
"DayOfBirth": 31,
"MonthOfBirth": 12,
"YearOfBirth": 1926,
"Address1":"Wool's Orphanage",
"NationalIDNumber": "111222333"
},
"RiskInfo":{
Phone: "1112223333",
Email: "[email protected]"
}
},
"AcceptTruliooTermsAndConditions": true,
"CountryCode": "UK",
"VerboseMode": "True"
}
Anomaly Detection Response
Response Fields
Parameter Name | Parameter Description |
---|---|
RiskScore | Summary Score of Anomaly Detection |
RiskLevel | Summary Level of Anomaly Detection |
RiskDetails | Breakdown of Anomaly Detection model components score and level |
RiskSignals | Relevant Risk Signals for Decision Making beyond score and Level |
RiskSignals Fields
Parameter Name | Parameter Description |
---|---|
IdentitiesSeen | Number of times this Identity has been used to login to Trulioo’ s Platform |
AccountCreationInterval | Average number of minutes between an accounts creation on Trulioo’s platform during one day |
AccountsCreatedPerDay | Average number of accounts created per day |
RoboticFraudAccountsPercentage | Percentage of Accounts created on Trulioo’s platform using bots |
HybridFraudAccountsPercentage | Percentage of Accounts created on Trulioo’s platform using bots and humans working together |
HumanFraudAccountsPercentage | Percentage of Accounts created on Trulioo’s platform by humans |
CrossBorderFraud | Has Trulioo seen this Identity used in multiple countries |
CrossIndustryFraud | Has Trulioo seen this identity across multiple industries |
EmailDiscrepancy | A different email has been used than the associated email in Trulioo’s Identity Graph |
AddressDiscrepancy | A different Address has been used than the associated email in Trulioo’s Identity Graph |
PhoneDiscrepancy | A different Phone has been used than the associated email in Trulioo’s Identity Graph |
DoBDiscrepancy | A different Date of Birth has been used than the associated email in Trulioo’s Identity Graph |
Email/DoBMatch | The Email and DoB submitted match with Trulioo’s Identity Graph |
Phone/DoBMatch | The Phone and DoB submitted match with Trulioo’s Identity Graph |
IDNumber/DoBMatch | The ID Number and DoB submitted match with Trulioo’s Identity Graph |
Sample API Response
{
"TransactionID": "f9de9726-707d-4eec-9c94-3f5b6ee926d0",
"UploadedDt": "2023-04-26T16:28:37.211295",
"CompletedDt": "2023-04-26T16:28:39.50633",
"CountryCode": "US",
"ProductName": "Identity Verification",
"Record": {
"TransactionRecordID": "20793047-47d4-6f2e-c9d0-6f075cb23d21",
"RecordStatus": "nomatch",
"DatasourceResults": [
{
"DatasourceName": "Trulioo Fraud & Risk",
"DatasourceFields": [],
"AppendedFields": [
{
"FieldName": "RiskScore",
"Data": {
"RiskLevel": "Low",
"Score": 24
}
},
{
"FieldName": "RiskDetails",
"Data": {
"VelocityMonitorScore": {
"RiskLevel": "Low",
"Score": 3
},
"IdentityGraphScore": {
"RiskLevel": "Low",
"Score": 0
}
}
},
{
"FieldName": "RiskSignals",
"Data": {
"VelocityMonitor": {
"IdentitiesSeen": 6,
"DaysIdentitySeen": 2,
"AccountCreationInterval": 276,
"AccountsCreatedPerDay": 2,
"RoboticFraudAccountsPercentage": 0,
"HybridFraudAccountsPercentage": 0.66666666666666663,
"HumanFraudAccountsPercentage": 0.66666666666666663,
"CrossBorderFraud": false,
"CrossIndustryFraud": false
},
"IdentityGraph": {
"EmailDiscrepancy": false,
"AddressDiscrepancy": true,
"PhoneDiscrepancy": false,
"DoBDiscrepancy": false,
"EmailDoBMatch": true,
"PhoneDoBMatch": true,
"IDNumberDoBMatch": true
}
}
}
],
"Errors": [],
"FieldGroups": []
}
],
"Errors": [],
"Rule": {
"RuleName": "Category 3 KYC v3",
"Note": "Match(FamilyAndGivenInitial, DOB) or Match(FamilyAndGivenInitial, FullAddress) or Match(FamilyAndGivenInitial, ID) MiddleName Ignored"
}
},
"Errors": []
}
Updated about 1 month ago