Model validation service of the year
Yields.io offers a comprehensive model risk platform for automating and industrialising model validation and monitoring. It offers a cost-efficient approach to model risk and aids compliance with regulatory initiatives and international standards such as the European Central Bank’s Targeted Review of Internal Models, the Bank of England Policy Statement (PS) 7/18, the US Federal Reserve’s Supervision and Regulation Letter (SR) 11-7 and others.
The solution has three components. First, a data governance module centralises all data needed for model risk in a distributed data lake. The module supports data lineage, data versioning and the measurement and analysis of data quality. Then, an analysis module provides an interactive workspace for validators to investigate models, measure performance using numerous statistics and compare models with automatically generated benchmarks. It can be used to automate periodic validations, while specified analysis can be run continuously for ongoing monitoring and to detect issues in real time. Last, reporting module generates both technical validation documents for risk managers and audit, and creates interactive dashboards for senior executives.
Financial institutions use Yields.io across the three lines of defence. First-line use cases include pre‑validation – automated model testing and report generation – and ongoing monitoring of models such as those for valuation and various types of valuation adjustment. Second-line applications are centred mostly on automating and industrialising the validation process. In the third line of defence, institutions use the platform to create additional challenges to models.
The Yields.io platform is generic and not restricted to any single model type. The solution is available on-premise as well as Software-as-a-Service on the cloud. It enables institutions to make a strategic commitment to owning the validation process, not outsourcing it. The platform guides users through the full model validation process in a natural fashion, enabling a unified approach to model risk management (MRM) across the enterprise.
To improve the speed of validation, clients can use artificial intelligence (AI) for data quality analysis and model benchmarking, embedded in distributed infrastructure to deal with massive datasets. A large part of model risk is related to analysing data quality and industrialising the process. Yields.io’s capabilities in these areas are why it can generate model validation documents that are compliant with the strictest regulatory frameworks such as SR 11‑7 and PS 7/18.
Emmanuel Lesur, head of sales at Yields.io, says: “MRM is going through an industrialisation phase, and at Yields.io we support our clients’ transition to this new era through its state-of-the-art technology platform that allows them to validate and manage both classical and machine learning models. Our solution uses AI to automate MRM, which means our clients can spend more time investigating exceptions. Our data and model monitoring functionality helps our users build more robust analytics. Better MRM is needed to remain competitive in a world full of algorithms and AI. We are delighted to have won this award from Risk.net as it recognises our hard work, experience and vision in this area.”
“The Yields.io solution integrates the most important steps in model validation into one platform and takes into account the critical regulatory standards. Users can experiment with AI features to see to what extent they are useful for validation.”
“Yields.io offers a generic model validation platform that satisfies a number of requirements. Their client references are positive. This is a marketplace that is not yet fully defined and developed, but the company is well placed to succeed further.”