Fraud analysts examine current and historical information related to user, device and IP in context to determine if a given user session or transaction is a risk or legitimate. This allows them to analyze not only transactions but also the behavior that preceded them, shedding light on fraud indicators that were previously ignored.
For example, looking at a user journey within a session, mouse movements, copy-paste usage, autocomplete, etc. together provides insight into a user’s behavior and allows the analyst to identify fraudulent activity with greater accuracy and earlier. Unconscious behaviors like clicks and mouse movements, scrolling, and more look different when a human is doing them compared to a bot or script. Conscious behaviors—navigation, actions and their order, speed, and more—reveal a user’s intent, and those also show pronounced differences between human and bot.
Without data from a fraudster’s full journey, it’s difficult to eliminate false positives. For instance, if a tool only does transaction analysis, by the time a transaction is categorized as fraud, it's too late, the damage is done. There’s a large gap between the initial session, when a user first enters a website or a mobile app, and when the user checks out. That gap gives cybercriminals all the time they need to defraud you.
This lack of insight into what is actually happening during a session is what must be addressed. When you continuously collect dynamic data throughout the user journey, you can identify weaknesses that are being exploited and detect and stop fraud attempts before they do damage.
With data analysis through the entire user journey by way of continuous monitoring, fraudsters' efforts can be flagged well before checkout. It catches them in the act, and exposes patterns manual reviewers can look for when evaluating whether a particular case is fraudulent or not.
Behavioral data analysis opens a window into what fraudulent behavior looks like and provides in-depth insight into how to act on that data to create a safer, more efficient experience for your customers.
How can I avoid negatively affecting the customer experience?
Quite simply, don’t interrupt your customers and don’t treat them like criminals. They are quick to abandon shopping carts or move to a competitor’s website if they encounter intrusive measures to prevent fraud that treat them as a possible threat.
The easier you make it to complete a transaction, the better the chances they will follow through on it and return in the future. Improve the user experience by removing intrusive authentication measures like CAPTCHA or collecting personal identifiable information (PII).
That means that you need to monitor behavior and evaluate the risks that fraud is occurring without actively impeding users. Your ideal fraud prevention solution provides a seamless experience for customers as they shop and keeps fraud detection invisible yet effective.
Features to look for in a solution include:
- Full data visibility through the entire user journey
Full data transparency helps you understand why fraudulent behavior is flagged. By collecting behavioral and device data, all the actions that occur during the entire customer journey are at your fingertips.
- An effective, adaptive integrative tool
Along with seeing each user’s activity, it’s helpful when your solution adapts to the ever-changing landscape of fraudulent behaviors and patterns effectively and efficiently. When fraudsters apply new methods or adjust existing ones trying to beat or bypass your barriers, your fraud prevention tool should be able to keep up and flag discrepancies.
- Seamless data collection invisible to the customer
Collect behavioral data through the entire user journey without disrupting your legitimate customers' experiences through session monitoring.
Solutions like PingOne Protect work invisibly to protect your enterprise without imposing burdens on your customers.