> For the complete documentation index, see [llms.txt](https://docs.sportradar.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sportradar.com/itservices/models/customer-confidence-factor-ccf-api/faqs.md).

# FAQs

<figure><img src="/files/Tygvy3qu5wzIzgNnXdtq" alt=""><figcaption></figcaption></figure>

### ❓ What is the CCF API?

The Customer Confidence Factor (CCF) API allows you to retrieve the current trust level (CCF score) of any customer, shop, or terminal. This score is central to your risk management strategy and is directly tied to stake validation logic in MTS.

### ❓ How does the CCF score work?

CCF is a dynamic risk grade, typically between 0.01 and 10.00, that reflects how much trust is placed in a customer/shop/terminal:

* Higher CCF → higher permitted stakes and fewer restrictions
* Lower CCF → reduced exposure and increased scrutiny

CCF scores are used during ticket validation to apply stake caps or trigger rejection flows.

### ❓ How is the CCF score calculated?

CCF values are:

* Manually assigned via the MTS Console
* Automatically updated via Auto CCF logic, using the machine-generated sCCF score as input\
  Manual overrides always take precedence. Operators can define automation rules and caps to ensure safety.

### ❓ What entities does the CCF API support?

You can retrieve CCF scores for:

* Individual customers
* Entire shops (e.g. retail branches)
* Specific terminals (e.g. kiosks)

Each of these can be queried separately or in combination via API.

### ❓ How often are CCF scores updated?

The scores are always live and reflect the most recent update — whether manual or automatic. Use the API for real-time retrieval of these values.

### ❓ What does a specific CCF score mean?

| CCF Score Range | Interpretation            | Colour (Console) |
| --------------- | ------------------------- | ---------------- |
| ≥ 3.01          | VIP / Very High Trust     | Green            |
| 1.00 – 3.00     | High Confidence / Default | Light Green      |
| 0.61 – 0.99     | Caution / Reduced Trust   | Orange           |
| < 0.60          | Restricted / Suspicious   | Red              |

*These are default interpretations; actual validation behaviour depends on MTS configuration.*

### ❓ Can I auto-adjust CCF values?

Yes. CCF values can be adjusted using:

* Auto CCF logic, based on machine-learned sCCF values
* Configured rules (min/max caps, rate limits, delta thresholds)
* Manual overrides, which disable automation for specific entities

This enables scalable, adaptive risk management.

### ❓ What are the rate limits for the CCF API?

| Limit Type      | Value            |
| --------------- | ---------------- |
| Requests/second | 10               |
| Daily quota     | 200,000 requests |
| Minute quota    | 500 requests     |

If you exceed these, you will receive a `429 Too Many Requests` response. Use exponential backoff for retries.

### ❓ What if I don’t receive a CCF value?

If a customer/shop/terminal has no score, check:

* Is the ID correctly formatted and belonging to your sub-bookmaker?
* Had player placed at least one bet that reached MTS/Insight Tech?

Contact your OAM or CI engineer for support if the issue persists.

### ❓ Who should I contact for CCF support?

For access issues, integration help, or data questions, contact:

* Your OAM
* Your assigned CI engineer
* Or submit a ticket via Sportradar support.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.sportradar.com/itservices/models/customer-confidence-factor-ccf-api/faqs.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.