Small, focused engineering groups are outpacing the consulting giants and giving financial institutions a faster path to production in an era of AI.
For the past decade, banks and insurers have been told to think like fintechs. Move faster. Innovate quicker. Break fewer things along the way. Yet many of the largest financial institutions still struggle to match the pace of smaller challengers, even as they invest heavily in cloud, data, and AI.
The problem is no longer awareness. It is execution. And a growing number of financial institutions are looking outside the traditional consulting giants to find it.
Boutique firms, once considered niche players in a field dominated by the Big Four, are becoming the preferred partners for institutions that want real results rather than sprawling transformation roadmaps. A technologist and advocate for this shift is Rahul Goel, CEO of BrainRidge Consulting, a premium fintech consulting partner that has carved out a reputation for helping established players advance their AI journey by harnessing the latest technologies.
Goel spends much of his time working with executives inside major financial institutions. From that vantage point, he has developed a theory that runs counter to the prevailing narrative: financial institutions do not need to move faster. They need to move smarter.
“Speed is not a technology problem. It is a clarity problem,” Goel says. “Fintechs move fast because they know exactly what they are solving, who owns the outcome, and how success is measured. Many finance giants lose that sharpness and the ability to move quickly as decisions climb through layers of governance.”
In Goel’s view, the institutions that make the fastest progress are those that treat compliance as a design input rather than an audit hurdle. By bringing business, technology, and risk teams together early, the organization moves as one unit. Value is proven in smaller increments. Confidence grows. Governance remains intact. And innovation stops feeling like a gamble.
“The future belongs to institutions that can balance pace with precision,” Goel says. “The goal is to move with purpose and back those efforts with data and discipline.”
This approach has struck a chord with senior leaders who are exhausted by multi-year transformations that fail to deliver measurable outcomes. Goel argues that the pivot to boutique partners is less about budget and more about the desire for accountability.
“Boutique firms operate on ownership, not hierarchy,” he says. “Our clients deal directly with the people solving the problem. That closeness creates momentum. Decisions happen in hours instead of weeks, and that can be the difference between a pilot that stalls and a solution that scales.”
Companies continue to bet big on AI, yet many of their pilots are getting stuck at the starting line, sometimes for more than a year. Goel shares how the firm once helped a global bank turn an AI project that had been idle for 18 months into a live production system within ten weeks. Use cases like this elevate BrainRidge as a partner that can move projects beyond decks and into action on a short runway. The fast turnaround is the result of a small, focused team with the authority to act.
“The secret ingredients to success included proximity, focus, and the right mix of technology and accountability,” he says.
Another element of BrainRidge’s advantage comes from its talent pipeline. Many of the firm’s engineers and data scientists are alumni of MIT, Waterloo, IIT, and other top institutions, and these high performers are recognized for their advanced AI research or Mathematical Olympiad honors.
“They could work anywhere but choose to work with us because they want to build solutions that matter,” Goel says.
BrainRidge also collaborates with universities on open-source AI initiatives, giving students the chance to work on research that ultimately becomes part of real-world banking systems. This merging of academic rigor with enterprise delivery is part of what sets boutique players apart from their large, siloed competitors.
“Large firms often win on scale,” Goel says. “Boutique firms win on precision, speed, and the freedom to care deeply about every engagement.”
The conversation naturally turns to AI, an area where many traditional financial giants feel the greatest pressure to catch up. Nearly every major institution is running pilots, training teams on new tools or cleaning data in preparation for the next wave of intelligent automation, yet only a fraction are seeing meaningful returns.
Goel believes this is because most AI programs are structured around experimentation rather than performance. The path to value, he argues, begins with focus.
“Choose one business problem, one success metric and one model. Measure everything against that,” he says. “If a project can’t show results in 90 days, it’s simply a research project.”
His clients have seen measurable gains with this approach, including significant reductions in operational costs, faster resolution times, and higher customer satisfaction scores. The results have less to do with cutting-edge algorithms and more to do with disciplined scope, clean data, and leadership that treats AI as a business tool rather than a novelty.
“AI demos often fail because the goalposts are unclear,” Goel says. “When leaders connect AI to clear financial outcomes, success stops being theoretical and becomes measurable, repeatable, and real.”
For Goel, the lesson is simple. The next decade of financial innovation will not be defined by which institutions adopt the most technology. It will be defined by which ones make every investment count.
“True agility is not about speed,” he says. “It is about clarity, accountability and the courage to measure what matters.”
As fintechs continue to set the pace and competitive pressure mounts, more banks and insurers are discovering what startups have known for years: small, sharp, deeply invested teams can outperform the largest consulting armies. And as the sector approaches its next wave of AI-driven change, that difference may prove decisive.
