Feedzai, the world’s first RiskOps platform, has achieved two significant accolades from Chartis Research. We are proud to be recognized as the leading AI-driven anti-fraud platform and to rank among the top 5 overall in the prestigious RiskTech AI 50 2024 rankings. These achievements underscore Feedzai’s pioneering role in leveraging artificial intelligence and machine learning to advance financial risk management. With an AI-first approach, our technology is designed to swiftly adapt to emerging fraud and scam patterns.
Fraud is already a complex challenge, but merchants face an additional hurdle: first-party fraud perpetrated by their own customers. Unlike second- or third-party fraud, first-party fraud occurs when consumers use their legitimate payment credentials to commit dishonest acts for personal gain. This creates a significant challenge for acquiring banks and payment service providers (PSPs) in assisting merchants with fraud prevention. To effectively support merchants, acquiring banks must develop a thorough understanding of how first-party fraud operates. This article explores how acquirers and PSPs
Acquiring banks often face the challenge of balancing merchant satisfaction with risk management. On one hand, they aim to keep merchants happy by enabling quick payouts. On the other, they must protect themselves from financial losses if a merchant's risk profile unexpectedly shifts. Dynamic risk assessment plays a crucial role in safeguarding acquirers while supporting businesses with the liquidity they need to operate smoothly. Here’s how Feedzai’s Dynamic Risk Assessment, available as an add-on to its Merchant Monitoring solution, helps acquirers mitigate risk while ensuring merchants maintain
Delivering an improved digital employee experience (DEX) has become a top priority for many enterprise IT leaders, as it directly influences productivity, employee morale, and other critical aspects of business success. However, many organizations still lack the necessary visibility into their IT ecosystems to fully understand how digital tools impact employee experiences and productivity. This gap often hinders efforts to effectively manage the digital workplace and provide employees with an exceptional experience.
Having spent many years immersed in IT and information security, I can confidently say it has been a rewarding journey. Over time, I’ve observed a significant shift in how organizations perceive cybersecurity. It has gained prominence and relevance, with the role of the Chief Information Security Officer (CISO) evolving positively. CISOs are no longer seen as mere “blockers” but as agents of change who actively contribute to business decisions, enhance visibility, and drive impactful organizational outcomes.
In today’s digital era, cloud computing has become a cornerstone of application modernization and digital transformation. By 2025, it’s anticipated that over 85% of organizations will adopt a cloud-native approach for application development. Yes, you read that correctly! The primary goal of this approach is to streamline development processes, enhance scalability, and boost agility. Unlike traditional methods, cloud-native development doesn’t follow rigid rules. Instead, it focuses on addressing unique business challenges and leveraging the most suitable software solutions.
Netskope offers a unique capability to deeply inspect network packets (post-decryption) and understand the interactions between users and the SaaS applications they use. This enables the application of granular policy controls to regulate specific actions, such as downloading, uploading, editing, posting, or creating content within any application. However, it’s essential to avoid imposing such restrictions on critical business applications like corporate email or OneDrive that employees rely on for their daily tasks.
Augmented analytics represents a groundbreaking approach that integrates artificial intelligence (AI) and machine learning (ML) to unlock deeper insights from data. By automating data preparation and uncovering hidden patterns, it generates actionable recommendations that address the shortcomings of traditional BI systems. The driving forces behind this innovation include the explosion of data volumes, advancements in AI, and heightened customer expectations for faster, smarter decision-making.