Quickly spin up new and customizable data science projects on the cloud.

Organizations are looking to artificial intelligence (AI) to make better business decisions. AI can help leaders reimagine business models, automate decisions and shape future outcomes. AI also allows people to do higher value work and solve more complex problems.

However, AI is also hard work. It requires organizations to carefully consider the tools, operating models and talent that they have in place. And one of the most difficult parts of working with AI is just getting started. Many organizations need “as-a-Service” tools that are easy to use, set up and require little-to-no maintenance.  

But even with tools delivered as-a-Service, figuring out how to use AI with your own data, use case and industry can take a while. That’s why we’ve introduced new industry accelerators to help our customers quickly get started with AI that is tailored to their own business needs by using IBM Cloud Pak® for Data as a Service.

Kick-start AI with industry accelerators

Industry accelerators are downloadable and customizable sample applications built for specific use cases to help business leaders and data scientists address specific challenges.

These industry accelerators offer a great way to get started on data science projects on IBM Cloud Pak® for Data, a unified platform for data and AI.  The accelerators each provide a pre-built package of assets that demonstrates how to address common business issues. A typical package shows how to work with data and use it to train a machine learning model. Further, it shows how to use governance and analytics to build trust in the results.

Industry accelerators help organizations advance from demonstration to implementation in hours, rather than weeks or even months. They help companies close the data science skills gap and expedite personalization strategies to meet unique business needs.

IBM Cloud Pak for Data as a Service

IBM Cloud Pak for Data as a Service provides fully managed and integrated data and AI services that simplify and deliver a unified experience. Whether you’re facing challenges in data operations, the AI lifecycle or just want to get data science projects up and running quickly, IBM Cloud Pak for Data as a Service empowers users at all technical levels to easily tap into the power of trustworthy AI with a large ecosystem of components and services.

IBM Cloud Pak for Data as a Service integrates seamlessly with industry accelerators. Typically, these services work in concert to create and demonstrate an end-to-end scenario:

How can you leverage industry accelerators?

You can leverage an industry accelerator in a couple of ways. Use it as a targeted demo to review the capabilities of IBM Cloud Pak for Data as a Service technologies or customize the assets and use with your own data to tackle your next data science project. With a business glossary, sample data, notebooks, scripts, sample applications and more, you can quickly get started with your own implementation.

The following diagram illustrates a typical accelerator workflow. Each use case allows you to clean and prepare data, run machine learning algorithms and score the resulting model. There are also sample dashboards to display the results interactively and API endpoints that you can call from other applications:

Industry use cases

Let’s go through the most requested industry use cases.

Financial Markets

Financial Markets Customer Segmentation: This accelerator helps to identify patterns of behavior to boost predictive accuracy, target the right potential customers and improve customer journeys. A wealth adviser can use this type of application to classify clients, go beyond the traditional demographic markers such as age and income and identify common business behavior patterns based on their financial goals and practices:

Example of the customer segmentation dashboard using the Financial Markets Customer Segmentation accelerator.

The overall dynamic segments of clients are divided based on their similarity and market-based information. The model considers and automatically selects the features best suited for categorizing the customer segments and their top statistics. The accelerator flow also populates the data returned from a segmentation API pipeline, which includes individual customer segment assignments and feature ranges of each segment, to create a visualization that represents customers within their corresponding segments:

Financial Markets Customer Attrition Prediction: This industry accelerator helps you to predict which customers are at risk for attrition. Wealth advisors can understand why their clients are leaving and prevent their attrition by identifying the ones likely to leave and presenting them with recommended remedial ideas to retain those clients.

Financial Markets Customer Offer Affinity: This industry accelerator helps you predict which products the customer is most likely to consider or purchase. A wealth advisor would be able to use this use case and plan for making the best offers to the client by understanding them and their financial interests better.

Energy and Utilities

Utilities Customer Attrition Prediction: This industry accelerator provides likely causes of customer attrition in the industry. The purpose of this use case is to identify customers that are more likely to switch energy providers. This information allows utilities providers to send proactive offers to keep customers from leaving. The accelerator highlights business metrics for the providers, customer filtering options for segregation and insights to optimize the attrition targeting:

Example of insights from Utilities Customer Attrition Prediction accelerator.

This use case highlights analytical and statistical trends that provide insights based on historic data and real-time predictions from machine learning models. The real-time predictions are made by scoring the model using APIs. The scoring process uses the machine learning model that was trained on customer data. When presented with new client data, the model predicts their likely behavior in real-time with a confidence score so you can tailor your business response.

Utilities Customer Micro-Segmentation: Customer micro-segmentation is a program used by utility companies to divide a company’s customers into small groups based on their lifestyle and engagement behaviors. This accelerator gives an example of how micro-segmentation can be used in IBM Cloud Pak for Data as a Service.


Insurance Loss Estimation Using Remote Sensing Data: This accelerator shows how to derive insights from remote sensing data, using an example of studying flooding events based on satellite imagery, for assisting insurance claims.

Accelerate your insights – get started with an industry accelerator

As you can see, our industry accelerators make it fast and easy to introduce AI to your organization’s use cases. To get started with any of these projects, visit the IBM Cloud Pak for Data as a Service Gallery. Choose an accelerator and put it to work for your organization.

For more information and to talk with an expert, schedule a consult.

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