Yields.io is the first FinTech platform that uses AI for real-time model testing and validation on an enterprise-wide scale.

Our model risk management solution has three main modules. The data lake component allows model validators and developers to apply data governance at scale. Our validation and monitoring module merges statistical tests with ML algorithms to created structured validation documents and to detect model issues in real-time. All this data is then fed into a model inventory component that links process workflow and quantitative data together. This allows for C-level dashboards that summarize real-time model quality while simultaneously supporting detailed drill down for the technical teams.

Yields.io was founded by Jos Gheerardyn and Sébastien Viguié in 2017. Our R&D team counts numerous senior data scientists and quantitative analysts while our sales team is composed of experienced risk management professionals. The company has its offices in London (UK) and in Gent (Belgium) and is backed by investments from Volta Ventures (early-stage European VC) and Michel Akkermans (serial entrepreneur, private investor, and former CEO and chairman of Clear2Pay).

Xenomorph provides trusted data management solutions to many of the world’s leading financial institutions. The company has more than two decades’ experience managing large volumes of complex data and analytics. Over that time, we have consistently reinvested in our technology, culminating in our latest generation enterprise data management platform TimeScape EDM+.

Our software is built to be future-proof. With our rules-based single-stack architecture, flexible data model, easily configurable workflow engine and integrated feature updates, TimeScape EDM+ empowers you to address any future requirements. It can be operated by business users without any prior programming expertise, which means it offers a truly agile and cost effective solution to address evolving business, regulatory and technology trends. The platform also excels at managing and validating model-derived data, thereby enabling firms to address their model risk management challenges by making sure inputs and outputs of business critical models are always validated and kept in sync.