• Overview
• FraudMAP Online
• FraudMAP Mobile
• FraudDESK
• Behavioral Analytics
• SaaS Deployment
• Benefits

Behavioral Analytics - Transaction Monitoring and Anomaly Detection to Defeat Today's Fraudsters

Cyber criminals are successfully defeating anti-virus, secure clients, multifactor authentication, and traditional fraud monitoring systems and walking away with millions.  To protect their customers, financial institutions need to start using the strategic advantage they have over the fraudsters – deep knowledge of their customers.

Behavioral analytics is a proven fraud detection and prevention methodology that uses online banking behavior as the starting point to detect fraud. Different users quite naturally have different behavior from each other, as well as being different from a fraudster. Behavioral analytics takes advantage of this fact. Rather than solely looking for specific malware, fraud indicators or fraud patterns, which are all changing too rapidly for most institutions to keep up, behavioral analytics combines knowledge about fraud with transaction monitoring and anomaly detection during every online banking session to determine if it is expected and legitimate behavior or suspicious behavior. (Video: Using Behavioral Analytics to Stop Fraud)

Dynamic Account Modeling™ Overview

FraudMAP Online's implementation of behavioral analytics is Dynamic Account Modeling™. Dynamic Account Modeling works automatically - there are no burdensome rules to write or maintain, no algorithms to manually train — and from day one, it can catch fraudulent behavior.

• Using Dynamic Account Modeling, FraudMAP Online automatically creates and continually updates a model of expected behavior for each individual account holder.
• With each session, Dynamic Account Modeling analyzes individual account behavior from login to logout — how they access their accounts, how they manage their accounts, the types of transactions they engage in, the frequency of activities, what kinds of activities take place during the same session, the type and amounts of payments, who the payees are, and more.
• Dynamic Account Modeling then determines if any of those events or combination of events are normal and therefore legitimate behaviors or if they are unusual, unexpected, or suspicious. Because it is looking across the entire online banking session and for every session, Dynamic Account Modeling can detect fraud at any stage of the attack - initial account compromise, account reconnaissance, or at the transaction, allowing institutions to proactively intervene before money is lost.

With Dynamic Account modeling, FraudMAP Online can detect when someone other than the legitimate user is accessing on online accounts, even if the machine, location, IP address, etc. appear to be the legitimate user's as they do in many Man-in-the-Browser attacks.

Dynamic Account Modeling Catches What Others Miss

There are over 70,000 variations of Zeus. Phishing attacks via email, SEO, and mobile phones are rampant. Criminals move money online via the ACH network, wire transfers, bill pay, and execute varying forms of offline fraud. Some attacks are automated, some have a real human behind them. Financial institutions simply do not have the resources to understand, anticipate and respond to every possible online fraud threat.

Solutions that detect fraud based on fraud rules, specific attack pattern definition or malware identification will miss fraud.  Why? Unless the fraud happens exactly as the rule was defined and follows a specific pattern or uses a certain piece of malware, it will not be detected. There are too many types of threats and attacks to make these solutions effective.

By nature, malware detection, rules-based or pattern detection-based systems are reactive - security vendors and institutions need to know what the fraud looks like in order to define a rule or train an algorithm. But fraudsters rarely stick to the same attacks and are quickly innovating, meaning never-before-seen threats will be missed.

Because Dynamic Account Modeling is not dependent on rules or patterns, but instead looking for any deviation from predicted behavior, it can find the widest array of attacks and automatically detect new and emerging attacks. And, because it is focused on specific account holders and not generalized patterns of behavior, FraudMAP Online not only maximizes detection, it does so with minimal alerts.