Fraud Prevention 2.0, Like Web 2.0 Has Revolutionized the Internet
When Web 2.0 was first introduced, it meant many different things to many different people. But fundamentally, it represented a more interactive and responsive web experience.
Gone were the days of unchanging websites with static content and fixed dimensions. Content and designs became dynamic, responding automatically to user characteristics and device types. Data flowed not just one way. Instead, digital interactions became multi-path communications and sharing extended across multiple platforms. Second-generation developers began using the Web as a rich platform for applications and services, not merely as a simple, unresponsive medium.
Now, the same concept of dynamic, adaptive response is changing the face of fraud detection. The Mercator Advisory Group calls this Fraud Prevention 2.0. Technologies and capabilities that differentiate Fraud Prevention 2.0 from static, legacy Fraud Prevention 1.0 include:
- Artificial Intelligence (AI) and Machine Learning
- Order Linking
- Mobile Device ID
- Persistent identity
- Dynamic Scoring™ and Re-Scoring
- Behavioral biometrics
- and more
This move from static to dynamic fraud prevention defeats fraudsters’ sophisticated capabilities to rapidly change their methods of attack and circumvent passive fraud defenses.
Let’s look a few of the similarities between Web 2.0 and Fraud Prevention 2.0:
Dynamic vs. static. Legacy Web 1.0 web pages were comprised of static, relatively unchanging blocks of content. The similarity to Fraud Prevention 1.0—with its use of static, historical databases and fixed risk scoring—is striking. But much like Web 2.0, Fraud Prevention 2.0 delivers dynamic response to rapidly-changing scenarios. In real-time, powerful technologies like AI and Machine Learning apply hundreds of algorithms that continually re-assess risk based on changing data inputs. The result is superior, up-to-millisecond accuracy in risk assessment.
Adaptive. With Web 2.0, how a web page gets displayed is quite different depending if the user is viewing it on a desktop, tablet, or smartphone. Fraud Prevention 2.0 also responds to changing devices. For example, an interaction from a mobile device triggers different assessment factors, such as Mobile Device ID, mobile geo-location and other mobile-only screening technologies and policies. Other techniques like Dynamic Scoring™ and Re-Scoring report changing risk levels as new data is introduced after a transaction or digital interaction occurs. This enables online businesses to adapt and respond to changing risk profiles.
Mashup application. In Web 2.0 use, the term mashup describes a web page or web application that combines data from multiple sources to create a new unified service, for example, combining photos, street address text, and a Google map to make a “Locate Us” page. It’s something that is more than the sum of its parts. The same kind of mashup happens with Fraud 2.0. In real-time, it integrates results from multiple screening technologies such as Device Fingerprinting, Geo-Location, Proxy Piercing, Personas, Order Linking, and Dynamic ScoringTM and Re-Scoring via Machine Learning to create Personas—“shortcut” descriptions of data sets that speed identification of fraud. This result is more than the sum of its parts.
Collaborative consumption. In Web 2.0, members of a network can both provide and consume a good or service. For instance, a web community in which members share accommodations at travel destinations through house swapping is a good example of collaborative consumption. In a similar vein, the Big Data generated by all the members of the Kount network resembles collaborative consumption. The more users who join the network and share their transaction data, the better the results for everyone.
Behavioral biometrics. Web 2.0 has made swiping the screen of a mobile device second nature to us all. It has also made Fraud Prevention 2.0 possible. Behavioral biometrics analyze how a person swipes their screen, holds the device, enters text, etc. It can tell if the current behavior of the user matches the behavior profile on record.
Discover more ways the dynamic, adaptive capabilities of Fraud Detection 2.0 is revolutionizing fraud prevention. Download the White Paper “Fraud Detection 2.0: Dynamic Tools For Fighting E-Commerce Fraud".