When New York-based DailyPay first started looking to expand internationally in 2021, Managing Director Paul Hill advocated for Belfast. DailyPay quickly saw the benefits of Belfast’s quality talent pool and creative technology ecosystem, and invested £24 million.
Today, DailyPay Belfast has created 293 new jobs and is fast becoming the fintech giant's go-to for artificial intelligence innovation.
On-demand pay, powered by AI
DailyPay’s on-demand pay, that helps daily workers get their pay early if they want, is changing the way daily workers get paid. The scale is huge - DailyPay processes millions of pay period data points monthly, with each transaction requiring meticulous tracking for audit purposes.
So how do DailyPay manage that kind of scale while keeping fraudsters out? Artificial intelligence.
Angela Friend, Vice President of Data Science at DailyPay has led the team through an ambitious growth phase, integrating data science applications and expanding her team’s footprint into Northern Ireland.
DailyPay’s innovation centers on its on-demand pay platform, to not only meet the scale of the product her team has developed advanced machine learning models ensure employees have real-time access to earnings. The data science team in Belfast is deeply involved in shaping these models, developing systems for intelligent anomaly detection, enriched data ingestion, and platform observability.
For instance, Belfast engineers have built observability frameworks that monitor millions of transactions monthly, ensuring data integrity and transparency across the platform. Data scientists collaborate on anomaly detection tools that flag unexpected patterns in payroll processing—vital for accuracy and operational resilience.
Beyond these core functions, the team is also developing treasury forecasting models to help financial teams anticipate cash flow needs, directly impacting how pay can be delivered faster and safer to users.
Angela sees the Belfast team’s contribution as transformative: “Northern Ireland’s talent isn’t just supporting operations—it’s driving the technology behind our product and shaping how on-demand pay is delivered worldwide.” The investment is about more than job numbers; it’s about giving highly skilled local professionals opportunities to define the future of financial technology at every level.
"Fraud patterns are actually quite low, but they're somewhat unique,” she says. This uniqueness proves both blessing and curse - whilst fraud amounts tend to be small and rare, it means conventional fraud detection measures simply couldn't help.
"We had to build a custom solution in-house," she says. Working in Python within AWS's modular environment, her team has created something resembling digital Lego blocks - fraud detection systems that leverage user behaviour, statistics, and machine learning to understand patterns that might indicate fraudulent activity.
DailyPay’s innovative approach combines different AI methodologies. Why? Because "machine learning and AI serve different functions, and have strengths in different areas," Angela explains.
Last but not least, DailyPay uses AI to support daily workers using on-demand pay with an AI-powered chatbot integrated into support systems. Paul says their Net Promoter Score is climbing whilst service times plummet. Notably, the cost to support daily workers has dropped by over 70% in the past four years.
Solving U.S. technical challenges
As Managing Director of DailyPay Belfast, Paul’s technical challenges extend beyond fraud detection to logistical.
Unlike Northern Ireland, there's no federal guidance in the US - meaning DailyPay must accommodate individual states (plus Canadian provinces), each effectively representing a different regulatory market. The complexity is mind-bending. For example, one territory passed legislation making on-demand pay free of charge; then completely changed just a year later to allow on-demand pay fees of up to $30 monthly.
"Uniquely, every US state's a little different," says Paul. "Even over two years, we've had one state go from one extreme to another then to something in the middle."
Paul’s solution has been characteristically systematic, establishing and growing a technical programme management team to bridge big-picture strategy and granular execution.
Unlike traditional project managers who rely on engineers for technical depth, technical programme managers possess both deep technical experience and the business acumen to translate between technical and strategic concerns, coordinating multiple teams whilst managing dependencies and risks.
“A big part of it is to have people that aren't necessarily into the weeds on the tech side - they're looking at the big picture" Paul says. Technical programme managers ask the crucial question: what are the checkboxes needed to ensure coordination and collaboration actually happen?
The future of AI - in Belfast?
Angela and Paul are exploring applications for AI that haven't even been imagined yet. Angela’s background in cognitive psychology provides unique insight into human behaviour patterns, whilst Paul’s systematic approach to scaling engineering operations ensures innovations can be deployed globally.
For Angela, Large Language Models (LLMs) mark only the beginning of a transformation that will reshape work and forge new career paths. One immediate role emerging is that of the prompt engineer, a specialist who designs, tests, and refines the inputs used to guide AI models. She encourages aspiring technologists to gain an intuitive understanding of this nascent field through hands-on experimentation. However, Angela remains clear-eyed about the technology's limits: "LLMs are not good for everything. There are times when machine learning or Bayesian methodologies are always going to be superior."
The true excitement, she contends, lies in agentic AI, systems that move beyond simple responses to queries to generate their own actions and decisions. “You’re going to eventually have layers of LLMs managing other LLMs, so we’redefinitely breaking through another technological revolution.
For those worried about AI replacing human jobs, Angela offers a perspective rooted in technological history and suggests other opportunities will be forged. "That's a fear that always happens when you're in the beginnings of a technological revolution - jobs are going to change, and being ready for that change is where the opportunity is."
This philosophy of continuous adaptation is central to DailyPay’s Belfast culture, where she encourages her team to dedicate time—whether an hour daily or a full day weekly—to learning. As she states, "As technologists, it’s our responsibility to maintain our knowledge, our experience, our learning, our education throughout our careers. Technology is constantly changing.”
For DailyPay, the future of work is being written one paycheck at a time. And if DailyPay's Belfast operation is any indication, that future looks remarkably bright.
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