5 Best AI Tools For Investment Banking and Research

If you’re exploring AI tools for investment banking and research, you may recognize some of these challenges.

• If you’re on the buy side, your investment research and analysis teams might be juggling multiple tools and manual workflows that slow insight delivery and cause missed opportunities.
• If you’re on the sell side, your investment banking teams may be losing revenue to hours spent reviewing documents and qualifying new deals without automated buyer–seller matching or onboarding support.

Whichever side you’re on, it might also be that:

• You’re using traditional tools that offer only basic dashboards and filtering that prevent you from analyzing, reaching decisions and creating reports faster.
• You’re unsure whether you need off-the-shelf tools, custom AI, or a mix of both, and which option will support your goals most effectively.

So you know what your options are and what to look for in a solution, we’ll cover the top five AI tools for investment banking for 2025.

In this article:

• Five best investment banking tools: A comparison table
• Neurons Lab
• Bloomberg
• Claude for Finance
• Hebbia
• Delta Capita
• What to look for in an AI tool for Investment Banking
• FAQ

Want custom AI tools for investment banking that help you meet all your KPIs? Book a call with us today.

Five Best AI Tools for Investment Banking: A Comparison Table

1. Neurons Lab: Tailored AI Tools for Investment Banking

As an AI enablement company with AWS-certified expertise in Generative AI and Financial Services, we build AI solutions that provide key artificial intelligence capabilities, from research synthesis and insights generation to real-time data integration, all from a single interface.

Specifically, for firms on the buy side that need to analyse and compare data from multiple sources, we provide solutions that streamline the entire research process while mitigating hallucinations and ensuring accuracy. This includes:

• AI-driven search
• AI-enabled multi-step analysis
• Conversational queries
• Automatic chart generation
• Actionable insight generation
• Deterministic financial reasoning tools

For sell-side teams in investment banks that need to process high volumes of deal materials and make faster, data-supported decisions, we provide:

• Automated document analysis
• Automated memo and summary generation
• AI-driven compliance support (KYC/KYB/AML)
• Custom AI-powered tools to match buyers with companies

Leading financial services firms like Visa, AXA, and SMFG already trust our solutions to support secure, compliant AI at scale. By partnering with us to develop AI-powered investment banking tools, you can expect to:

Move beyond the limitations of off-the-shelf tools with an AI solution tailored to your business needs

Your current tools and existing systems may rely on basic databases with filters that keep your teams stuck in manual analysis. They may also lack conversational interfaces and can’t perform multi-step reasoning or automate workflows.

With Neurons Lab, you can build custom tools that automate multi-step analysis and complex workflows from a single interface on either the sell side or buy side. This creates a one unified point of access for your analysts or bankers.

The system pulls and integrates data from your internal platforms, real time market feeds, and compliance approved documents. Specialized AI agents then analyze these combined inputs and produce clear insights that would otherwise take hours of manual work across multiple tools. Your teams can then query a single system, receiving instant, source-backed answers.

And with enterprise-grade security, governance, and cloud best practices built in from the start, your solution will align with your goals, fit your workflows, and meet compliance requirements.

For example, an investment firm was struggling with a reporting process that was slow and prone to errors. Teams spent about 20 days each month gathering and checking data from different sources. This long cycle delayed important insights and directly affected investor decision-making.

The firm’s older systems also struggled to keep up with evolving data and regulatory changes, which limited their strategic responsiveness.

We built an AI-powered reporting solution that:

• Integrated seamlessly with the firm’s legacy systems
• Automated data extraction and consolidation from more than 10 sources.
• Used AI to turn raw data into comprehensive, insightful reports.

As a result, the firm achieved these outcomes:

• Monthly reporting was 75% faster, dropping from 20 days to 5.
• Errors fell by 90%, helping teams optimize report reliability.
• Report updates based on market or regulatory changes were 60% faster.
• Investor confidence increased by 40%.

Partner with an AI-exclusive and FSI-specialized consultancy to integrate compliant AI tools with audit-ready outputs

With Neurons Lab, you’ll have the hands-on support to select use cases that can scale and deliver measurable results. You’ll also have the necessary guidance to determine whether it makes sense to invest in an off-the-shelf or custom AI tool.

In either situation, our financial services expertise allows us to tailor and integrate compliant AI solutions that address use cases your current systems cannot. This means you can implement solutions that support everything from KYC/KYB/AML workflows and back-office regulatory checks to document-heavy due diligence, audit-ready summaries, investment memos, and compliance reports.

Our AI focus also ensures you gain audit ready outputs through AI operations (AIOps) that track data sources, decision steps, and AI model behaviour for full traceability, making reviews and regulatory checks faster.

Deploy your tailored AI tool for deal sourcing and buyer-seller matching in as little as two to four months

With tested code, reusable components, and proven frameworks, our pre-built AI accelerators only need to be tailored to your workflows. This speeds up production timelines and allows you to deploy in as little as two to four months.

For example, our NeuraDoc accelerator helps you move beyond slow, error-prone document processing to handling everything from routine document extraction to complex multi-step workflows.

Through combining agentic AI with advanced OCR and generative AI, you could also see:

• 40% reduction in your operating costs
• 80% faster processing times
• 99% document accuracy

Who We’re Best For

We work best for mid-to-large-sized financial institutions that view AI as a strategic advantage but don’t have the in-house expertise to build custom AI solutions, have previously tried to implement AI and failed, or got stuck at the proof of concept (PoC) stage.

Our boutique size makes us agile in helping you identify the right AI solutions and deploy them effectively, while our deep sector expertise and 500+ AI engineer network ensures you make decisions and develop solutions that maximize ROI.

However, we know that we might not be the right fit for every company, so here are four more AI tools for investment analysts and bankers to consider:

2. Bloomberg

Bloomberg is a global financial news, data, and analytics platform that delivers real-time market data, financial data analysis, and trading tools via its Bloomberg Terminal⁶.

While not a complete solution, investment bankers use it for financial analysis, and it powers finance-focused AI tools like Claude for Finance and Perplexity Finance. It can also serve as a data source within custom AI solutions that unify multiple workflows into a single system.

Key AI capabilities: Insights generation, AI document search and analysis, AI-powered news summaries, command line natural language processing (NLP), instant Bloomberg/BloombergGPT

How it helps buy side firms: Investment analysts can screen companies, pull financial statements, compare metrics, track earnings, monitor markets, and export data into Excel models for deeper analysis.

How it helps sell side firms: Investment bankers can access company profiles, track news and filings, review transactions, and build high-level valuation views to support pitches and deal preparation.

Best for: Real-time financial data and market analytics, and in-depth industry reports

3. Claude for Finance

Claude Finance is a financial AI platform that supports both immediate workflows and custom development⁷. Teams can use its Financial Analysis Solution, API, or Claude Code to automate research, modeling, and operational tasks. It also relies on tools like Bloomberg for market analysis.

Key AI capabilities: AI search, Multi-step financial analysis and modeling, research synthesis and insights generation, real-time data integration

How it helps buy side firms: Investment analysts can accelerate diligence and market research, run competitive benchmarking and portfolio deep dives, build and validate financial models with full audit trails, and generate institutional-quality investment memos and pitch decks.

They can also monitor portfolio performance, compare metrics across investments, and surface new opportunities faster than traditional research methods.

How it helps sell side firms: Investment bankers can automate document-heavy workflows such as reviewing data rooms, filings, and transaction materials. They can generate comps, profiles, and pitch content through AI-driven analysis, and produce investment memos and deal summaries using structured, citation-linked outputs sourced from integrated financial data providers.

Best for: Investment research, multi-step financial analysis, and generating structured insights from large volumes of filings, transcripts, and market data

4. Hebbia

 

Hebbia is a multi-agent AI platform for finance that handles complex multistep workflows, reasons over large data sources, and provides insights.

 

Key AI capabilities: Insight generation, AI search, AI document analysis, AI summarization, and AI report generation

 

How it helps buy side firms: Investment analysts can scan company lists and reports, benchmark new deals against past IC memos, track comps from filings and earnings calls, synthesize research from consultants and brokers, surface diligence answers across data room documents, and generate first drafts of investment memos and quarterly reports.

 

How it helps sell side firms: Investment bankers can pull precedent transaction data, compile company profiles, review activist trends, create CIM outlines, run fee analyses, and ramp quickly on new opportunities using public and private sources.

 

Best for: Automating multi-step workflows, deep analysis, and extracting insights from large unstructured datasets

5. Delta Capita

 

Delta Capita is a global capital markets consultancy and managed-services provider with financial expertise and technology capabilities⁸.

Key AI capabilities: Machine learning (ML) data remediation and quality checks, AI client onboarding and lifecycle management, intelligent document processing for KYC, KYB, and compliance, ML-based workflow automation

How it helps buy side firms: Investment analysts can benefit from regulatory reporting support, portfolio and data-automation services, and outsourced operations.

How it helps sell side firms: Investment bankers can get post-trade processing technology and market-infrastructure consulting to improve efficiency and reduce operational risk.

Best for: Streamlining post-trade operations, regulatory workflows, and data-heavy processes using machine learning and managed services for both buy side and sell side firms, often in workflows where pricing accuracy is critical.

What to look for in an AI tool for Investment Banking

For an investment research AI tool that simplifies complex multi-step workflows, here’s a short checklist of what to look for:

• Does it integrate with your existing workflows and systems? The right AI tool connects seamlessly to your current setup. It’s also backed by a provider with the consulting and integration expertise to tailor everything to your requirements.
• Does it combine and connect to the right data for accurate financial analysis? For accurate outcomes, an AI tool must connect to a range of public and private data sources.
• Can it handle large volumes of documents and support compliance tasks such as KYB and AML checks? Look for a robust AI tool that can process high volumes at speed, extract key data, compare details, generate structured summaries, and surface risk-relevant information quickly.
• Does it support complex multi-step analysis? For example, can you compare revenue, EBITDA, and performance across multiple companies instantly? The right tool lets you combine filters, comparisons, and charting in one flow.
• Does it use deterministic tools to ensure accurate, reliable outcomes? Financial analysis requires precise calculations. As such, your AI systems should connect to financial calculators and models instead of relying on LLM prediction.
• Does it have a conversational query interface to speed up research? Opt for a tool with a single conversational interface so users don’t waste time switching between different functions.
• Can you produce charts, visuals, and outputs such as memos instantly? The right tool saves you hours from having to produce these materials manually.
• Does it automate buyer-seller matching? Look for a tool that can analyze company profiles and buyer preferences and help you identify the right investors or faster.

Choose Custom AI tools that Meet your Investment Banking and Research Needs

Whether you’re on the buy side or sell side, custom AI tools can be designed to do exactly what you need. This means your teams won’t have to force-fit or stitch together multiple ChatGPT-style off-the-shelf tools to handle complex multi-step flows. Instead, they’ll increase productivity and efficiency while focusing on higher-value tasks.

To achieve this, you’ll want to partner with a provider with deep financial services expertise, advanced AI capability, and a proven track record of deploying similar solutions successfully.

That way, you can be confident that every requirement around accuracy, compliance, data integration, multi-step analysis, and speed is handled properly. It also ensures that you have a system that can scale securely as your needs evolve.

If you’d like to explore how AI can apply to your investment workflows, our team can share insights from working with leading financial institutions. Book a call with us today.

FAQs

How can we ensure compliance when using AI in investment banking?

You can ensure compliance by working with a partner that has extensive FSI industry expertise. This ensures they understand the industry’s regulatory landscape and its complex workflows.

It also ensures compliance can be built into your solutions from the start. For example, with Neurons Lab, you’ll have custom AI solutions designed to meet the standards set by regulators, such as GDPR, OCC, MAS, and ISO/IEC 27001, while ensuring your data never leaves secure environments.

Do you need a large upfront budget to get started with AI in investment banking?

Not necessarily. It depends on the solution and your implementation partner. As an AWS partner, Neurons Lab can extend cloud credits and grants to reduce upfront costs. Our phased rollout approach also helps you validate ROI early and spread investment over time.

How do AI tools ensure accuracy for financial calculations and analysis?

AI tools ensure accuracy by connecting to deterministic tools such as calculators, financial models, or structured formulas rather than relying solely on probabilistic LLM reasoning. This ensures accurate and reliable outputs.

Can AI tools replace manual spreadsheet-based financial modeling?

Yes. The right AI tools can automate spreadsheet-heavy work, generate structured insights instantly, and help analysts move from manual inputs to faster decision-making.

Do we need in-house AI engineers to adopt investment banking AI tools?

Not at first. You can start by working with an AI enablement partner like Neurons Lab, which provides dedicated AI engineering teams. If you later want to build internal capability, we can help train your existing technical staff or guide you on the roles you’ll need to hire.

Sources:

1. https://www.bloomberg.com/professional/solutions/ai/#overview
2. https://www.anthropic.com/news/advancing-claude-for-financial-services
3. https://www.hebbia.com/
4. https://www.deltacapita.com/services/kyc-client-onboarding#Technology
5. https://www.deltacapita.com/services/post-trade
6. https://www.bloomberg.com/professional
7. https://www.anthropic.com/news/claude-for-financial-services
8. https://www.deltacapita.com/