AI is transforming the financial services industry, promising better risk management, fraud detection, and personalized customer experiences. Yet, despite massive investments, many financial institutions are failing to scale AI and see real ROI.

According to Gartner, only 57% of organizations meet their AI ROI expectations.

The problem? It’s not the AI models—it’s the data.

At TopQuadrant, we’ve worked with industry leaders like JPMorgan Chase, T. Rowe Price, and others, and we’ve seen a common trend: firms don’t struggle with AI technology—they struggle with the foundation needed to make AI work at scale.

Why Financial Firms Can’t Scale AI

Even firms with the best AI models in place hit a wall when they try to scale. Here’s why:

1. Siloed & Disconnected Data

Financial firms have vast amounts of data across different systems—customer transactions, credit risk profiles, compliance reports, and more. But when AI can’t access a complete, unified data set, insights are fragmented and unreliable.

2. Compliance & Regulatory Bottlenecks

From Basel III to GDPR to the SEC’s AI risk guidelines, financial institutions operate under strict regulations. If AI models lack transparency and traceability, compliance teams slow down or block deployment—stopping AI from scaling.

3. Lack of Context in AI Models

AI is great at crunching numbers, but financial data isn’t just about numbers—it’s about relationships. Without context, AI models can misinterpret transaction patterns, miss fraud indicators, or fail to recognize meaningful trends.

How Leading Financial Firms Are Solving This

We’ve helped major financial institutions overcome these barriers by fixing the data problem first—before AI ever comes into play.

Here’s what works:

• Unifying fragmented data so AI models see the full picture
• Automating governance & compliance to eliminate regulatory roadblocks
• Enriching AI with contextual data so models make better, explainable decisions

One firm we worked with unlocked AI-driven insights in weeks, not months, simply by fixing how their data was structured and governed.

The Path to Scalable AI in Financial Services

If your firm is investing in AI but not seeing real scale and ROI, the first step isn’t a new AI model—it’s a data foundation that enables AI to work.

The financial institutions that get this right are seeing:

• Higher AI accuracy for risk modeling and fraud detection
• Faster compliance approvals through automated governance
• More personalized customer insights powered by contextual AI

Want to explore how your firm can overcome AI’s biggest scaling challenges? Let’s talk.