Fraud prevention often comes to fraud and payments teams with its fair share of challenges across operational, technical, and customer experience (CX) areas. Here are the most pressing ones:
Operational issues
Technical challenges
CX concerns
We present a fraud detection solution designed to address these challenges while securing platforms, online businesses, and financial institutions against various fraud types, such as account takeover, fake account creation, payment fraud, and chargebacks.
Let’s walk through the features and benefits Mangopay’s fraud detection software brings to your business.
With a rich suite of low-level attributes, our risk detection tool goes beyond the surface and provides profiling for each user attempting to transact on your website or mobile app. We look at the device’s hardware, software, browser, and user behavior to catch any spoofed details or if someone's trying to hide their online tracks. What’s more, by collecting dark web insights, we reverse-engineer fraudsters’ techniques and thus help you stay ahead of fraud.
When you know, you know. Fraudsters use advanced techniques to hide their tactics. Clever fraudsters avoid popular tools known by solution providers and use shady ones that only they know about. At least, this is what they think because we know about them, too. A fraud detection software's role is to distinguish legitimate users from fraudsters with high precision - this is possible with extensive knowledge of fraudsters’ modus operandi.
Our flexible decision engine allows you to adjust and refine your rules whenever you need to. What’s more, you can use historical data to test new rules before implementing them. This approach enables you to evaluate the potential success of changes in a risk-free setting.
When you need to dig deeper, sort, filter, and explore fraud inquiries to examine individual transaction outcomes. This gives you a microscopic view into the effectiveness of your current setup and helps you decide where to make adjustments.
In a controlled environment where you can backtest your rules before they start influencing the final recommendations, it is possible to identify and address false positives or false negatives results. You benefit from a more reliable and accurate system while reducing the risk of flagging legitimate transactions.
Build complex expressions in an easy way and create rule sets that align precisely with your fraud detection requirements. These expressions can be customized based on hundreds of attributes, fixed or variable values, velocity, distance, and text similarity. By leveraging this wide array of configuration possibilities, you can create rules that adapt to the characteristics of your business.
Fed with relevant users’ data points and fine-tuned with advanced algorithms, ML models learn from and adapt to new data over time and increase the ability to detect and prevent fraud in real time.
You can also opt for a dedicated data scientist who can simulate, assess, and monitor fraud rule sets to optimize your security and detect and prevent complex fraud attempts.
With the setup within our hub, you may enable fraud prevention without extra steps. You can screen transactions using data from across the Mangopay network - with insights from thousands of businesses, millions of users, and billions of transactions data - set rules and analyze data with a no-code engine.
Depending on your risk appetite, you can choose to integrate the profiling solution with AI-powered device fingerprinting to prevent sophisticated fraud cases.
To wrap it up, here’s what you need to consider to create a safe environment where fraudsters are weeded out while more genuine transactions come in.
In this dynamic online environment, what you know that works today might not work next week or even tomorrow. Tools that fraudsters, devices and operating systems, and customer behavior - all change at a fast pace. So, go with the solution that adapts to the market shifts and enables network effects. The more users you protect, the more knowledge you gain, and the better and quicker you can react to the new ways the fraudsters operate.
Keep your platform safe with our built-in fraud prevention engine. Get in touch for more details.
Fraud detection software is a technology designed to identify and prevent fraudulent activities, and suspicious behavior in real time by analyzing various data points and using advanced algorithms, including machine learning models.
Several common types of fraud that these systems can detect include identity theft, payment fraud, account takeover, money laundering, and fraudulent transactions within applications, APIs, systems, and data.
For precise customer risk assessment, fraud detection software solutions must adapt by learning from both new legitimate and fraudulent data. We recommend retraining fraud detection models on a regular basis, ranging from weekly to monthly intervals.
Rules-based systems provide criteria that security and fraud teams can easily understand and modify. Once set, rules do not change unless manually updated, which implies consistent decision-making over time. However, they may not efficiently handle large volumes of data or adapt to new types of fraud as they rely on predefined rules.
Machine learning models, on the other hand, work really well with large and complex amounts of data. They can learn and adjust to new patterns of fraud and incoming data.
To learn more about how Mangopay can help you select and connect the products you need to succeed, get in touch with us.