At Nomis, we've spent over 20 years helping banks price trillions of dollars in loans and deposits across three continents. That experience has taught us something crucial: the best banking decisions come from combining sophisticated analytics with human expertise and judgment.
Now we're bringing that same philosophy to AI. Our AI business analyst doesn't try to replace your team — it accelerates their ability to find what matters in your data.
Our approach starts with a simple observation: experienced analysts already know the patterns that matter in banking. They understand which metrics signal opportunity or risk. They recognize when portfolio behavior deviates from normal. So we built our AI to think like they do.
Instead of waiting for someone to ask the right question, our AI business analyst continuously analyzes your portfolios, product performance and market dynamics. It surfaces the insights that matter, like the unexpected changes in application quality, the geographic variations in performance, the early warning signs of competitive pressure.
This isn’t about basic reporting. Tools that answer questions like “What are my competitors’ rates?” or “How did Portfolio X perform versus Portfolio Y?” have existed at Nomis for decades. It is about finding the insights you didn't know to look for. After all, typing questions into a chatbot interface might feel modern, but it still puts the burden of discovery on already-busy product managers who need answers, not another tool to interrogate.
We had two choices when building our AI analyst. We could ship a generic tool and let each bank train it through months of trial and error. Or we could build in two decades of banking analytics expertise from day one.
We chose the second path. It's significantly harder because it requires encoding deep knowledge about portfolio management, pricing strategy and risk patterns directly into the AI. But it means our clients get immediate value. No training period. No hallucinations about banking fundamentals. Just insights, grounded in real banking experience.
Banks run on Excel and PowerPoint. Product managers juggle multiple systems. Executives need insights presented in familiar formats they can trust and share. We built our AI to fit into these realities, not fight them. It delivers insights in familiar formats, directly addresses the business problems your teams face and integrates with the workflows that drive actual decisions.
The banking industry involves complex decisions with real consequences. Pricing strategies affect profitability and market share. Risk assessments impact the entire portfolio. These decisions require not just data, but understanding of competitive dynamics, regulatory constraints, internal politics and strategic objectives.
That's why our AI is designed to accelerate insight, not automate decisions. It handles the heavy lifting of data analysis —testing hypotheses, identifying patterns, surfacing anomalies — so your experts can focus on what they do best: making informed decisions that consider the full context. The goal isn't to bring every piece of information into an AI and let it decide. It's to get the right insights to the right people as quickly as possible.
The pace of banking continues to accelerate. Depositors move money faster. Competitors adjust pricing in real-time. Market conditions shift daily. In this environment, the difference between spotting a trend today versus next week can be measured in millions of dollars.
Even the most sophisticated traditional analytics approaches struggle to keep pace. Manual analysis takes time. Dashboard queries only answer the questions you think to ask. And while chatbot interfaces might seem like the answer, they're just a faster way to run the same reactive playbook. By the time you've figured out what to ask and typed your query, the opportunity may have passed.
Our AI business analyst changes that dynamic. It's constantly watching, analyzing and surfacing what matters. Not to replace your team's expertise, but to ensure they can apply it when it matters most.
After 20 years in banking analytics, we understand that technology is only valuable when it enhances human capability. Our AI business analyst embodies this philosophy — sophisticated technology that amplifies expertise rather than attempting to replace it.
The future of banking analytics isn't about choosing between humans and AI. It's about combining the pattern recognition and processing power of AI with the judgment, experience and contextual understanding that only humans can provide.
Ready to accelerate your analytics? Contact us at sales@nomissolutions.com to see how our AI business analyst can transform your team's ability to find and act on insights.
This is Part 2 of our series on AI at Nomis. Don't miss Part 3 coming soon: How AI Enhances Recommendation Engines by Combining Models and Judgment
Revisit Part 1 of the series here: How We're Actually Using AI at Nomis: A Pragmatic Approach to an Overhyped Technology
Written by: Wes West, Chief Analytics Officer at Nomis Solutions