> For the complete documentation index, see [llms.txt](https://docs.payshield.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.payshield.ai/payshield-fraudcheck/overview.md). # Overview TxShield's Fraud Management system evaluates transactions for risk using a configurable set of local rules and third-party scoring providers. Fraud checks can run in two modes: embedded within a payment transaction or as a standalone check independent of any payment.\ \ Two Processing Modes\ 1\. Embedded Fraud Check (Payment-Triggered)\ Fraud checks run automatically as part of processing a `PAYMENT`, `PREAUTH`, or `AUTH` transaction. If the transaction's threat score exceeds the configured threshold, the payment is declined before authorization is attempted. No separate API call is needed — the fraud evaluation is built into the transaction flow.\ 2\. Standalone Fraud Check\ A fraud check can also be submitted on its own — without processing a payment — using the `FRAUDCHECK` action. This allows merchants to evaluate a cardholder's risk profile before committing to a transaction, or to use TxShield's fraud scoring as a decision layer in their own workflow.\ A standalone check accepts the same inputs as a payment (card details, billing/shipping address, email, IP, cart data) but produces only a risk result — no charge is made.\[8:05 PM]Fraud Checks: Built-in vs. External\ Built-in checks (processed locally and immediately):
* Velocity — repeated identical transactions within a short window * BIN validation and issuing country check * GeoIP — IP location vs. billing/shipping address * Transaction limits — daily/monthly caps by IP, email, or card * Chargeback and decline history * Card and IP whitelists/blacklists * Repeat transaction detection across card, email, or phone External risk provider checks (real-time third-party scoring):
* IP reputation, proxy/VPN/TOR detection * Email validity and disposable email detection * Phone number intelligence and risk scoring * Identity verification across name, address, phone, and email * Device fingerprinting and behavioral signals * Order-level fraud scoring --- # 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.payshield.ai/payshield-fraudcheck/overview.md?ask=&goal= ``` `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.