Oscilar vs. IBM Safer Payments

Oscilar is an innovative no-code platform that utilizes artificial intelligence to streamline risk decision-making processes, specifically designed for fintech companies to adeptly handle challenges surrounding fraud, credit, and compliance. It acts as an all-encompassing tool for handling risk, fraud, and credit assessments, enabling users to minimize engineering hours through automation while eliminating the necessity for coding skills. The platform incorporates machine learning models that are tailored to your specific data, continuously enhancing its functionality by learning from user interactions and behaviors, which allows for the automation of a large portion of risk-related decisions. This solution is particularly beneficial for those wanting to advance operational rules and workflows without needing to write any code, as it simplifies the creation and alteration of these rules. Users can also evaluate changes through various simulations, including unit tests, backtests, shadow tests, and A/B tests, facilitating a seamless shift from local environments to staging and subsequently to production. Oscilar delivers a real-time, holistic view of users and their transactions by effortlessly merging both internal and external data sources with minimal effort. Moreover, the platform can be tailored to address specific risk management needs, providing decision-making workflows that integrate rules, machine learning models, velocity counters, and more, all presented through an intuitive interface. This adaptability ensures that organizations are equipped to swiftly tackle emerging risks while retaining oversight of their decision-making practices, ultimately enhancing their operational efficiency and responsiveness. By offering these customizable features, Oscilar empowers users to make informed decisions and stay ahead in a rapidly changing financial landscape.

IBM Safer Payments enables organizations to create personalized and user-friendly decision models that facilitate rapid responses to emerging threats while improving fraud detection accuracy and speed, without the reliance on external vendors or data scientists. This innovative solution significantly accelerates the modeling optimization process by providing essential analytics and simulation tools that support continual monitoring of business performance and adjustments to changing fraud patterns. Clients benefit from remarkable detection rates and a reduction in false positives upon integrating this system into their workflows. Users have the capability to build, assess, validate, and deploy machine-learning models within days rather than months, thereby eliminating vendor dependency. The platform is capable of handling thousands of transactions per second, delivering an enterprise-level solution with an impressive 99.999% uptime and outstanding throughput. Its open architecture allows for seamless importation of detection models, model components, and proprietary insights, all while offering a comprehensive interface for the development of new models. Furthermore, it accommodates a diverse array of data science, machine learning, and artificial intelligence techniques, making it an adaptable resource for any organization seeking to bolster their payment security. The inherent flexibility of this platform ensures that businesses can proactively address potential fraud threats more efficiently than ever, ultimately leading to a more secure financial environment. As organizations continue to evolve, the ability to swiftly adapt to new security challenges becomes increasingly critical.