Top 10 Fraud Management Solution Providers 2022
Enterprises require more than a one-size-fits-all fraud defense plan in a world where digital identities have been compromised on a large scale. Arkose Labs offers a dynamic attack response that adapts to changing fraud strategies that jeopardize account security and trust. By diminishing the economic motives behind attacks, Arkose Labs provides long-term fraud protection & account security. Read More…
Fraudsters are smart and adaptive. When a traditional fraud detection solution is put in place, usually it works in the beginning, then the fraud detection performance slowly goes down over time. Moreover, even with difficulties, for companies that have an in-house fraud management tool, 88% of AI projects don’t land in production. Read More…
For a long time, businesses, especially in the banking sector have been suffering from the lack of well performing fraud management systems. Financial fraud within this digital era are constantly increasing therefore, risk and fraud management becomes a very key aspect for financial institutions and customers. Read More…
Identity and authentication fraud controls have traditionally and predominantly relied on static data to prevent ATO, but most static data has already been breached due to massive historical attacks, and the availability of such data on the dark web continues to flourish. One reason for this is often-used weak and non-unique passwords. Read More…
Cybersecurity and fraud management are the needs of the hour. Companies are facing many issues due to fraudsters. SEON assists online companies in lowering the cost, time, and issues associated with fraud. Whether it’s a global financial giant or a tiny eCommerce start-up, the solution streamlines fraud control so that a company can focus on its development and growth. Read More…
Detecting bot versus human conduct isn’t enough to put an end to ATO. Complex scripts and human-driven assaults can defeat rules-based bot detection systems. Bot defense based on rules only prevents one sort of ATO attack. Sift’s industry-leading, custom ATO machine learning model identifies real-time threats at the point of login with over 100 indicators. Read More…
Customers are often confused by transaction descriptors within their issuer billing statement or banking apps. Unfortunately, customers call their issuer 51% of the time to clarify confusion (AITE, Improving the Dispute Experience, 2021)or initiate a dispute, rather than contacting the seller who may be able toresolve the inquiry without escalating to a dispute. Read More…