Provenir AI for Advanced Risk Machine Learning
Challenge
The surge in volume, velocity and variety of data allows organizations to harness advanced Machine Learning algorithms to make better, faster decisions. However, this approach poses some challenges regarding algorithm selection, explainable predictions, scalable infrastructure and data diversity.
Our Solution: Provenir AI
Provenir AI enables organizations to rapidly build, deploy and monitor predictive, explainable and scalable advanced Machine Learning algorithms.
Selection: Choose the most appropriate algorithm (Gradient Boosting Decision Trees, Random Forests, Deep Neural Networks, etc.) depending on the nature of the dataset, and the use case.
Explainability: Through a careful adoption of SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME), explain how and why your model has made a certain prediction.
Scalability: Reduce the development time from months to days; automatically train, test, monitor and manage your model through our MLOps capability.
Diverse data: By leveraging traditional and alternative data, improve your model accuracy, while reducing bias and promoting financial inclusion.
Applications:
Our solutions help organizations efficiently train appropriately selected and explainable advanced Machine Learning algorithms that can be seamlessly deployed, monitored and re-trained in Provenir’s unified decisioning platform. Make smarter, faster and more accurate risk decisions, which enables enhanced credit and fraud risk management.
