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The traditional model of investment research has relied on institutions for market data, corporate connections, and client networks. Today, AI and increasing access to market data are lowering these barriers. Analysts can independently synthesize filings, model risk, highlight trends, and combine diverse inputs, tasks that once took teams of analysts weeks. Independence also allows analysts to focus purely on research outside of institutional constraints.

In theory, institutional research should reward accuracy. If markets value information, the most accurate analysis should attract the most attention and commercial value. In practice, it rarely works that way. Portfolio managers allocate research dollars based less on forecast precision and more on differentiation, idea generation, and clarity of thesis - qualities that drive engagement and ultimately commercial relationships.

Last week, I attended the TWST Events User Group Day in Midtown Manhattan, where conversations around AI and corporate access were front and center. The technology on display was impressive and clearly will open new revenue opportunities. But as the discussion unfolded, one theme stood out: AI performance depends on organizational readiness. This is where KTB Advisory does its best work—helping organizations build the foundations that allow advanced technology to actually wor

Fintech teams spend years building powerful, differentiated products. And, too often, assume the rest will follow. But even the most innovative technology will fail to reach its full potential without a deliberate commercialization strategy behind it. Without one, best-in-class products can disappear into the ether. My deep experience within the financial services sector has led me to strongly believe that this outcome can be avoided with strategic investments in the people,

Equities have long mastered turning content into revenue, but credit hasn’t applied the same discipline. Yet credit research can be monetized with the right infrastructure: clean client data, consistent interaction capture, smart tagging, and basic analytics. With these in place, firms can uncover trading opportunities, guide strategy, and unlock high-margin business that moves the needle.

Companies pour millions into data and analytics, and most firms are overflowing with talent—but their commercial and data teams often operate in parallel universes. The real value comes from the people who can bridge them: translating business goals into data use cases and data outputs into action. These “translators” aren’t a luxury anymore—they’re the missing link that makes analytics actually drive growth.

The pace of September conferences swallows entire teams, leaving little room beyond survival mode. The visible wins—meetings fought for, introductions demanded—prove success. But what about the hidden opportunities, the ones never even on the agenda? With clarity and focus, those overlooked wins can surface—and turn into outcomes that truly set a firm apart.

Buying star talent creates short-term splash, but lasting impact can come from building in-house. Like Barcelona’s academy turning prospects into champions, equity firms can transform rising analysts into first-call leaders. Spot the talent, sharpen their content, amplify their visibility, and engage strategically — and watch them drive both revenue and recognition.

Culture has always defined success in banking—discipline, hard work, and relationships remain core. But in 2025, firms must pair those values with modern capabilities and ways of working. Underinvesting will quietly erode market share, talent, and revenue, while those that embrace evolution strengthen competitiveness and sustain growth.

At KTB Advisory, I help markets and research businesses transform scattered data and underused resources into clear, actionable strategies. My proven, human-centered consulting process enables smarter analytics, improves client engagement, and drives measurable results—whether you need a full strategy reset or targeted optimization in key areas.

Success in institutional sales and research comes from judgment, relationships, and experience — not dashboards. But used right, data doesn’t replace your instincts; it sharpens them. It helps prioritize calls, flag trends, and surface gaps you might otherwise miss. The value isn’t in the numbers — it’s in what you do with them.

Last week at Unbundling Uncovered, the vision for AI and research was bold, but so were the reminders of what’s holding firms back. Legacy systems, fragmented data, and internal friction make it hard to move forward. Clean, accessible data is just the start. We need integrated systems, smart classification, and segmentation that supports real decisions. The future is AI—but the foundation has to come first. #research #AI #fintech

Before analytics can drive impact, sell-side firms need the right data foundation. That means consistent client records, full engagement tracking, centralized storage, smart research tagging, and clear client segmentation. Without these basics, even the best tools fall short. Strong foundations turn content into commercial results—and make monetization strategies scalable.

FY24 trading revenues hit decade highs—but the real story is what’s driving the outperformance. Top desks are using smarter client intelligence to deepen relationships, spot opportunities faster, and focus resources where they matter most. From sharper analytics to strategic engagement, insight is becoming impact.