IPQS Device Fingerprinting vs. Ekata

Leverage over 25 unique data metrics to gain in-depth insights into device fingerprinting that evaluates both risks and device traits. The device fingerprinting solution offered by IPQS serves as a remarkable fraud detection tool, adept at identifying even the most cunning fraudsters, malicious actors, and cybercriminals. By examining more than 300 data points—including operating systems, screen resolutions, and installed fonts—it successfully reveals counterfeit devices, location spoofing, and dubious behavior linked to a user’s online presence. This innovative technology is capable of recognizing bots, automated actions, device impersonation, and other signs that may indicate fraudulent motives. You can opt for JavaScript device fingerprinting for web environments or utilize our SDKs tailored for mobile applications across both iOS and Android platforms. With its powerful risk assessment features, IPQS effectively identifies fraudulent accounts, chargeback attempts, credential stuffing incidents, and automated activities that suggest misuse. Moreover, the Device Fingerprinting solution from IPQS is proficient in uncovering advanced fraud strategies, including those involving cutting-edge emulator software, thereby providing a holistic defense against emerging threats. This state-of-the-art detection system not only bolsters security measures but also plays a pivotal role in helping businesses preserve trust among their genuine users, ensuring a safer digital ecosystem. Overall, the comprehensive analysis delivered by this technology enables organizations to stay one step ahead of potential fraud.

Detecting and preventing the creation of fake user accounts is crucial in order to protect loyalty programs from those attempting to take advantage of them. Organizations can significantly improve their risk evaluation processes by cross-referencing customer data with trustworthy external sources. To combat payment fraud effectively, it is essential to make accurate risk judgments at every phase of the transaction, whether it be prior to, during, or following authorization. Simplifying the authorization process is key to reducing friction for customers as they make purchases. The Ekata Identity Engine employs sophisticated data science and machine learning methods to merge two distinct datasets: the Ekata Identity Graph and the Ekata Identity Network. These datasets emphasize critical identity features, converting them into actionable insights that enable businesses to conduct thorough risk assessments of their customers. By validating a larger volume of legitimate interactions, companies can broaden and sustain their customer base. Furthermore, identifying more fraudulent activities allows organizations to protect their financial assets more effectively. Swift risk evaluations facilitate the approval of additional legitimate transactions, thus ensuring the prevention of fraud while simultaneously embracing more reliable customers. This strategy not only enhances security protocols but also fosters improved customer satisfaction and loyalty over time, which can lead to long-lasting business success. The combination of advanced technology and thoughtful risk management creates a more secure and efficient transaction environment for everyone involved.