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Online Booking Fraud Detection

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The sample project will show how to detect online booking fraud based on Fraud Rating Score.


In this example, we used commonly available Fraud Rating Scores to determine the online booking fraud. Based on the Fraud Rating Score, the system can either approve or reject the transaction. If the score is within a pre-defined acceptable range, the transaction is approved. If the score is too high, the transaction will be rejected. If the score is within pre-defined buffer range, the transaction is flagged as potentially fraudulent and may be reject or approve after reviewing by a fraud analyst.

The calculated Fraud Rating Score should be less than 200 to approve the online booking. If the score is over 300, the booking will be rejected. If the score fall in between those two margins, the transaction will be flagged and forwarded to a fraud analyst to review further.

Running the Sample

File Workflow
  • Click on the Logic Run template.
  • Click on any given template.
run template for booking fraud
  • You can click the ‘Next Step’ button to go step by step to follow the flow.
  • If you select “Flagged” run template, you will have the following window to select either Approve or Reject decision outcome.
Approve human task for booking fraud
  • Now you can see the output values in the ‘Parameters’ window.
Outcome of booking fraud
  • You can see the notifications in the Notification window base on the actions you perform.
Notification for booking fraud

Process Steps

The process contains the following two steps to determine “Online Booking Fraud”

  1. Straight through processing for determine Fraud Decision
  2. Fraud Analyst’s Decision

Project Description

The project contains the following documents.

Decision Table

  • Determine History based Fraud Score.xml – Determine the score based on customer’s order history.
  • Determine Payment Method based Fraud Score.xml – Based on different payment method, the score will be calculated.
  • Determine Product based Fraud Score.xml – Based on different products, the score will be calculated.
  • Determine Fraud.xml – Determines the fraud status and decision outcome based on the Fraud Rating Score.

Business Glossaries

  • Concept.xml – Allows to reuse the customer, booking and outcome details throughout the process.

Decision Graph

  • Fraud Decision.xml – Determines the fraud decision based on the score.


  • Workflow.xml – Overall flow of the process. If the fraud decision is flagged, it refer to a fraud analyst as a human task.

The Flow Design

The Fraud Decision (Decision Graph)

Decision Graph for booking Fraud

1. Decision Table to calculate score based on product type.

Product type DecisionTable

2. Decision Table to calculate the score based on payment method.

Payment type DT

3. Decision Table to calculate the score based on customer booking history.

previous order DT for booking fraud

4 Expression for check the active disputes.

Expression for active dispute

5 Compute Fraud Rating Score : This sub decision invokes the above sub decisions and sums up the calculated fraud score from each.

6. Decision Table to determine the booking fraud based on Fraud Rating Score.

Fraud Decision Table

The Workflow Design

Workflow for booking fraud

The Workflow contains the Fraud Decision (Decision Graph) and a human task with 2 notifications based on the human task action.

If the Fraud Decision outcome is ‘Flagged’, then Fraud Analyst’s Decision will execute. Otherwise, the process will end. Fraud Analyst’s Decision can be either ‘Approve’ or ‘Reject’. Based on that decision, relevant notification will display.

Deploy into FlexRule Server

You can deploy this project into FlexRule Server and execute the workflow by following these steps.

Download the project

Use the attachment at the end of the page to download the sample project.

Updated on March 6, 2023

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