Investment banking is an industry built on numbers, verification, and getting the details right, where a single miscalculation can torpedo a billion-dollar deal. Yet somehow, most firms are still doing research the same way they did thirty years ago, with armies of analysts manually combing through documents, cross-referencing spreadsheets, and pulling all-nighters to compile reports that clients needed yesterday. Meanwhile, generative AI (GenAI) tools specifically designed for financial analysis sit unused because everyone assumes ChatGPT is the only game in town.
While Wall Street debates whether artificial intelligence will steal jobs or create them, a quiet realization is happening in the research departments of savvy investment banks. The problem isn’t that bankers don’t know AI exists. Most have tried ChatGPT for quick summaries or basic research tasks. But when it comes to the heavy lifting, ie, comprehensive due diligence or competitive analysis, they fall back on the same manual processes because generic AI tools just aren’t built for this work.
Yes, they’ve figured out that AI can help here and there. But even with generic AI models like ChatGPT and Copilot, smarter bankers will eventually realize that these tools weren’t built for the high-stakes world of investment banking. They lack the specialized datasets, industry know-how, and fact-checking processes that serious dealmaking requires. Our deep research tool, Scholar, changes everything.
Built for Bankers, Not Bloggers
Scholar represents a completely different approach to AI-powered research. Built specifically for advisors, corporates, and research teams who need to move fast and dig deep, it uses agentic AI workflows to create detailed research reports of up to 30 pages or more in just minutes, pulling from both our private database of over 30 million companies and trusted outside sources.
Unlike consumer AI tools that summarize random internet stuff, Scholar breaks down complex financial data with the precision and sourcing standards that big institutional clients demand. The tool doesn’t just summarize, but actually thinks through the data. And with proper citations and smart workflows that double-check everything for accuracy, it produces quality material you can use.
So while ChatGPT might give you a basic overview of market trends, Scholar delivers investment-grade analysis with the depth and specifics that billion-dollar decisions truly need.
The Five Game-Changing Applications
- Lightning-Fast Due Diligence
Traditional due diligence means weeks of document review and analysis. Deep research using Scholar flips this due diligence timeline completely. The platform can analyze target companies against their entire competitive landscape, pulling regulatory filings and market data into one comprehensive report, with full source notes and professional-level analysis.
- Market Intelligence at Scale
Investment bankers live and die by their ability to spot trends before everyone else. Scholar’s agentic AI workflows constantly monitor market signals across industries, identifying new opportunities and potential problems. The platform doesn’t just flag news articles, but analyzes what they actually mean, connects the dots, and gives actionable intelligence.
- Comprehensive Competitive Analysis
Understanding the competitive landscape is crucial for any deal, but manually researching dozens of potential comparables is time-intensive and error-prone. Scholar automates this process by analyzing business models, financial metrics, and strategic positioning across entire industries.
- Scenario Modeling and Stress Testing
Modern dealmaking requires understanding not just current performance but future possibilities. Scholar excels at scenario analysis, using historical data and market trends to model various outcomes. The platform helps investment bankers stress-test assumptions against actual data.
- Client-Ready Deliverables
Perhaps most importantly, Scholar creates polished, client-ready materials. The final report includes access to our predictive analytics as well as proprietary algorithms for deal-sourcing, capital raise and acquisition fit tools. Every output includes proper citations, professional formatting, and the analytical depth that clients expect.
Why Generic AI Falls Short
The fundamental problem with consumer AI tools in investment banking isn’t their intelligence but lack of specialization. ChatGPT knows a little about everything except for the deep financial datasets, regulatory context, and industry-specific knowledge that serious dealmaking requires. It can’t access proprietary company information, doesn’t understand the nuances of different deal structures, and has no mechanism for validating the accuracy of its outputs against professional standards.
Scholar solves these problems by combining GenAI capabilities with purpose-built financial intelligence. Scholar is the ChatGPT for dealmakers, built for the way deal professionals actually work, but much more sophisticated. It understands the difference between enterprise value and equity value, knows how to interpret EBITDA adjustments, and can analyze the strategic rationale behind complex transactions.
Another Scholar advantage is that instead of jumping between multiple databases, verification systems, and analysis tools, bankers can conduct comprehensive research within a single platform.
Speed Without Compromise
The traditional trade-off in investment banking research has been speed versus quality. Faster analysis usually meant shortcuts, missing details, or relying on outdated information. Scholar breaks this by delivering institutional-grade research at unprecedented speed without sacrificing accuracy or depth.
The platform can transform grueling research processes that typically consume weeks into tasks completed in minutes. This isn’t about replacing human judgment but amplifying it, giving senior bankers more time to focus on strategic thinking, client relationships, and deal execution.
What makes Scholar particularly powerful is its integration with our broader ecosystem of deal-making tools. While standalone AI tools require constant data imports and manual verification, Scholar operates within a comprehensive platform that includes real-time company data, market intelligence, and predictive analytics.
One Broad Ecosystem
Scholar represents just one component of our comprehensive approach to transforming investment banking workflows. Finder revolutionizes deal sourcing by using AI to identify investment and acquisition opportunities across our database of over 30 million companies. Complementarily, Acquirer uses proprietary AI to identify relevant target companies through concepts and keywords, designed specifically for bankers and investors to target the most relevant bolt-on acquisitions. Meanwhile, Raiser helps identify and connect with the most relevant investors for any deal, allowing teams to prioritize which investors to approach while tailoring their pitches. Together, these tools create an integrated workflow that spans the entire deal lifecycle, from initial sourcing through execution and closing.
This ecosystem approach represents the future of investment banking technology with purpose-built tools that understand the industry’s unique requirements and AI capabilities that enhance rather than replace human expertise. For firms ready to embrace this transformation, the competitive advantages are clear and significant.
Ready to see Scholar in action? Contact us now.
