A next-generation hybrid fraud management solution is developed to increase fraud detection accuracy and improve operational effectiveness. The solution is fully integrated into our digital commerce platform: a single integration and onboarding for our payment services and Microsoft’s Fraud Protection. There is no limitation on geographics or business verticals.

Features

• AI-powered tool: core technology is adaptive AI, trained by the fraud protection network, which empowers machine learning and provides a broad awareness of fraud activity across the globe and within business verticals
• Mixed fraud screening models: suit your business needs by choosing traditional static rules, machine learning, or a hybrid combination of both
• Multi-hierarchy: manage your fraud strategy at any level (set up rules per branch, country, MID, etc.)
• Payment methods variety: choose from all presented card products, direct debit, and alternative payment methods supported by us
• Device fingerprinting: benefit from a fully integrated device intelligence at no additional cost
• Custom data flexibility: send any extra data fields in the desired format to create fraud rules and enhance their performance

What does it mean for you?

• Pre-authorization monitoring: filter potential risks before the transactions are sent to the bank and increase authorization rates
• Outstanding dataset: combine Worldline, Microsoft’s Fraud Protection network, industry leaders, and your transactional data to build up your own machine-learning fraud tool
• Risk appetite calibration: find the optimum balance between approving orders and detecting fraud activity
• Virtual fraud analyst reporting: analyze and monitor your controls

Available tools

View the transaction details

A comprehensive transactional summary is easily accessible, neatly organized into predefined sections for your convenience.

Virtual fraud analyst

You can analyze patterns and gain profound insights into your fraud management controls.

Risk score

This score uses AI to estimate the chance of a transaction being fraudulent. The platform relies on data from the fraud protection network to identify events and detect fraud connections. By carefully examining each transaction within Microsoft Dynamics 365, you can use these identified links to efficiently tackle emerging fraud risks and protect your business.

The risk score is an integer between 0 and 999 (inclusive). The higher the score, the higher the likelihood that the transaction is fraudulent.

Lists

You're free to create Standard, Block, Watch and Safe lists using the built-in functionality to simply add any of these 5 attributes to your list:

• User ID
• Device ID
• IP address
• Payment ID
• email address

Custom lists are created and defined by you to implement specific business policies to manage your fraud protection strategy. You can reference your lists in rules dynamically.

Rules 

You can create rules with the parameters you send in the payment request, use the risk score generated by the AI model, or employ both methods. The output will be a decision that determines the next transaction step.

The rate at which certain actions occur, whether attributed to a user or entity (like a credit card), can be a signal of suspicious behavior and possible fraudulent activity. For example, when fraudsters attempt a series of separate orders, they frequently use one or more credit cards to swiftly perform multiple orders from a single IP address or device. This pattern often points to potential fraudulent actions.

You can also set up velocity checks to monitor unusual patterns and how often suspicious events occur. There's an option to define thresholds in your rules to control and mitigate potential risks effectively.

Case management

When you configure the rules to activate a Challenge decision, it initiates the creation of a case in your designated queue that the fraud expert within your organization will review. You can also categorize these cases into distinct queues for your fraud team to assess manually. To perform a transaction review:

1. Go to Case Management and select View Cases from the specific queue you need to review. Inspect the transaction details.

1. Inspect the transaction details.

1. On the Link Analysis tab, you can examine additional transactions related to the case you're reviewing. Choose specific attributes to display transactions that share the same attributes. This feature helps to trace and understand the links between transactions.

1. Using this data, decide to Approve or Reject the transaction, specifying the reason (it's also possible to include notes).

Data fields 

When you send a payment request, there are various fields included that need to be filled out. We encourage you to send as many fields as possible, as not all of them are mandatory. Sending more data in your request also helps the machine learning models to get educated in real time by consuming and assessing the data signals for more effective fraud detection.