Results
The output of an API call is provided by our decision engine - an automated evaluation mechanism which helps us reduce the risk of fraud as well as improving customer experience in non-assisted enrollments. There are several logical units of evaluation which need to be considered in terms of decision mechanisms and these units are called Trust Factors.
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Trust Factors
An output consists of (a) Verification (set of “Trust factors”- logical units of the decision engine could result in one out of four possible levels - HIGH / MEDIUM / LOW / UNAVAILABLE / UNKNOWN) and (b) Decision (summary of Trust Factors providing summarized result).
Decision
Single outcome of the onboarding process. Usually it is sufficient to operate with this response only, without digging into Verifications.
Expected values:
Decision | Description |
---|---|
HIGH (GREEN) | onboarding process passed successfully |
MEDIUM (YELLOW) | some verifications are suspicious, we recommend to implement additional checks, depending on the business case or customer preferences |
LOW (RED) | onboarding process not passed |
Verifications
Number of Verifications (Trust Factors) depends on the configuration of the solution, and usually includes verifications like Liveness, Age, Cross- and Face verification checks. Trust Factors that are evaluated can be divided into three main categories; Biometric Trust Factors, Document Trust Factors, and Data Cross Check. Data Cross Check is an internal Trust Factor, and its outputs are fused into the other two Trust Factors on the Customer Dashboard. Each Trust Factor has its own mechanism of capturing possible fraud attacks. Each Trust Factor provides an output (Score). Low scores represent a high likelihood of a fraud attack. Each Trust Factor has a different range of scores, so we have a normalisation table for each of them.
Expected values:
Trust Factor | Description |
---|---|
HIGH (GREEN) | minimum value for successful onboarding with low percentage risk of possible fraud - should be automatically approved |
MEDIUM (YELLOW) | minimum value for suspicious evaluation - all suspicious cases should be considered for manual review, depending on the business case or customer preferences |
LOW (RED) | minimum value for negative evaluation which represent high percentage risk of possible fraud - all cases should be considered for automatic rejection |
UNKNOWN | no value returned, probably due to processing error |
UNAVAILABLE | no part of the evaluation process. Feature not available for given onboarding application |