Recently, Arkose Labs, which is working to develop a platform to detect and reduce online fraud, announced $22 million in financing. Kevin Gosschalk, the chief executive and founder, said the money would be used to hire employees and further develop its corporate platform to protect consumers from account takeovers, fake account abuse, crawls, spam, gift card abuse and other fraudulent activities.
Core anti-fraud mechanism
Given that there is an average of one hack every 39 seconds, the platform developed by Arkose Labs could be a boon for businesses that handle sensitive data.
Some of the current mainstream online fraud detection tools are based on behavioral analysis or risk scoring mechanisms, and these methods are inherently flawed. Arkose’s detection analyzes data from the user’s session to determine the context of each request, behavior, and past creditworthiness.
Current fraud detection methods
Based on the risk score, the platform shows users the challenge of distinguishing between real users and fraudsters: delivering real requests to the enterprise, rather than real requests, is controlled by the system.
The dynamic risk engine Arkose Detect taps behavior patterns across devices and networks in real time for behavioral analysis and anomaly detection. It analyzes and categorizes requests based on potential user intent to notify dynamic authentication challenges and find hidden traces of fraud based on data over time for sessions and behavior patterns.
Arkose Enforce, on the other hand, is a bilateral human-machine recognition of remote sensing node-decision engine (Enforcement), which can be used in conjunction with Arkose Detect and authenticate requests in 31 different languages.
Telemetry sample diagram
The response is generated from proprietary visual data (millions of security images orchestrated from 3D models, each time a unique view image is generated for the user, each image identified with each defense strategy) that is clearly not recognized or classified by the AI algorithm, but prevents an attacker from predicting Arkose Enforce’s future behavior.
And through each assessment to help improve the system, provide some easy-to-implement dynamic conversion mechanisms to update the defense strategy, can effectively improve the efficiency of online fraud detection.
Anti-online fraud prospects
Arkose said it has significantly expanded its customer base in recent months, which now includes brands such as EA, Twilio, Roblox, Kik and Singapore Airlines.
Today, Arkose Labs employs approximately 74 people and is headquartered in San Francisco with an office in Brisbane, Australia. Microsoft’s venture capital fund, M12, led the financing as a lead investor, with existing investors PayPal and USVP participating in the round.
Some applications of anti-fraud technology
As you can see, online fraud detection and prevention is a potential market, with estimates of $43 billion worth by 2023.
Barcelona-based Red Points, which provides online tort detection and elimination tools for brands such as beauty, clothing, luxury, sports, toys and homewares, has recently raised $38 million.
In March 2018, fraud detection start-up Sift Science raised $53 million in financing, bringing its total to $107 million. DataVisor, another company of its kind, was also reluctant, developing fraud detection software based on machine learning algorithms and earning $40 million in the same year.
Other profitable online fraud detection companies include CashShield, Forter, Shift Technology, Featurespace, Pindrop, Simility and RedMarlin.