Outseer Fraud Manager vs. Oscilar

Outseer Fraud Manager is an advanced platform designed to oversee transactional risk, utilizing state-of-the-art machine learning algorithms combined with a powerful policy engine to thoroughly assess and mitigate risks throughout the digital customer experience. By leveraging insights gained from innovative data science methodologies validated in high-risk contexts, organizations can better protect themselves against new fraud trends through exclusive consortium data. Users benefit from risk models honed through the analysis of billions of transactions from major financial institutions worldwide. This platform also facilitates the smooth integration of insights from both authentication and payment processes, improving risk scoring by considering signals from both first-party and third-party data sources. With the ability to implement consistent risk controls across all customer engagements, businesses can effectively use standardized risk scores to find a balance between reducing fraud, enhancing customer satisfaction, and controlling operational costs. Furthermore, it allows for timely policy modifications in response to the constantly shifting threat landscape. Ongoing collaboration with a dedicated team of experts promotes continuous enhancements and enables comparative evaluations with industry counterparts. Ultimately, this holistic strategy positions organizations to proactively combat fraud while building and maintaining customer trust in an increasingly complex environment. By prioritizing these efforts, companies can stay ahead of potential threats and ensure a safer transaction experience for their clientele.

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.