In 2026, the challenge for investment banks isn’t winning deals—it’s closing them. After a few tough years, announced US merger and acquisition (M&A) deal value in 2025 roared back to its 2021 high watermark of $2.6 trillion—up 58% year-over-year, according to the Securities Industry and Financial Markets Association. But in the intervening five years, deals became bigger and more urgent, the role of private capital increased dramatically, and AI began reshaping investment banks’ workflows before governance controls could catch up. These major trends underpin the eight big challenges investment banks are dealing with as 2026 winds down.
Key Takeaways
- Investment bankers’ core M&A advisory business is roaring, lifted by the rising tide of global AI investment.
- But market pressures, regulatory uncertainty, the rise of private credit, and AI’s effect on business workflows are challenging banks to complete deals.
- Growing private credit—now roughly $1.4 trillion, or about 10% of US nonfinancial corporate debt—has changed who supplies capital and has led to potentially dangerous interdependencies in the corporate finance ecosystem.
- Technology modernization and cyber defense are now inseparable. Every new platform, vendor, and digital connection expands a bank’s capabilities and its exposure.
- As automation takes on more and more routine work, firms must rethink how the next generation will learn the fundamentals.
Big Changes Are Transforming Investment Banking
AI is fueling two of the three structural forces that are reshaping how investment banks operate in 2026. First, it has galvanized dealmaking to a new level of strategic urgency—despite historically high valuations—as companies race to buy capabilities they can’t build fast enough. Second, AI technology has crossed from back-office support into the heart of deal work, and firms are adopting it faster than they can lay down the governance and controls needed to manage the new risks they present, according to an analysis from the Financial Industry Regulatory Authority (FINRA).
The third force is private capital, which has moved from the margins of corporate finance to the center. Banks, funds, and insurers now form a single financing ecosystem with interlinkages that create potentially dangerous dependencies, according to an October 2025 report from the International Monetary Fund (IMF). In the same report, IMF warned that risk asset prices are again above fundamentals, so macroeconomic conditions can shift quickly.
These forces are rewriting both how deals get done day to day and where firms will place their long-term bets.
8 Major Challenges Investment Banks Are Facing in 2026
Investment banks must cope with these eight challenges all at once. To heighten the difficulty, the challenges interact with and feed each other, complicating any simple plan to address them.
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Navigating Market Pressures
Market pressure has raised the priority of financial risk management for investment banks because they earn most of their fees only when a deal closes. Advisory and underwriting work made up 91% of one independent investment bank’s revenue in 2025. Such engagements rarely produce recurring revenue, and a stalled or broken deal hits the top line directly. That risk is growing due to the investment banking trend toward fewer, bigger “mega-deals” of $10 billion and up—a situation that could leave a firm’s results relying on only a handful of large, complex closings. With several proposed 2026 transactions topping $100 billion, a single delayed signing can swing even a large bank’s quarter. And other forces can reprice or derail a deal after it’s signed: stretched valuations, higher financing costs, or geopolitical friction, including tariff uncertainty and cross-border reviews.
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Compliance and Regulatory Shifts
Investment banking rules themselves are in motion. US regulators proposed sweeping capital-framework changes in March 2026, for example, and these unfinished rules leave capital planning uncertain. The uncertainty does more than make it harder to improve regulatory compliance. Indeed, the rules could change how much a bank can lend, affecting its ability to back advice with financing—the combination that often wins the deal. Recordkeeping obligations, meanwhile, remain firmly in force—the Securities and Exchange Commission collected more than $600 million in fines during fiscal 2024 from off-channel business communications on unauthorized apps and personal devices.
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Increasing Competition
The keenest competition comes from outside traditional investment banking. Private credit has grown to roughly $1.4 trillion—about 10% of US nonfinancial corporate debt—having doubled in five years, according to the Federal Reserve. Direct lenders offer speed and flexibility that challenge syndicated loans, especially in the middle market. These funds also rely on banks for advice, capital raising, and restructuring, though, which creates new partnership revenue even as they compete. That dual role—competitor one day, client the next—makes private capital one of the trickiest dynamics for banks to navigate.
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Keeping Pace With Technology
Aging infrastructure and disconnected data hindered banks even before AI arrived. Now, FINRA reports that AI is firmly entrenched in financial services, embedded in everyday tasks like summarization and research, with some firms deploying agentic AI to handle multistep work. Yet, foundational technology infrastructure challenges could be causing banks’ AI governance and controls to lag behind adoption. AI needs clean, consistent, coherent data to produce sound results. Flawed AI output can become a valuation, conduct, and recordkeeping problem all at once. The faster AI tools spread, the wider the gap that grows between capability and control.
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Handling Cybersecurity Threats
For investment banks, a breach can wreck a live deal before it ever registers as a financial loss; leaked terms move markets and destroy client confidentiality. Recent reports from the Financial Services Information Sharing and Analysis Center indicate attackers are sharpening their methods with generative AI, using deepfake voices and convincing social engineering to exploit urgency and authorize fund transfers. Both FINRA and the Basel Committee caution firms that relying on a handful of cloud and software providers widens cyber risk exposure and that banks remain accountable, even for incidents caused by third-party systems.
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Cost Management
Investment banking revenue may be episodic, but its costs are continuous. Another way to look at it: A bank’s cost structure behaves like a fixed-cost business but its revenue model is highly variable, deal by deal. Compensation can consume roughly two-thirds of revenue—one investment bank’s compensation ratio reached 64.9% in 2025—and stays high even when deal fees fall. But cutting staff when deals fail risks losing talent and the controls a firm needs to win new work. Layer on steady spending for technology and compliance, and firms face a genuine operating-leverage challenge with no obvious answer.
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Employee Retention and Morale
Investment banking remains a human-capital business, where relationships and judgment determine which firms win and keep clients. Employee retention is only part of the talent challenge. The apprenticeship model that turned analysts into seasoned advisors is not-so-quietly eroding. AI is automating the repetitive junior work traditionally used to train analysts. Remove that work without replacing its learning value, and a firm risks creating a judgment void in its next generation of bankers.
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Changing Client Expectations
Clients no longer need banks for information—they have their own data and in-house corporate-development teams. They now expect senior bankers on the deal, rather than junior teams, as well as deep sector expertise and a clear view of financing options across public and private markets. In Goldman Sachs’ 2026 survey of 500 clients, 58% named scale and strategic growth as their primary M&A driver—a sign that they want advisors who actively help them act decisively. Proving that kind of differentiated value, fee after fee, is harder than ever.
Leveraging Technology to Troubleshoot Investment Banking Challenges
No single tool solves all investment banking challenges, but the right mix helps make each hurdle more approachable. For most firms, the first step is to connect the data scattered among systems that weren’t built to work together. That fragmentation is the hidden drag behind slow scenario analysis, weak compliance evidence, and unreliable AI.
Accounting and financial management systems can gather general ledger, consolidation, and reporting in one place, along with real-time, audit-ready records, and provide visibility into profitability down to the individual deal. CRM software tracks coverage, pipelines, and client relationships. Business intelligence tools and a growing layer of AI facilitate faster research, sharper forecasts, and analytics to support better, data-driven decisions. Separate cybersecurity and communications-capture systems guard confidential deal data and archive the messages regulators now scrutinize. Every tool tackles a real challenge—the problem is, the tools rarely draw on the same data. The greatest benefit comes from integration that lets all these systems work from the same unified view of trusted data.
Unify Financial Data With NetSuite for Financial Services
In a business where a single deal can define the quarter and compensation can consume two-thirds of revenue, working from one set of numbers keeps deal teams, finance, and compliance aligned no matter how fast the transactions move. NetSuite ERP Software for Financial Services unifies financial and operational data on one cloud platform, so teams can trace any figure back to its origin. That’s the kind of audit trail regulators expect in the aftermath of enforcement actions like the SEC’s $600 million sweep of off-channel communications. Real-time dashboards give leaders a live view of performance occurring in different deals and currencies, while profitability views break down results by deal or segment to show where fee revenue lands.
Automated reconciliations and AI agents that monitor exceptions throughout the period speed closings and give bankers and senior leaders time to focus on deals in progress and client relations, respectively. Role-based permissions restrict access to sensitive deal data to the teams that need it. Those permissions extend to NetSuite’s AI agents, which act only within the approval workflows a firm already has in place. Ask Oracle, NetSuite’s conversational AI, lets bankers query deal and portfolio data in plain language and get clear answers, with explanations of cited data sources. Embedded AI also spots the anomalies and payment irregularities that fraud and cybersecurity teams strive to catch before a breach or a business-email-compromise scheme disrupts a live deal. In investment banking, where results ride on the next deal, NetSuite can provide the speed and clarity that help firms win complex deals—and complete them.
Investment banking has rebounded, but bigger, faster dealmaking is colliding with tougher competition, shifting regulation, rising cyberthreats, and a workforce reshaped by automation. Firms that take on these pressures—and build the data, controls, and talent to best them—will turn today’s challenge into tomorrow’s edge.
Investment Banking Challenges FAQs
What are the challenges faced by investment bankers?
Investment bankers must close increasingly complex deals despite volatile markets and shifting valuations, as they also navigate changing regulation and competition from fast-growing private credit. They need to adopt AI safely, protect confidential deal information, and manage the cost pressures of a business whose revenue is episodic but whose costs are omnipresent. Investment banking firms must develop talent, expertise, and trusted relationships, at the same time as AI takes over routine work and clients demand more value.
What are the key risk-management challenges faced by investment bankers?
Investment bankers must connect risks that span financial (market, credit, liquidity), operational (cyber, model, third-party), and legal (compliance, conduct, reputational) categories, and manage them together rather than in silos. The hardest risks increasingly cross categories. A single flawed AI output, for instance, can become a data, supervision, client, and litigation problem all at once.
