Set up Sigma Synthetic Fraud

Before you start

Make sure you have the following:

Access to the RiskOS™ Dashboard with the Sigma Synthetic Fraud enrichment enabled.
- Your account owner or administrator can enable this for you. If you're unsure who to contact, reach out to support for assistance.
A basic understanding of RiskOS™ workflows and components.
- If this is your first time working with workflows, review the Workflow overview to understand inputs, enrichments, routing logic, and decisions.

How it works

Sigma Synthetic Fraud is a fraud detection enrichment available in RiskOS™. It evaluates identity attributes against consortium data to identify signals associated with synthetic identity fraud.

Sigma Synthetic Fraud returns:

Model scores: Normalized synthetic fraud risk scores generated by one or more models.
Reason codes: Indicators that explain the contributing factors behind synthetic risk signals.

These outputs can be used to inform routing, step-up verification, review, or escalation decisions in your workflows.

How Sigma Synthetic Fraud fits into a workflow

In RiskOS™, workflows are built by connecting reusable components. Sigma Synthetic Fraud is added as an Enrichment step.

Once the enrichment runs, its outputs are available to downstream workflow components, including:

Conditions
Decision rules
Rule score cards
Manual review steps
Final decisions

For more detail on these components, see Workflow Steps.

Execution flow in RiskOS™

Sigma Synthetic Fraud runs synchronously as part of a RiskOS™ workflow. There is no user handoff or pause in execution.

Input

Sigma Synthetic Fraud

Routing logic

Decision

At a high level, the execution flow looks like this:

Input

You call the Evaluation API with identity attributes.
Sigma Synthetic Fraud enrichment

RiskOS™ evaluates the provided attributes and returns model scores and reason codes.
Routing logic

The workflow evaluates synthetic fraud scores and reason codes.
Decision

The workflow returns a final outcome (for example, Accept, Review, or Reject).

Workflow components used by Sigma Synthetic Fraud

Sigma Synthetic Fraud uses a subset of standard RiskOS™ workflow components.

Component	Purpose	Typical input	Output / What to use next
Input	Start an evaluation	Identity attributes	Workflow execution begins
Enrichment	Detect synthetic identity fraud	—	Model scores, reason codes
Condition	Branch based on risk signals	Synthetic fraud outputs	Route to appropriate path
Decision Rule / Score Card	Apply policy or scoring logic	Synthetic fraud outputs	Pass/fail or cumulative risk classification
Decision	Emit final outcome	Routed value	Accept / Review / Reject

Configure Sigma Synthetic Fraud

Add Sigma Synthetic Fraud to a workflow

In the RiskOS™ Dashboard, go to Workflows and create a new workflow or open an existing one.
On the workflow canvas, select the plus (+) icon.
Add an Enrichment step and select Sigma Synthetic Fraud.

After the enrichment is added, its outputs can be referenced by downstream workflow logic.

Configure routing using model scores

Sigma Synthetic Fraud returns one or more model scores under:

socure_sigmasynthetic_response.synthetic.scores

Each score object includes:

score: Normalized risk score between 0.001 and 0.999
name: Model name
version: Model version identifier

Using a single score

If your integration is configured to return a single model score, you can reference it directly when defining Conditions in your workflow, for example:

socure_sigmasynthetic_response.synthetic.scores.0.score

Customers typically define thresholds based on their own risk tolerance and downstream verification strategy. For integrations that receive only a single score in the response, Conditions can be added directly against socure_sigmasynthetic_response.synthetic.scores.0.score. A common starting thresholds is 0.99 for step-ups to eCBSV or Document Verification.

Using multiple scores

If multiple model scores are returned, do not rely on the position of a score within the array. Instead, Conditions should evaluate both the score value and the associated model version.

For example, to evaluate whether a specific model version meets a given threshold, construct Conditions that:

Check the score value, and
Confirm the corresponding version field matches the intended model

This may require evaluating more than one element in the scores array, depending on your configuration.

Configure routing using reason codes

Reason codes are returned under:

socure_sigmasynthetic_response.synthetic.reasonCodes

This field contains an array of strings (for example, "R220") that explain contributing synthetic risk signals.

You can route based on reason codes by:

Adding a Condition step
Selecting the variable socure_sigmasynthetic_response.synthetic.reasonCodes
Choosing array contains or array does not contain
Providing the reason code value in quotes

Refer to the RiskOS™ Dashboard for the list of reason codes available for Sigma Synthetic Fraud.

Save and publish

Once your workflow is configured, publish it to go live.

Workflow testing checklist

Use this checklist to confirm accuracy, resilience, and completeness of the workflow before going live.

Input validation:

Required identity attributes are collected and passed consistently.
Supporting identity and account attributes are provided where available.

Routing and decisioning:

Model score–based routing behaves as expected.
Reason-code-based routing behaves as expected.
Review or escalation paths are clearly defined.

Operational readiness:

Synthetic fraud scores and reason codes are accessible to relevant teams.