How analysts can embrace innovation without compromising trust, compliance, or performance.
Why genAI Adoption in Banking Must Balance Speed with Safeguards
GenAI is reshaping how analysts in investment banking work, making research faster, pitchbooks sharper, and due diligence more scalable. According to the LexisNexis report: GenAI in Financial Services: The Rise of the Creative Professional, 81% of financial professionals are already using genAI-based tools in their daily work.
But the faster genAI adoption accelerates, the more critical risk management becomes. Investment banking demands precision, accountability, and trust which must be maintained as new technologies enter the workflow.
Unlike other industries, investment banking operates under intense regulatory, reputational, and operational requirements. Analysts, often the first to use genAI in daily tasks, are now at the center of transforming it from a promising tool into a trusted, compliant part of banking workflows. This brings about the challenge of using genAI confidently while ensuring compliance, traceability, and accuracy at every step.
The Risks Analysts Need to Understand — and How to Mitigate Them
The report highlights three top concerns among financial professionals when using genAI tools:
- 52% cite privacy and security risks
- 43% worry about over-dependence on technology
- 34% flag concerns around inaccuracy and misinformation
These concerns are valid, especially when using genAI to prepare client-facing documents, summarize financial reports, or generate competitive intelligence.
How analysts can mitigate risk:
- Use genAI tools built for financial workflows (e.g., Nexis+ AI™) that include secure data access, transparent attribution, and enterprise-grade auditability
- Always verify outputs with trusted content sources like Nexis®, Nexis Diligence+™, and your firm’s proprietary data
- Flag gaps or inconsistencies early and escalate unclear results — don’t rely on genAI to fill in what you wouldn’t present manually
- Track your prompts to ensure you can recreate and defend output if challenged by reviewers, compliance teams, or clients
Why Explainability Matters
In investment banking, results matter but so does the journey, the thought and research behind the data. You need to show how you reach conclusions and answers. Whether presenting to clients or internal teams, being able to explain the process behind an insight is just as critical as the insight itself. Therefore, explainability is a non-negotiable in this industry.
The report shows that 70% of financial services professionals identified transparency and explainability as essential to building trust in genAI.
What explainability should look like in practice:
- Source traceability: Analysts must be able to point directly to the original documents, filings, or datasets that underpin genAI outputs.
- Prompt transparency: Teams should document key prompts used to generate client-facing material, ensuring repeatability and auditability.
- Confidence under questioning: Whether it’s a client asking, “Where did this data come from?” or a senior banker challenging assumptions, analysts must feel equipped to walk back through the genAI process step-by-step.
Tools like Nexis+ AI are designed to support this need. Explainability is about accelerating trust — with managers, clients, and compliance teams.
Analysts Are the Leaders of Responsible GenAI Use
The report shows that all respondents in financial services expressed concern over ethical issues related to genAI — including accuracy, transparency, and accountability. Yet only 14% of firms offer advanced AI training.
Analysts who take the lead on responsible genAI usage can quickly position themselves as trusted users.
What responsible use looks like in practice:
- Review AI output with the same rigor you’d apply to a junior analyst’s work
- Know when to use genAI (e.g., summarization, content drafting) and when not to (e.g., final modeling assumptions)
- Raise risks when you see them — creating a culture of shared responsibility
- Champion ethical prompting and here’s how:
- Frame prompts neutrally to avoid biasing outputs (e.g., request risk summaries rather than conclusions)
- Prioritize prompts for verifiable facts, not speculation
- Direct genAI to trusted, auditable sources whenever possible (e.g., Nexis®, regulatory filings)
- Ask for balanced perspectives, especially in complex or strategic analyses
- Flag genAI-generated drafts internally with clear notes that human validation is pending
By mastering how to apply genAI responsibly, analysts can increase speed and insight while building trust within their teams and with clients.
Analysts Who Balance Innovation and Risk Will Lead the Next Generation
Firms are looking for professionals who don’t just know how to use genAI — but who know how to use it well. Analysts who understand the risks, validate results, and embed best practices into their workflow will become the model for what high-performance looks like in a tech-enabled future.
High-Performing Analysts Aren’t Just Using genAI — They’re Mastering It
Learn how to validate, verify, and elevate your output with insights from firms at the forefront of responsible AI adoption.