Customer Confidence Factor (CCF)

The Customer Confidence Factor (CCF) API OpenAPI specification is available for download here. Explore the API endpoints here.

The Customer Confidence Factor (CCF) API allows clients to retrieve the latest confidence score associated with each customer, shop, or terminal. This value plays a central role in managing risk across sportsbook operations, particularly when combined with automated or manual stake restrictions.

What it does

The CCF represents a real-time grading of an account's trustworthiness or value, reflecting a bettor’s historical behaviour, risk profile, and betting pattern. It is used to calculate permitted stake levels and control exposure. CCFs are either assigned manually via the MTS Console or computed using the sCCF model and adjusted via Auto CCF logic.

When it's triggered

Clients can call the API on demand to retrieve the latest CCF values. The data is available for individual entities or in batches. The API supports pagination and allows lookups by customer, shop, or terminal – either individually or in combination.

Input requirements

Each request must specify the following identifiers:

• bookmaker – the assigned Insight Tech or MTS bookmaker ID

• sub-bookmaker – the sub-entity of the bookmaker (use * to retrieve all sub-entities)

• customer, shop, or terminal – depending on the selected endpoint

Some endpoints also support range filters (lower, higher) or pagination using startKey. A full breakdown of all accepted parameters is available in the Endpoints section.

Output schema

A typical response includes the list of items, and each object under responseItem contains:

• srcId: compound source identifier for internal tracking

• ccf: the current customer confidence score (a decimal number)

• id: entity identifier

Interpretation guidance

The returned CCF values determine the allowed stake size and validation flow. Higher values (e.g. 1.2 and above) reflect trustworthy or high-value accounts, while lower values (e.g. below 0.8) indicate accounts under scrutiny or severe restriction.

Auto CCF logic automatically adjusts CCFs based on model outputs (sCCF), within configured limits and rules. Manual overrides are respected, and analysts can disable automation for specific accounts.

The colour-coded CCF groups in the Console (e.g. red for low, green for high) provide quick context when reviewing tickets and accounts.