DataOps, governance and resilience dominate 10th QA Financial Forum New York

Michiel Willems
May 13, 2026

Senior QA, quality engineering, DevOps, DataOps and technology risk leaders from across banking, payments, capital markets, fintech and enterprise technology gathered at the Harvard Club of New York City for the QA Financial Forum New York 2026, as financial institutions face mounting pressure to modernise software delivery while tightening governance, resilience and AI oversight.

This year’s Forum arrived at a pivotal moment for the industry. Across banking and financial services, quality engineering teams are increasingly being pulled into wider conversations around operational resilience, AI governance, cloud risk, observability and enterprise-wide automation strategies.

Against that backdrop, this year’s agenda focused heavily on how financial firms are embedding AI into engineering workflows, modernising test data strategies, scaling DevSecOps and redefining the role of QA inside highly regulated environments.

*Gold sponors at this year’s event in New York City*

The event featured speakers from banks, fintechs and enterprise software providers including Bread Financial, Morgan Stanley, Bank of America Merrill Lynch, Citi, Fidelity Investments, CLS Group, Apex Fintech Solutions, Qube Research & Technologies, OpenText, Digital.ai, Qase and iceDQ.

The speaker roster reflected the increasingly strategic role quality engineering now plays across financial services technology organisations.

Among the banking and financial services leaders appearing were Rakesh Sukla of Bread Financial, Jayesh Garala of Morgan Stanley, Pawan Gaitonde of Bank of America Merrill Lynch, Seth Shenkman of Citi, Rangoli Mathur of Fidelity Investments, Tatyana Z. of CLS Group, Richesh Pareek of Apex Fintech Solutions and Lev Yatsemyrskyi of Qube Research & Technologies.

They were joined by technology and QA specialists including Julio Arteaga and Monica Hovsepian of OpenText, Rahee Khan of Digital.ai, Vitaly Sharovatov of Qase and Subu Desaraju of iceDQ.

Together, the agenda covered everything from AI-driven testing and enterprise observability to DevSecOps pipelines, synthetic test data, risk-based testing and the operational realities of delivering software inside heavily regulated financial institutions.

*Evol Greaves of Betterment in conversation with Matthew Crabbe in NYC*

Operational control

Artificial intelligence dominated some discussions throughout the day, particularly as banks shift from isolated pilots toward broader deployment of AI inside software engineering and testing workflows.

This year’s sessions explored how AI is being integrated into automated testing, orchestration, defect prediction, impact analysis and release prioritisation, while also examining the governance challenges that emerge as firms rely more heavily on AI-assisted engineering.

*Hod Rotem and Haim Arava (right) of K2view at the event*

For QA teams, the challenge is increasingly no longer whether to use AI, but how to control, validate and monitor it inside complex enterprise environments.

That wider shift featured prominently in sessions involving OpenText’s Julio Arteaga and Monica Hovsepian, where discussions are expected to focus on the evolving “self-driving enterprise” model and how AI-driven automation changes testing, observability and software assurance requirements across financial services.

The agenda also examined how firms can build AI-ready engineering organisations without creating new operational or compliance risks.

*Dharani Sundaram (left), Seth Shenkman, (centre) and Hod Rotem (right)*

During a panel discussion, Dharani Sundaram, SVP at Bank of America, Seth Shenkman, SVP at Citi and Hod Rotem, chief product evangelist at synthetic data specialist K2view, shared a panel, discussing how AI is transforming business-driven testing requirements, particularly the need for growing volumes of secure and scalable test data.

Sundaram focused on the testing requirements for Agentforce, the agentic Salesforce platform, and Shenkman discussed testing for the FIX trading protocol.

*Dror Avrilingi of Amdocs addressing the Forum in NYC*

Dror Avirlingi (above), CTO of Amdocs Studios, discussed how firms can cross the ‘Quality Breakpoint’, as AI systems become more autonomous.

Traditional quality assurance approaches were not designed for systems that generate code, make decisions, and continuously adapt. Avirlingi explored how quality engineering must evolve to address this shift.

Test data and DataOps become critical priorities

Test data management and DataOps emerged as another major theme throughout the Forum.

As financial firms operate across increasingly fragmented architectures, partner ecosystems and cloud-native environments, the ability to provision realistic, production-grade test data quickly has become a major bottleneck for many QA organisations.

Bread Financial’s Rakesh Sukla addressed those challenges directly from the perspective of a large-scale financial services engineering organisation.

“Companies in this space in highly regulated companies like Bread Financial and other fintech in this space, we do face the issues around test data,” Sukla said.

“I would definitely categorise this as one of the very top things faced by pretty much across the industry. It’s definitely a huge problem to solve.”

Sukla also warned that many traditional approaches are no longer sustainable.

“The traditional practice, I would say, is not really scalable because it’s manual, it is written in spreadsheets, people are going through line by line in that,” he said. “Those things are not scalable.”

That focus on scalable, automated and API-driven data provisioning resonated strongly with many attendees as firms continue modernising enterprise QA pipelines.

Vitaly Sharovatov and Richesh Pareek spoke about the responsible use of AI

Risk-based testing and observability

Another key topic that dominated the agenda was the growing convergence between observability, monitoring, incident response and quality engineering.

As regulators increase scrutiny around operational resilience and technology risk, QA teams are increasingly being asked not only to validate software releases, but also to demonstrate traceability, reproducibility and evidence-ready governance controls.

*A panel discussion at the Forum led by QA Financial CEO Matthew Crabbe*

The ability to reproduce incidents quickly and accurately is becoming particularly important.

“Generally when an incident happens, like the first thing that we want to do is exactly reproduce what happened in production in our lower environment,” Sukla explained.

“So in that particular point of view, like the quality of data and how quickly you can create it is really paramount.”

That theme connected strongly with sessions involving enterprise observability, distributed tracing, risk profiling and incident-driven testing strategies

Several sessions also examined how AI is changing the economics and operational structure of software testing itself. That evolution toward AI-supported quality engineering was one of the defining conversations of the day.