arrow right

Investment Banking Technology Trends for 2024

5 technology & investment banking trends to watch in 2024

Get Looped In

Join our newsletter to stay up to date on features and releases
January 23, 2024

Increased market disruption and competition have led more investment banks to embrace digital transformation. With cutting-edge technologies taking hold across artificial intelligence (AI), deep learning, robotics, and more, plus rapidly evolving requirements for landing deals, firms must update their tactics if they're to win.

Similar to banking trends in 2023, the trends in investment banking in 2024 offer a plethora of opportunities for the firms that are paying attention. Read on for the latest trends and technology in banking and how your firm can embrace them to get ahead this year.

5 Digital Investment Banking Trends to Watch in 2024

  1. AI in Banking
  2. Deep Learning in Banking
  3. Robotics in Banking
  4. NLP in Banking
  5. Investment Banking Automation

Trend #1: AI in Banking

Artificial Intelligence (AI), especially generative AI (GenAI), has taken root across many industries, investment banking included. The latest annual Jack Henry survey found that 79% of financial institutions plan to increase their tech spending over the next two years, with over a third planning to increase their investment by 6 - 10%. Nearly a quarter of those respondents (23%) listed AI as one of their top three priorities.

Financial institutions are using AI-powered tech more often to improve profit margins and help compensate for reduced deal volume and value. In fact, Deloitte says GenAI use in the front office can boost bank productivity by 27% – 35%, a $3.5 million revenue increase per person, making it one of the key investment banking technology trends in the financial services industry for 2024.

Trend #2: Deep Learning in Banking

No one can predict the future with 100% accuracy. However, deep learning models have the potential to give investment bankers a much clearer picture. From exchange rate and stock market predictions to more accurate revenue and investment return rate forecasting, taking advantage of deep learning can help advance your firm.

Recently, deep learning has risen in popularity over its more well-known counterpart, machine learning (ML). Deep learning aims to resemble and emulate human thinking and reasoning more closely than ML and can process many more types of material. However, deep learning requires a massive amount of resources, including computing power and the data necessary to train the models. But as deep learning grows more accessible, expect it to become an integral part of the investment banking industry.

Trend #3: Robotics in Banking

Before we can dive into how robotics is changing the landscape for firms, it's important to first understand robotics in banking most often entails robotic process automation (RPA) — not physical robots. RPA can help automate many of the processes firms must do on a regular basis. From inquiry management — at least the intake and initial handling — to speeding up document management, RPA can boost your firm's productivity across the board.

RPA is different from AI since teams generally set up the rules RPA follows, giving firms tighter control over what they get from the technology. Some companies have paired RPA with AI, but the process is still quite new. As the tech is not yet mature enough, leaving AI automation unchecked is not recommended, though as the tech evolves, it's sure to become a bigger part of how the banking and finance industry improves productivity.

Trend #4: Natural Language Processing (NLP) in Banking

Natural language processing (NLP) is technology where AI models and algorithms that have been trained on massive amounts of language data can more easily understand how humans regularly communicate over text and voice. Perhaps the most common example of NLP is AI-powered assistants, such as Apple's Siri or Microsoft's Cortana.

Think of NLP as an advancement to the phone trees you often get when calling customer service. Rather than say "representative" several times, NLP is able to take a sentence, understand it, and then route you appropriately. As you might imagine, NLP in banking can be incredibly useful, and firms that implement the technology to further their communication efforts will be rewarded.

Trend #5: Investment Banking Automation

Each trend we've covered so far leads to a larger conclusion: Advanced technology and automation will become mandatory for investment banking firms. Automating the more time-consuming, repetitive tasks that bog down dealmakers should be a priority in the coming year, and AI, RPA, and NLP are tools that can help you in that endeavor.

For example, if you add a SaaS investment banking software, such as a deal sourcing platform, that uses AI to source and validate information on potential investment opportunities, you're far more likely to find a company that accurately matches your thesis than with a platform that doesn't use AI. That deal sourcing platform can then automate sending its findings to your CRM to speed up the dealmaking process.

Additional Questions Regarding AI in Banking and Finance

You may have some concerns about the ramifications of these banking industry technology trends, so here are some of the most frequently asked questions about AI in banking:

What Are Some AI in Banking Examples?

AI has many uses within banking. From raw data processing to enabling insight gathering for financial forecasts and trend analysis to more easily personalizing communications, AI can be incredibly beneficial. On top of the examples we’ve shared already, a simple yet powerful instance of AI in banking and finance is streamlining document processing. AI can scan and vet a contract much more quickly than a human while still flagging any potential problems for manual review.

What Are the Disadvantages of AI in Banking?

As with all new technology, it can be tempting to let AI take on more than it should. A major disadvantage of AI in banking is that AI has no human reasoning potential. So while the technology can process data at far faster rates than humans, you should never let it make decisions or take actions on that data without a human in the loop.

Will AI Replace Investment Bankers?

Despite how AI is depicted in science fiction, the technology is still a long way from displacing humans. As we explained above, AI can take on the easiest parts of the investment banking job, but people must define the strategy and rules that it follows.

The Future of Investment Banking Is Here

Now is the time to take advantage of new banking technology. AI, NLP, deep learning, and automation are all integral to this tech-enabled future that will help you increase productivity in every part of your firm. From initial deal sourcing to streamlining the entire dealmaking process, AI has the potential to launch the banking and finance industry forward.

Learn More About the Future of AI in Banking

To learn more about how AI is changing the banking and finance industry and how you can navigate these technological advancements while avoiding catastrophe, watch our webinar on-demand.