Case Study: How Enzo Accelerated Their Time to Market

Meet Enzo

Enzo is a collection of financial tools designed to empower millennials to build their dream lives.

While Enzo offers its customers a rewards based checking account, such as cashback on rent and mortgage payments, Enzo’s real power lies in what they’re building; an all in one money management platform in a beautifully designed app.

By aggregating spending, saving, investing and planning into a single location, Enzo empowers its customers to optimize their most important money decisions. Combine this with other innovative features like rewards checking accounts, and long-term oriented investments, Enzo is challenging the status quo for consumer banking.

The Challenge

When Enzo started to build their platform, they knew that customer financial transaction data would be a crucial ingredient to their customer experience. In fact, this data would be the face of their platform. Specifically, Enzo wanted accurate merchant names and logos to show consumers where they spent money, and contextual labels to provide insights into how they spent their money.

What Enzo quickly realized though is that the transaction data they had to work with was raw - it came unstructured, inconsistent, and with key missing information (such as location, logo and labels).

With thousands of Enzo customers transacting across thousands of disparate merchants, locations, and payment providers, Enzo would need an efficient way to normalize and enrich the merchant and transaction information of millions of transactions a day.

Enzo was faced with two options:

1. Spend additional time and resources hiring a team of data scientists to build a tool to enrich their data in-house
2. Partner with a solution that would make it easy and cost effective to use their transaction data, and in real-time 

The Solution

Enter Ntropy. Enzo evaluated the time and resources it would take to build in-house, as well as several potential partners; but there were three core factors that led to Enzo’s decision to partner with Ntropy.

• Ease and speed of deployment of Ntropy’s API: Enzo estimates it would have taken close to 1 year to build v.s just days to fully deploy the Ntropy API

• Cost efficiency compared to building in-house: Enzo estimates it would have cost $500,000 to hire full time data scientists, compared to Ntropy at a fraction of the cost

• High degree of accuracy of Ntropy labels and merchant information compared to other tested solutions: Consumer transaction accuracy is above 90%

The Ntropy API now provides the Enzo Product Development team with organized data in real-time, so that they can focus on building a better banking platform. One that is ahead of even some of the largest financial institutions.

For Enzo, the decision to partner with Ntropy was easy.

“We knew that from a time & resource perspective we did not want to build this inhouse - it didn’t make sense for us to be both a bank and a data science team. After looking at other vendors we found Ntropy’s API to be the most scalable, accurate and adaptable to our business needs:The tech is supported by a team of experts in data science and machine learning. Working with them is an extremely collaborative process; Because we made the decision not to build this in-house, the Ntropy team is like an extension of ours.”

Jeremy Shoykhet, Enzo CEO