Take your customer analysis to new heights with ComplyRadar Risk-Scoring
The ComplyRadar risk scoring module allows for the configuration of individual/entity-based risk scoring that is automatically calculated on metrics extracted from the individual/entity profiles as well as behavioural factors. Factors making up the risk score can be based on information coming from the individual/entity details. For example, age, nationality or country of residence, category, occupation/industry and products utilized can all be utilized as metrics that influence the overall score. More importantly transaction activity can be used to calculate statistics over transaction patterns/behaviour. For example, the number and type of different parties receiving funds from the same account, the volume or frequency of transaction, as well as ratios between incoming and outgoing transactions.
For numerical metrics, the range of values can be split into fuzzy buckets (e.g., high, medium, low), meaning that ComplyRadar is able to consider the degree of membership of a measure into each bucket. Once these ranges are defined, the rule engine accepts rules that can take the form of:
If Transaction Volume is HIGH and Average Transaction Value is MEDIUM then Risk is MEDIUM
The system can be configured with a list of these rules, and it will come up with an overall risk score for the individual/entity based on an aggregation of all the outcome of set rules. This means that the overall risk of an individual/entity will be based on the aggregation of all the rules output. In terms of rule output aggregations, we support both cumulative and averaging methods across all rules being triggered. The solution permits users to review what factors make up the risk, as well as view and compare fluctuations in the risk score and metrics over time.
Customer Analysis Taken To The Next Level
By accessing the customer screen users can immediately view the latest calculated risk score for each business function the user has permissions to access. Risk score shows the overall score and risk term associated, as well as the ratio whether that risk score is composed of low, medium or high risk items.
Accessing the configuration screen allows risk score calculations to be defined. Different scoring calculations can be configured for each business function (AML, Fraud, Responsible Gaming (RG)), running at regular intervals ( e.g., hourly), going through a subset of customers in ComplyRadar. This means that a separate scoring calculation can be performed by customer type such as individuals or corporates, or against different jurisdictions.
Risk Score Designer
Accessing the risk score designer allows users to create scores based on various scoring metrics defined on customer information such as age, country or industry risk; or else on behavioural data such as transaction statistics or occurrence of other rules that monitor customer activity.
The user is permitted to define several scoring metrics such as:
Values for each metric are mapped into categories of risk based on values or ranges. Ranges may be overlapping, making the risk scoring calculation fuzzy. This means that the system can account for difference between a customer that is at the limits of the range.
Metrics can be combined into scoring rules that define the overall impact on the score. For example,
Customer performed more than 10K DEPOSITS in the last 30 DAYS and the jurisdictional risk of deposits is HIGH, then set risk score as HIGH.
The various rules are then combined into a single scoring value/term based on two methods:
Centre of Gravity: Each rule activated provides a weighted force towards the different risk score bands. The overall score considers the overall area of the scoring function and sets the score as the centre value across the score range.
Weighted Sum: Each rule that is activated contributes to a value that is added to the overall score. These are summed together to get the overall risk score.
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