It’s been a while since I did a product review on the blog, but I recently caught up with the team at Zoot and thought a blog post was in order.
Zoot, for those of you who don’t know them, deliver capabilities and services for automated decisioning across the customer credit lifecycle. They’ve been at this a while – 31 years and counting – and focus on delivering reliable, scalable and secure transactions in everything from customer acquisition, to fraud detection, credit origination, collections and recovery. They have some very large financial institutions as clients as well as some much smaller ones and a number of innovative fintech types.
Zoot’s customers all run their systems on Zoot infrastructure. Zoot has 5 data centers (2 in the US, 2 in the EU and a new one in Australia) for regional support and redundancy – though each is designed to be resilient independently and is regularly reviewed to make sure it can support 10x the average daily volume. These data centers run the Zoot solution framework – tools and services supporting a variety of capabilities including data access, user interfaces, decisioning and more.
The core of the Zoot platform is the combination of the WebRules® Live execution service and the WebRules® Builder configuration tools. These cover everything from designing, developing and deploying workflow and user interfaces to decisioning, attributes and source data mapping. Zoot’s focus is on making these tools and services modular, on test-driven development, and on reusability through a capabilities library. The same tools are used by Zoot to develop standard capabilities and custom components for customers and by customers to extend these and develop new capabilities themselves. Most clients begin with pre-built functionality and extend or customize it, though some are starting to use Zoot in a Platform as a Service way, building the whole application from scratch to run on the Zoot infrastructure.
Zoot’s library consists of hundreds of capability-based microservices across 7 broad areas:
- Access Framework, functions as a client gateway and makes it easy to bring real-time data into the environment and manage it.
- User interface, to define responsive, mobile-friendly UIs that create web-based pages for customer service and other staff.
- System automation, to handle background and management tasks.
- Data and Service Acquisition, to integrate third party data into the decisioning from a wide range of providers and internal client systems.
- Decisioning, to apply rules to the data and make decisions throughout the customer credit lifecycle.
- Data Management, to manage the data created and tracked through the workflow, store it if necessary and deliver it to the customer’s environment.
- Extensions, to fulfill the unique needs for clients, such as machine learning and AI models.
One of the key differentiators for the Zoot platform is the enormous range of data sources they provide components for. Any data source a customer might reasonably want to access to support their decisioning is integrated, allowing data from that source to be rapidly pulled into decisions without coding. Even when clients come up with new ones, Zoot says they can quickly and easily add new sources to the library.
WebRules Builder is a single environment for configuring and building all kinds of components. A set of dockable views can be used to manage the layout and users can flag specific components as favorites, use search to find things across the repository and navigate between elements that reference each other.
A flow chart metaphor is widely used to define the flow of data and logic. Components can be easily reused as sub-flows and the user can drill down into more detail when needed. Data is managed throughout the flows and simple point and click mapping makes it easy to show how external data is mapped into the decisioning. Flows can be wrapped around inbound adaptors to handle errors, alternative data sources etc. Libraries exist, and custom versions can be created with a collection of fields, flows, reports and other elements. These can be imported into specific projects, making the collection of assets available in a single action.
Within these flows the user can specify logic as either rules or decision tables. Decision tables are increasingly common in Zoot’s customers, as in ours. A partner region allows for external code to be integrated into the client’s processes – for instance a machine learning model or external decisioning capability. An increasing number of clients are using this to integrate machine learning with their decisioning – though some of this is parallel running to see how these more opaque models compare to the established approaches already approved by regulators. Debugging tools show the path through the flows for a transaction and all the data about the flow of transactions – which branch was taken, which rules fired – can be recorded for later analysis outside the platform.
Sample data for testing can be easily brought in and Zoot provides sample data from their third party data interfaces also to streamline this process. APIs and interfaces can be tested inside the design tools, with data entered being run through the logic and responses displayed in situ. Unit tests can be defined, managed and executed in the environment. Clients can handle their production data entirely outside Zoot, passing it in for processing, but a significant minority of clients use database capabilities to store data temporarily on the Zoot infrastructure. System scripts are used to make sure that all the data ends up back in the client’s systems of record and data lake when processing is complete.
Zoot occupies an interesting middle ground among decisioning providers. Everything is hosted on their infrastructure – clients don’t have the option to run it on their own infrastructure – and Zoot has invested heavily in providing a robust infrastructure to support this. Yet Zoot is not trying to “own” the customer data or do multi-customer analysis, as many SaaS and PaaS companies are – their customers own their own data. Indeed, Zoot makes a point of pointing out that all the data gets pushed out to the client nightly or weekly. This gives clients a managed infrastructure without losing control of their data, an interesting combination for many I suspect.
More on the Zoot platform at https://zootsolutions.com
