Inside look: Taking aim at data processing blockages
A startup is looking to automate the bulk of banks’ data processing workflows.
At a press conference in October 1963, President John F. Kennedy paused.
He had just been asked whether or not, in the wake of ongoing job losses due to workplace automation, it was good for human beings to continue down this modernizing path. Collecting himself, Kennedy reasoned with the reporter that the introduction of machines made the labor of people easier and that it was his intention to make life easier. “Automation does not need to be, we hope, our enemy,” he said.
Sixty years later, the debate continues.
After a new round of job losses at big banks and with new technologies demonstrating ways to make difficult tasks easier, innovative companies are striving for greater levels of automation in all areas. This is where startups like EZOps hope to come in.
The data automation company was founded in 2014 by Bikram Singh and his two business partners, Dutt Chintalapati and Sarva Srinivasan. Singh had spent the previous five years at Citi, most recently as global head of OTC derivative services. Over the course of more than two decades, he worked at Goldman Sachs, Lehman Brothers and Lava Trading, among others.
Setting itself apart from competitors like Xceptor, Frontier and Duco, EZOps’ platform blends a low-code interface with machine learning to identify and predict anomalies across the data processing lifecycle.
That person who has been doing this for the last 10, 20, 30-odd years knows exactly what buttons to press, who to call, and how to get things done when issues happen. Unless you can replicate and automate that, you are really putting yourself in a very precarious position
Bikram Singh
One of the bigger challenges the startup faces is preserving data sanctity, which is the process of minimizing potential leakage throughout the data processing lifecycle. “Data goes through multiple business processes, through multiple systems, and in some cases, it is even done manually. Through this preponderance of systems, it becomes a hodgepodge of processes that most of these financial institutions have to deal with,” Singh says.
Inefficiencies in the data processing business for banks are well documented. There are issues with data leakage, outdated legacy tech, and there’s a general lack of a seamless authority across each section of the process. The firing and retiring of back-office workers with extensive knowledge of legacy systems can create scenarios where the only people who understand the quirks of the software take that knowledge with them, and that knowledge is hard to replace.
“That person who has been doing this for the last 10, 20, 30-odd years knows exactly what buttons to press, who to call, and how to get things done when issues happen,” Singh says. “Unless you can replicate and automate that, you are really putting yourself in a very precarious position.”
Firms that want to minimize the effects of the brain drain taking place are compelled to further automate their processes, which offers an opportunity for companies like EZOps—which has coined its own phrase, “The Five R’s of Data Processing”—to represent the use-cases for its service. Though data reconstruction, reconciliation, research of breaks, remediation and reporting are services individually offered by a number of companies, EZOps combines all five onto a single platform.
Singh says the company had its first “eureka moment” when it was helping a client with a data reconciliation issue.
“As we started working with them, we figured out that reconciliation was only one part of the problem they were looking to solve. There were things happening before and after the reconciliation stage, and if we could help solve those things before and after, that was where the actual value would be for this client and every other client,” Singh says.
Jacks of all trades
When it comes to his company’s hiring strategy, Singh abides by an old adage: “A jack of all trades is a master of none, but oftentimes better than a master of one.” While he emphasizes each new employee should be “multi-faceted and techno-literate,” Singh explains that some subject-matter experts are also offered training in another discipline to increase versatility.
“It’s not reasonable to expect that someone will know everything, but if they have the right attitude and the intellectual curiosity, that is what we look for. Those people really thrive in our organization. In this business, it really helps if you’re a problem-solver at heart. I solve problems every day,” he says.
Despite the demanding nature of a hiring strategy that requires employee competence in many separate areas, it appears to have been no obstacle for the company’s growth prospects. Of the 170 employees currently at EZOps, 60 were hired in the last year, and the company expects to surpass 200 employees by the end of 2023.
The vendor’s applications do not end within the data processing space. Singh recounts experiences of improving banks’ quality-of-life features too, such as providing an alternative to often outdated legacy tech.
“Our clients are using us to get them off of Excel. There are banks that have been using Excel since the late 1990s, and some of those spreadsheets that were written then are still in existence. Whoever wrote it back then has moved on to other things, but that version has been carried on at the bank, labeled as a high-risk Excel-based project. Nobody even understands what goes in and what comes out. These are the kind of things these banks can’t do anymore.”
Singh has lofty ambitions for EZOps. While he says the company today is on track with its goals for long-term development, he ultimately wants it to reach benchmark status in the data processing world.
“In a short time, EZOps is going to be the benchmark that all other data management companies will be judged against in terms of features and functionality and the size of the problems they will solve. We don’t want to be known as a niche player. We solve a lot of problems like reconciliation, migration, regulatory compliance, reporting, and data transformation. We will be known as a leader in this space,” Singh says.
In the same press conference back in 1963, President Kennedy said that machines can make life easier for people, if people do not let the machines dominate them. It was a big “if” and a daring attitude to possess; he and Singh seem to share that idealism.
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