What is an accelerator?
Get personal with your banking and insurance clientele
Streamline your loan process
Evaluate risk and facilitate decision-making
Get your automated credit models up and running faster
Automation with the right digital assets can provide a streamlined loan process and drive more efficient management
Leverage machine learning models to enhance your evaluation and build recommendations for your client
Reskill or upskill to simplify your decisions from predictions to improve your loan approval and recommendation process.
End-to-end AI Ladder application
An architecture enabling you to extract meaning from your data to pre-approve loans and provide tailored recommendations
From cataloging data through a glossary of terms to model development and deployment, simplify the lifecycle of your AI project
Composable and extensible pattern that can be applied to new data and industries
Start experimenting today. Download and use this accelerator in your Cloud Pak for Data instance. Refer to the README file to get started.
Kick-start your data science solution with this accelerator.
IBM Cloud Pak for Data
Built on Red Hat OpenShift Container Platform, IBM Cloud Pak for Data accelerates your journey to AI to transform how your business operates with an open, extensible data and AI platform that runs on any cloud.
Watson Knowledge Catalog
Help your data users quickly find, curate, categorize and share data, analytical models and their relationships with other members of your organization.
Empower your data science and AI teams to refine data and visually build and deploy models, using data on the desktop for anytime, anywhere access.
An award-winning development capability to automate Data preparation and Model development, and help simplify AI lifecycle management cycle.
Customer Offer Affinity
Identify the right financial products and investment opportunities for new and existing clients.
Easily differentiate between client segments by identifying patterns of behavior.
Mitigate loan defaults by anticipating at-risk accounts early on.