Expert Review: James Taylor Takes a First Look at the Zoot Solutions Platform

James Taylor is the CEO of Blue Polaris, former Decision Management Solutions, and one of the best-known voices in digital decisioning. On his blog JT on EDM, he reviewed the Zoot Solutions platform.

His verdict: Zoot sits in “an interesting middle ground”. Zoot runs the infrastructure. The client keeps control of the data and the decision logic.

The review covers the platform as a whole – from customer acquisition and fraud detection to credit origination, collections and recovery. Here is what stood out to him.

• One design environment, one runtime. The client’s own team configures the decisioning in WebRules® Builder. WebRules® Live executes it. Taylor highlights the modular design, test-driven development and reuse of ready-made components.
• Hundreds of microservices in seven areas. From data acquisition to decisioning to extensions such as machine learning models. Taylor sees the wide choice of ready-made data connectors as a key differentiator.
• Decision logic owned by the client. Rules, decision tables, a visual flow builder with reusable sub-flows, and point-and-click data mapping. External models can be plugged in and run alongside approved logic before going live.
• Testing and traceability built in. Sample data from third-party interfaces, API and unit tests inside the design tools, and a full trace of every decision.
• Managed infrastructure, client-owned data. Resilient data centres. All production data goes back to the client’s own systems.

The review was published in 2021. The fundamentals Taylor describes are still the foundation of the Zoot Solutions platform today – but each of them has grown.

The data layer now spans 480+ connectors across 150+ provider brands, from credit bureaux and open banking to fraud, IDV and AML services. One connection reaches all of them.

Builder now runs in the browser. No local Java installation, any operating system.

And the “partner region” Taylor noted in 2021 is now how AI works on the platform. An AI model is set up in Builder just like any other data source. The client’s team decides when it runs, which data it sees and what it does with the result. The model reads, checks and recommends. The decision is still made by the client’s own rules.