Salford Predictive Modeler (SPM)

Over thirty years of credit risk modelling expertise wrapped into model building software for today’s age of machine learning. Modeller is a feature-rich, flexible, interactive and transparent tool that helps organizations get the best from their analytical teams. It supports a choice of techniques, the rapid development of powerful models, full explainability and the advancement of less experienced team members. Choose from numerous modeling techniques, including machine learning, for optimal predictive accuracy – especially on datasets with multicollinearity and complex interrelationships. Create industry-standard continuous and binary target models at the click of a button. Use decision tree modeling with CART and CHAID trees. Choose from logistic regression, elastic net models, survival analysis (Cox PH), random forests, XGBoost, stochastic gradient descent and more. Export options for implementation in other scoring and decisioning software include SAS, SQL, PMML and Python.

Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.