Investment banking trends: what’s shaping the industry in 2025

 The financial services industry is undergoing a transformation driven by fintech startups, which causes traditional banks to advance deal-making procedures. For example, ANZ invested $2.5 billion in developing its technology infrastructure to defend itself against retail banking rivals. Yet, it’s inevitable that disregard for change will cause companies in this sector to become obsolete. 

Investment banking technology news shows that by 2029, it alone will generate a revenue of $416.50 billion. This shows that tech has grown and is skipping across all industries, and tech investment banking is a case in point.

Besides, this article will break down 9 crucial investment banking industry trends defining 2025. Today, you will find what matters most and profit from a change. Let’s start!

Artificial intelligence (AI)

Artificial Intelligence (AI) and machine learning have transformed how investment banks utilize data. Now, these technologies help top banks better understand consumer tendency, point-of-sale credit decisions, and other gaps in supply and demand. With the potential to automate trade processing for any investor, AI-driven banks offer faster trades. Some utilize specialized learning techniques to identify and predict successful customer investment strategies.

AI has revolutionized Fintech through its efficient fraud detection, risk management, and credit-rating algorithms. AI can help spot fraudulent transactions before they happen.  This allows for manual verification to reduce investment scams. Smaller fintech startups with limited consumer data can better estimate people's credit ratings and loan repayment ability to offer loans without requiring collateral, such as property or assets.

Real-life example

Man AHL, a London company, uses AI to find profitable investment strategies and executes trades automatically in various global financial markets.

Generative AI

Through leveraging technology LLMs and deep learning algorithms, the investment banking industry has experienced a transformation, thanks to GenAI. Larger banks and GPTs operate GenAI models with massive databases containing financial reports, market tendencies, and transaction records. Here’s everything you need to know:

• Financial models benefit from automation in generating discounted cash flow (DCF) models, deals and valuations reports, and scenario analyses.

• Market research systems deliver technology landscape performance, market tendency, and competitor study insights.

• The team prepares investor presentations through custom preparation of datasets and recommendation-specific pitchbooks and investor decks.

• The system performs risk simulation through existing and real-time market data to estimate future outcomes from past sequences.

Real-life example

For example, the JPMorgan Chase COIN (Contract Intelligence) program employs NLP-based General AI to extract essential data points from legal contracts. The system handles 12000 new contracts through a second-long operation process that requires 360000 hours of manual work each year.

Robotic process automation

RPA works through software bots to automate repetitive tasks, boost operational efficiency, and make processes more accurate. Core banking systems implement RPA tools, including UiPath, Blue Prism, and Automation Anywhere, to perform the following functions:

• The system uses automation to transfer financial data, eliminating human errors while processing data faster between different systems.

• Transaction observation and regulatory report generation support operational compliance regulation, which fulfills the requirements of MiFID II and Basel III.

• The system performs trade settlement duties alongside rciliation procedures to shorten settlement periods and decrease post-trade mistakes.

• The platform executes automated Know Your Customer (KYC) and Anti-Money Laundering (AML) procedures, shortening client verification.

Real-life example

The retail giant John Lewis adopted 60 autonomous robots as part of its warehouse operations to improve efficiencies during peak retail periods. The autonomous robots helped reduce costs by £1 million while boosting storage capability by 75% to optimize their packing and dispatching role of 17 million products in the pre-Christmas period.

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AI in Fintech: Use cases of AI and ML in Fintech

More than 90% of global Fintech companies are already relying heavily on artificial intelligence and machine learning. Do you know how?

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Direct listing technology

Most business models are moving towards direct listings instead of traditional IPOs to raise capital. With IPOs, banking and software companies must hire underwriters who boost the IPO process and charge a commission for their work. Multiple companies fail to meet the costly price tags associated with these high fees. Some businesses choose direct listings to retain ownership shares instead of giving them to investors. Through direct listings, companies avoid restricted lockup periods that impose buying and selling limitations after an IPO. Direct listings provide organizations with increased flexibility because of their desirable control features.

This shift toward direct listings has created a demand for new technological platforms to help small and medium-sized companies with the process. Soon, we will see many trends in investment banking that can help you save millions of dollars.

Real-life example

Spotify and Palantir are great examples of companies that have opted for direct listings instead of IPOs. This strategic decision highlights their desire for greater control and transparency.

Natural language processing

Natural language processing (NLP) uses AI to help computers understand and interact with human language. NLP helps investment analysts turn unstructured data into organized data faster than ever. It can crunch annual investment reports, investor calls, and regulator statements and convert them into digestible info.

NLP has seen widely used applications in the due diligence process. Due diligence teams can now use NLP to process information faster, work more efficiently, and save time on tasks that are usually very time-consuming.

FinBERT is a brilliant example of NLP in the investment technology sector. It uses pre-trained language models to perform financial sentiment analysis of specific data sets. This analysis tells how the market will react to certain info about a rise or fall in stock price.

Real-life example

By the way, NLP tools at Goldman Sachs analyze earnings calls by recognizing small variations in how executives phrase or express themselves. The study reveals forthcoming changes in business performance, thus enabling investors to have a market advantage.

Virtual Data Rooms

A Virtual Data Room (VDR) online database can securely store confidential information. VDRs are online spaces where businesses keep essential financial info, allowing companies to store, secure, and access their critical documents safely.

VDRs have provided a great solution against cyber attacks for investment banks. They virtually store deal-making sensitive finance information for company IPOs, mergers and acquisitions. Only the relevant parties have access to this info. This leads to increased productivity, better security, and improved regulatory compliance.

Real-life example

Goldman Sachs deployed VDR technology in 2019 when it managed the WeWork IPO. By implementing a virtual data room system, the bank distributed secure access to investors and investment to review sensitive financial documents that maintained strict confidentiality protection. VDR technology improved M&A activities and due diligence procedures because it protected vital info against outside threats.

Open Banking

Open banking is another current tendency based on the PSD2 directive and the Open API. Open banking allows the banker to share data with third-party providers (TPPs) easily. This gives customer account info and payment systems access through application programming interfaces (Open APIs).

One of the key advantages of open bank data is the “deployment” of a client-oriented banking service. This approach allows for innovative offerings and a more tailored customer experience.

Real-life example

Open banking holds its pioneer in the global financial sector in BBVA. Such investment bankers give third-party developers system-level access through its Open API, enabling startups and public tech companies to develop FinTech products that merge flawlessly with BBVA's infrastructure. Open-door access has unleashed new financial products alongside enhanced competition because it has created personalizations for customers within the industry. BBVA improved its relationships with tech firms through these efforts and strengthened its customer relationships.

Open bank data's main task is to overcome “data slavery.”  Classical financial institutions have info about customers, preventing innovators from entering the market. This also affects consumers, who do not have the opportunity to choose the most profitable and suitable services.

Open banking significantly reduces, if not eliminates, the issue  of “data slavery.” Open protocols enable all market participants to access and use the collected information effectively.

For classic financial institutions, open bank data is more of a threat than a strength in tech. Large banks will have to share info, which breaks their monopoly. Yet, if you look at the future, they get momentum for development. The need to share data and compete in new conditions leads to creating new services, innovating, and improving customer experience.

For financial startups, open banking development opens up many opportunities. But why would you need it? The key is initiating payments from a client's account and receiving transaction data.

Read more:  Core open APIs for Banking & Payments

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Sustainable finance products

An increasing number of investors and public authorities joined regulators in driving the rising interest toward sustainable finance products in investment banking operations. Sustainable finance moved from a specialized field to the main strategic priority within all business domains. The growth of technology investment banking creates a dominant position for sustainable finance, representing the most critical challenge and chance in the upcoming ten years.

Sustainable finance encourages organizations, especially technology companies and startups, to embed ESG elements into their future business planning. By implementing this strategy, organizations become better equipped to analyze extended consequences on their area of business as well as environmental and community effects. Maximizing stable growth forms the fundamental goal of developing solutions that simultaneously offer stability and growth benefits to sector companies and the community. Sustainable finance operates through investments made with consideration of ESG factors while encouraging inclusive capitalist systems that produce positive effects for everyone involved.

Real-life example

The investment banking leader, Goldman Sachs, pioneered sustainable finance by adopting leading positions. The company uses its expertise to embed ESG standards throughout its investment algorithms and public company and technology firm investment plans. The company's sustainable initiatives lead to the creation of technology companies through mergers and acquisitions (M&A) and partnerships that combine sustainable objectives with financial prosperity. The technology investment banking services delivered by the company serve as a benchmark for promoting ethical investments throughout the banking technology industry.

At present, investment banks recognize sustainable finance products and demonstrate their belief in how sustainability targets lead directly to stable long-term profitability. The market expansion for debt and equity products and services that support ESG initiatives results from increasing participation by primary banking tiers and boutique banking institutions. Companies in the world, including tech startups and internet companies, adjusts to this tendency because they want to create products that bring financial gains alongside societal and environmental benefits.

The investment banking sector has been changing its business model through sustainable operations because a core focus on technology remains in this evolving market. Investment big tech businesses like Morgan Stanley and Microsoft use technology to create new investment opportunities focusing on the middle market. Because this tendency is developing rapidly, the future direction of investment banking services will strongly depend on sustainable finance and Environmental, Social Governance (ESG) investment approaches.

You can find actual cases of using this tendency in the article Sustainable Fintech. Few cases to take as an example.

Blockchain technology

Blockchain is an extremely safe and highly traceable method for virtual financial transactions. Multiple cryptocurrencies based on the blockchain are being used in these types of deals.

The financial services sector is also experiencing an enhanced adoption rate of blockchain for several reasons. First, it replaces intermediaries between fund transfers and provides a peer-to-peer transaction method. Second, the blockchain is highly secure and almost impossible to tamper with. The chances for any fraudulent activity to occur are non-existent.

Although this investment bank technology is beneficial, it hasn’t experienced growth as fast as AI or ML. This is because blockchain is a slightly complex concept that average consumers don’t easily digest. Also, since cryptocurrencies are still not regulated in most parts of the world, there is a lack of trust in transactions on the blockchain, which is hindering mass adoption.

Real-life example

Several cryptocurrency wallets, such as DDKOIN and OKEx, actively leverage blockchain to process, hold, and transact cryptocurrencies for users.

Mobile apps

All blue-chip investment banks now have fancy apps with the same physical branch services. Some of these services include access to real-time market data analytics, market dynamics, the latest market intelligence, investment banking sector reports, and so on.

Users can create customized dashboards to share data directly with their representatives. The best part is that app APIs work directly with many other investment apps, making it even easier for consumers.

Real-life example

Acorns and Affirm are two apps that offer a wide range of financial and investment-related services, but they are only the tip of the iceberg. Dozens of others provide similar financial services in the investment banking space.

Relationship management

Relationship management systems are one of the most essential banking technology tendencies designed specifically for deal-driven teams. Such systems can streamline your business development workflow and make their networks work for them. The most crucial relationships form a matrix that spans any investment banking group within investment like industry, product, and financial sponsor coverage teams that make up your greatest technological asset. If you manage this asset efficiently, you can do wonders in investment banking.

Real-life example

Dedicated Customer Relationship Management (CRM) tools such as Dynamics 365 provide lots of predictive analytics and automation capabilities that you can leverage to nurture customer relationships and get the most out of them.

Final thoughts

Access to the latest investment banking technology trends can significantly help, but what is more important is how you put it to use. And if you don’t apply it right, even the most advanced financial technology can’t help you. The future of investment banking is likely to see a more tech-enabled workforce focusing on higher-value activities.

While technology may automate some tasks, the human touch will remain important. Investment banks must develop strong analytical and problem-solving skills to navigate complex situations and provide strategic advice to clients.

Choosing a reliable Fintech software development partner for your company may make you the next unicorn in investment banking. If you need professional guidance, our fintech consulting team is always available to fulfill your strategic objectives.