> For the complete documentation index, see [llms.txt](https://prismnetwork.gitbook.io/prismnetwork-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://prismnetwork.gitbook.io/prismnetwork-docs/5.-risk-management-system/5.2-data-trustworthiness.md).

# 5.2 Data Trustworthiness

Prism Network's strategy judgments depend on prediction market data and external signals, making data trustworthiness a direct factor in system security. News, on-chain data, social data, market data, GitHub activity, macro data, and third-party data sources do not directly trigger fund execution upon entry — they first enter the signal validation process.

The system tags data sources and evaluates them based on update time, source credibility, historical accuracy, propagation path, data consistency, and anomalous behavior. A single news item, social post, on-chain anomaly, or price movement can only serve as an initial reference signal. Only when multiple data sources reach consistency in timing, direction, and event subject do the relevant signals receive higher weighting.

For a given event e, Prism Network calculates the composite signal confidence based on multiple data sources:

S\_conf(e) = Σ(w\_i × c\_i × r\_i × a\_i) / Σw\_i

Where:

* w\_i = data source weight
* c\_i = historical credibility of that data source
* r\_i = relevance of the signal to the target event
* a\_i = consistency of that signal with other sources
* When S\_conf(e)falls below the system threshold, the signal can only enter the analysis and alert process and will not trigger automated execution.

AI Hallucination Prevention:

AI analysis and strategy generation must operate on structured data. Content lacking sources, market validation, or the ability to be mapped to specific events will have its confidence reduced and be restricted from entering the automated execution pipeline. The system classifies AI outputs into three levels: analysis, recommendations, and execution plans. Natural language analysis results cannot directly trigger fund operations — execution instructions must come from structured task objects.


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