It’s not just about what you can offer clients; it’s also about reducing the manual workload on your staff. At its core, it’s all about automation.
Did you know that over 70% of investment bankers see a major shift on the horizon? Automation provides them a chance for a smoother, more efficient future.
Why is that?
It’s a chance for everything to run like clockwork. A shiny conveyor belt moves tasks along with precision—that’s what automation offers. It transforms tedious processes into seamless operations.
If your firm is still doing things the old-fashioned way, it’s like trying to build a race car with a screwdriver while everyone else has the latest robotic tools.
What’s the cost of staying behind?
Will you risk losing clients to competitors who embrace innovation?
As of 2024, about 60% of financial institutions in the U.S. and 85% of large financial institutions have implemented automation, with another 65% saying they are actively incorporating automated solutions into their investment platforms. Another 23% of respondents associated with investment banking named AI as a top priority. Two-thirds of banks plan to increase automation investments by 6-10%.
So why has such a trend formed in the investment banking market? I dare to assume that it is due to high competition, the owners do not want to miss the opportunities that automation gives, to attract new clients, providing them with a new experience in investing.
In this article I will try to analyze in detail the problems associated with automation in investment banking, but I will also consider the advantages.
Current state of investment banking
But first is first, investment banking is a financial sector that deals with capital raising, mergers, acquisitions of companies, securities trading and financial advisory services.
Today, investment banking is undergoing a global transformation driven by several key factors such as: capital requirements, a stable political environment in a number of major countries and ESG (environmental, social and governance) integration.
Currently, investment banking has an average annual growth rate of 7.58% and a capitalization of USD 115.48 billion as of 2023. This situation is driven by the development of digital assets, infrastructure investments, and activity in the mergers and acquisitions (M&A) market.
Overview of traditional investment banking activities
Traditional investment banking operations are a wide range of services offered by banks to individuals and legal entities. In essence, they are a form of interaction between a financial institution and a customer and are the core of any banking activity. Below I will discuss a few traditional banking operations.
Deal sourcing and execution.
Investment banks are constantly analyzing the market for companies, industries and evaluating competitors. Such operations are very difficult to carry out without automation and until recently were carried out manually, which requires a huge amount of time.
Market analysis and research
This can include several types of analytics:
- Fundamental analysis. The financial capabilities of the company are studied, the profit is estimated.
- Technical analysis. This is where analytical tools that predict the main trends of growth or decline come into play. The volume of sales, trading, volatility is analyzed.
- Sectoral analysis. An entire industry or sector of the economy is evaluated. Investment opportunities are evaluated.
- Marketing research.
- Strategic analysis. At this stage it is necessary to develop a strategy for clients on the basis of various analytical data.
Customer Relationship Management
This is where CRM systems come into play, without which it is impossible to provide quality services to clients. Customer Relationship Management helps investment banks to effectively manage client data, store reminders, and make regular database updates. It is impossible to build a quality relationship with a client without personalization, which includes individual approach, development of strategies, evaluation of investment portfolio, access to personal reports.
Automation: challenges
I’ll start, perhaps, with the biggest fear of investment banking owners – cost. So that’s how much it will cost to automate the platform. Specific figures, such information, owners, as a rule, keep secret from competitors, however, I can assume that the price of the question depends on several factors:
Developing your own automation software. This is the path taken by large banks, creating Citi Velocity or Goldman Sachs Marquee platforms. The cost of development is estimated at hundreds of millions of dollars.
Buying a ready-made solution. This is the way Deutsche Bank has gone, having signed a contract for the purchase of the OpenFin platform.
The main page of OpenFin
BNP Paribas Bank also decided to use Symphony’s off-the-shelf solution.
The main page of symphony
The cost of off-the-shelf solutions can vary from 1 to 10 million dollars, it all depends on the individual needs of the investment bank.
There are other equally important risks. Investment banking owners face problems integrating automated platforms. There are difficulties in training staff. Let’s take a closer look at this problem:
- Outdated infrastructure. If the bank is using older software, implementing newer, modern automation platforms will require significant effort, including financial tomorrows.
- Bringing it under a single standard. The use of several platforms for automation will require the creation of connectors, to combine databases and interfaces. It will be more convenient for staff to work with one platform with one interface than to constantly switch and confuse between different systems.
Data protection and cybersecurity. I will elaborate on this point. The point is that when integrating new automation systems, vulnerabilities and gaps can be exposed that can become a target for hacker attacks. And no one wants valuable data leaks. To avoid this problem, the platform must comply with international security standards GDPR in Europe or CCPA in the US.
Support and scalability concerns. These are fair concerns. Poor support can lead to a significant drop in customer service. And a low-quality platform can cause scalability problems, up to data loss, damage to database integrity and other troubles. To avoid these problems, I recommend using solutions from trusted developers who are interested in preserving their reputation and supporting corporate clients.
As a rule, such developers have high-quality technical support, which promptly answers all questions and quickly solves problems related to integration, API modification and employee training.
Regulatory Pressure
Investment banks face various restrictions from government regulators. Following the 2008 global financial crisis related to the mortgage bubble, regulators have significantly tightened investment controls.
Enhanced capital and liquidity requirements (e.g., Basel III).
(AML/KYC). Controls on suspicious transactions and dealings. Prevention of money laundering and terrorist financing.
Restrictions on proprietary trading (Volcker Rule in the US).
Growing Competition
The main source of competition is young fintech startups offering an innovative approach to investment business. Such companies actively use advanced technologies (AI, blockchain, decentralization, transaction transparency, full automation, quality analytics).
Data management challenges
Another problem faced by investment banking. The growth of clients, increase in the number of financial instruments leads to a real information collapse. Data automation helps to solve the problem of structuring, transferring, analyzing. Inefficient data management can have a negative impact on the quality of customer service, which means loss of reputation, outflow of funds and other troubles.
What is investment banking automation?
Investment banking automation is the application of advanced information technologies that allow improving the quality of customer service, speeding up and reducing the cost of banking processes, and obtaining high-quality analytics.
Let’s take a look at what types of automation there are.
Robotic process automation (RPA)
This technology is based on “robots” or bots that mimic human actions. In investment banking, robotic automation is used to analyze transactions, to identify fraudulent or suspicious transactions.
RPA is increasingly being used to automate processes such as:
- Invoice creation.
- Payment management.
- Customer support.
The main benefit to investment banking from implementing RPA is accuracy of task execution, cost reduction, improved customer service quality, and increased productivity.
Artificial Intelligence (AI) and Machine Learning (ML)
With artificial intelligence, the quality of trading operations can be significantly improved:
- Speed increases. Transactions are concluded in milliseconds.
- Utilization of sophisticated strategies. Artificial intelligence can process and take into account many factors simultaneously, including technical indicators, macroeconomic news, and trading volumes.
- Elimination of the human factor. The main plus of AI is that it is not subject to emotions like a live trader. By eliminating such human qualities as fear, greed, panic, artificial intelligence can make quite different decisions.
According to The Trade in 2022, 57% of investors used algorithmic trading to make trades.
Artificial intelligence can help with recognizing various risks, including credit risks. The reader may have a question, how does this work? AI performs analysis on various customer data:
- Transactions.
- Credit history.
- Macroeconomic indicators. For example, reducing credit limit for customers during an unfavorable geopolitical situation or an impending financial crisis.
Using machine learning, patterns can be created that will be recognized and signal to security that a given customer is on the verge of default or bankruptcy. By analyzing customer data, AI is able to quickly recognize fraudulent activities, suspicious transactions that violate local laws and block them in time, sending them for manual review by a security operator.
Blockchain technology
When talking about the introduction of AI-based systems into automation, we can’t fail to mention blockchain. You may have heard about it in the context of cryptocurrencies. This technology is relatively new, but it has already managed to live up to the expectations for its application. So, let’s look at what blockchain is and what is it good for?
The main tasks that blockchain performs are asset tokenization. When ordinary shares, investments, currencies are converted into digital tokens. Security and transparency of transactions, tracking of all transaction chains. In addition to the above tasks, the technology is based on smart contracts that automate transactions.
Examples of automation tools currently in use
Let me start with Deutsche Bank. The Board of Directors realized the full potential of artificial intelligence a long time ago and is actively implementing it in its products.
“We expect these technologies to become integral to virtually every aspect of our business in the future, from internal processes to customer interactions and opportunities.
We are using AI solutions to automate manual processes and improve advisory services for clients. Examples include speeding up the manual review and processing of loan documents, using AI to optimize client portfolios in Wealth Management, and monitoring transactions for suspected financial crime.”, Deutsche Bank states in its press release.
Another bank is actively involved in integrating its systems with artificial intelligence. This is the British bank HSBC.
HSBC is currently using AI to automate compliance-related processes such as KYC and AML. AI algorithms are also being used to analyze customer data to identify suspicious transactions, preventing money laundering and other financial crimes.
“For us, AI is not just a buzzword; it is a fundamental pillar of our large-scale digitalization strategy. Through the thoughtful use of machine learning, we can offer our customers a more personalized experience, make more informed data-driven decisions and stay ahead of the curve in an ever-evolving industry.”, said Christiane Lindenschmidt, Director, Digital & Data, Markets & Securities, HSBC.
Benefits of automation in investment banking
In this section, I will try to review the main benefits that come with automation in investment banking.
I will start with the main one. Automation increases productivity by reducing manual labor. Routine operations such as verifying transactions, filling out form documents, collecting and analyzing data fall to the automated system. Employees can devote their time to more important tasks.
Increased efficiency and productivity
It would seem that why introduce new technologies, spend money, effort and risk if everything works as it is. But you can do much better, more efficiently. Increase productivity. This is why we need automation in investment banking.
Automation in investment banking will help to increase productivity. As an example, I propose to consider such an operation as transaction processing. If it used to take several minutes to several days, with automation a transaction is processed in a fraction of a second. Suspicious transactions are automatically blocked. Analytical reports, trading signals for traders received from automated systems are more efficient.
Optimization of repetitive tasks
This is one of the main functions and challenges of automation. Reduce routine operations by entrusting them to algorithms, robots and bots. You can automate such processes as data entry, processing requests, sending reports and performing standard operations.
The advantages of optimizing repetitive tasks are obvious: Robots work around the clock, without errors and at high speed, which allows you to speed up tasks and reduce costs.
Faster decision-making processes
Speed in investment banking plays a key role. Falling or rising quotes cost millions in losses or profits. It is very important to react quickly to changes in rates, quotes, especially for highly volatile assets. Automation based on AI and machine learning makes it possible to make a split-second decision to sell or buy, increasing profits and minimizing losses.
Increasing accuracy and reducing the human factor
Automation of investment banking implies the introduction of modern technologies. Investment banking is associated with risks and automation helps to minimize these risks by signaling the client at what point to get rid of assets or acquire assets. According to recent expert estimates, more than 52% of investment banks are using AI to generate profits. According to Gartner, the use of AI by investment banks could increase their value to $2.9 trillion. US DOLLARS. The increase in investment banks’ profits is made possible by reducing risks associated with human factors and increasing the accuracy of forecasts.
Data processing and analysis
Automation is changing the whole traditional view of data processing. I should mention a completely new technology of data collection. These can include automated systems using APIs, web scraping and specialized platforms that collect data in real time. Let’s take a closer look at data processing technologies:
- Big Data: Big Data technologies such as Hadoop, Apache Spark are used to process huge amounts of data in real time.
- Artificial Intelligence: AI systems help in analyzing historical data with high accuracy, studying current news and identifying trends and patterns.
- Python and R: Programming languages. namely some of their sublanguages that are widely used for financial analysis and building analytical models
Compliance and regulatory reporting
The reader may ask a very fair question, but how does automation help you comply with the current regulations being adopted by regulators? The answer to that question is simple. Automated systems can quickly verify that transactions are compliant with AML (Anti-Money Laundering) or KYC (Know Your Customer) requirements in real time. As a result, customers can avoid fines and being placed on various sanctions lists.
Improved customer experience
With most of the routine operations being done automatically, employees can spend more time on customer issues. A number of platforms have a digital assistant to help the customer resolve simple issues. Automated systems can predict customer needs and offer them new services and products. I will say more, such solutions are able to serve a huge number of clients at the same time, giving them access to different financial instruments: investment portfolios, trader interface, accounts, new asset classes.
It will be especially important for clients to receive any reports, statements and other documents related to investments, movements of funds.
Personalization through data analytics
I think many investment bank owners will agree with me, but the main task of such institutions is to make money for their clients by providing them with all the necessary tools.
Automated systems based on artificial intelligence can do this perfectly well by creating an individual customer profile based on their personal data:
- Social media, natural language processing (NLP).
- Use of certain services.
- Type of investment.
But the most important thing, in my opinion, is robo-advisers. AI-powered automated systems that offer clients customized investment strategies based on the analysis of their personal data, including credit histories, preferences, risks.
Faster response times
The role of automated systems in the scalability of investment banking cannot be overlooked. With fast processing of large amounts of data and high speed of transaction execution, it is possible to expand the business without significant financial costs.
The introduction of AI tools into automated platforms, gives wide opportunities to analyze events in the financial market. The client receives real-time forecasts (of fairly accurate quality) on the rates of stocks, metals and other assets, as well as hints on when to sell or buy.
Taken together, all these features associated with the automation of processes in investment banking give undeniable competitive advantages not only to owners, but also to clients.
Potential challenges and considerations
While there are many positives associated with automating processes in investment banking, there are some risks. In this section, I will attempt to describe some of the challenges associated with automation in investment banking.
Resistance to change in organizations
Automation can fundamentally reshape the team, for example, employees who used to do routine work that has now been replaced by software and “robots” can be made redundant. Another problem is the lack of qualified personnel and training for new software and interfaces.
Data privacy and security issues
Cybersecurity is a cornerstone of any bank. No one wants data about customers and their accounts to fall into the hands of intruders. The introduction of new automated systems jeopardizes cybersecurity and risks the emergence of vulnerabilities in new software.
Impact on employment and labor force dynamics
First of all, I would like to point out the fact that automation may cause a number of employees to be laid off. Algorithmic trading based on AI and machine learning does not require a large number of traders and analysts. In turn, new jobs related to IT-specialties appear. Such specialists are needed to customize software, fix vulnerabilities, train staff, and release updates.
Legal and regulatory implications
Automation systems must comply with international data protection standards, such as GDPR in Europe or CCPA in California. Investment banks are required to ensure that data is stored, processed and transmitted securely. Along with automated systems, financial institutions are required to implement systems that comply with anti-money laundering (AML), countering the financing of terrorism (CFT), and securities regulation.
Regulation of automated trading. Automated trading based on AI and machine learning can create certain risks, increase volatility. A number of regulators, such as the SEC in the US and ESMA in Europe, have put in place rules to limit the market risks associated with automated trading.
Future trends in investment banking automation
It is difficult to overemphasize the role of AI and automation in general in the investment banking sector. It is expected to play a key role in the coming years in creating strategic analysis, improving efficiency and minimizing risk. AI will soon become an integral part of all investment processes, including trading, risk management, improving forecast accuracy and reducing operational costs.
As we can see, the introduction of AI and automated systems into investment banking processes has more pros than cons. It is obvious that in order to increase competitiveness, it is necessary to be concerned about the introduction of automated systems based on AI already now. This will provide undeniable advantages and benefits for both the bank and investors.
Evolution of AI and machine learning in finance
In the 20s, the evolution of AI and machine learning has touched personalized financial solutions. This has enabled investment banks to offer their customers the products they need. Intelligent automation, including natural language processing (NLP), is actively evolving, which has significantly improved the quality of trading operations, increased the accuracy of analytics, and created profitable investment strategies.
Integrating automation with existing platforms
I can well understand investment bank managers who are wary of implementing automated systems and I fully share their fears. However, I will try to convince you that the risks of implementing automated systems are minimal and there are more pros than cons.
Let’s discuss in order, where to start. It is obvious that the integration process will affect all aspects of the banking institution’s work, from securities trading and asset management to bringing it to common standards set by the regulator and establishing customer service. So, it is necessary to prepare thoroughly:
Understand the scope and depth of automation.
Develop APIs and interfaces.
Create robo-advisors to manage investment portfolios.
Implementing artificial intelligence (AI) systems.
Providing technical support to clients and bringing them in line with the regulator’s legal norms.
Our company offers comprehensive investment banking automation solutions that will help reduce financial costs in the short term. With us you will get a reliable personal data security system that fully complies with global standards and is based on proven technologies:
Encryption of data at rest. Even if an attacker gains access to the data, they cannot decrypt it and use it for their own purposes.
Encryption in transit. All data transmission channels are securely protected by cryptographic means, e.g. TLS 1.2 and higher.
MFA. Multi-factor authentication. To access his account the client needs to enter a password, one-time code, biometric protection can also be activated.
Role-Based Access Control, RBAC. Differentiation of employee privileges. Each employee gets access only to the data he/she needs to work with.
Special attention is paid to customer support. Chatbots with artificial intelligence, available 24/7, messengers (communication with live employees), FAQ sections, full usage guide. We integrate various communication channels:
email (e-mail, phones, chats, mobile apps, social networks). I understand perfectly well how important it is to keep clients and make them have as few problems as possible when switching to automated platforms.
For stable operation of the investment banking system, it is best to use one vendor-developer of automated platforms. Long-term cooperation with our company guarantees quality support, timely release of updates and staff training.
Predictions for the next decade
Experts predict that in the next decade automated systems will work on the basis of self-learning algorithms. The development will also concern “smart platforms” that will combine all financial tools, from trading and transactions to analytics and reporting. Quantum computing no longer seems like science fiction. They will help to quickly process huge data sets without loss of quality.
Increase of implementation rates
It can already be safely stated that the pace of automation implementation in the investment banking sector is increasing. This is due to growing competition, attempts to attract new investments. New challenges require executives to utilize advanced technologies, including AI and machine learning.
The rise of hybrid human-automation models
Such hybrid models have started to emerge because of the need to combine automation with human involvement. Despite all the benefits and power of AI and self-learning systems, human expertise cannot be overlooked. This is especially important in times of transition, where many investment banks have a policy of supporting rather than replacing. Automated online platforms can be considered as a prime example. Such programs are set up by a human, the client or trader controls the course of transactions, observes the current operations and in case of a failure in the software before the situation under his control.
Examples of successful automation in investment banking
Recent history knows many examples of successful automation for investment banking. Let’s start with the famous Goldman Sachs bank and its Marquee platform, the development of which began back in 2014.
Platform Marquee of Goldman Sachs. Source: https://cdn.marquee.gs.com/cms/public/cryptodashboard.PNG
This platform has automated trading and investment operations within the Goldman Sachs structure, giving the client access to various analytical tools in real time. Marquee helps the bank reduce infrastructure costs, increase transaction speed and improve client experience. “We are investing in platforms like Marquee to serve clients in new and more efficient ways,” said CFO Stephen Scherr.
Another successful example of automation in investment banking is Citi Bank with its Velocity platform.
Platform for automation of process Velocity.
This platform has automated trading and investment operations within the Goldman Sachs structure, giving the client access to various analytical tools in real time. Marquee helps the bank reduce infrastructure costs, increase transaction speed and improve client experience. “We are investing in platforms like Marquee to serve clients in new and more efficient ways,” said CFO Stephen Scherr.
Another successful example of automation in investment banking is Citi Bank with its Velocity platform.
“Citi Velocity is one of the most widely respected client portals for content, data, analytics, and trading in our industry. We are proud of the platform and its continued evolution. With an ever-changing market landscape, we will remain proactive in our efforts to be at the forefront of the industry and deliver the best of Citi to our clients,” said Cris Rosenberg, Global Head of Citi Velocity.
Looking ahead, it’s clear that investment banking must continue to evolve to meet new challenges, making the integration of automation more important than ever.
The importance of automation in investment banking
To summarize, I would like to highlight a few important points. Automation today is a necessary process that will help you save significant money, attract new clients, and receive accurate analytical data for trading operations. Yes, so far, many people are suspicious of new technologies, but they should not be feared. We can already state the fact that automation has completely transformed the investment banking sector. It is no longer the same, and it continues to change.
More and more clients investing their funds trust the analytics and reports provided by AI-based automated systems. If you miss the opportunity to automate investment banking today, you are more likely to fall by the wayside or lose the market altogether tomorrow. It’s up to you!
Wrapping it up
Investment banking requires a great deal of automation. The business landscape is rapidly evolving. Companies have to change or risk falling behind.
Efficiency and accuracy are increased via automation. Customer service is enhanced. There is no ignoring their advantages.
Yes, there are difficulties. It can be difficult to integrate. Expenses could mount up. However, these obstacles are surmountable with the correct instruction and equipment.
The move is anticipated by more than 70% of investment bankers. Now is the moment to take action. Welcome automation. Continue to be competitive.
Future times will be mechanized. Grab the chance. Rethink success by transforming your operations.
s have high-quality technical support, which promptly answers all questions and quickly solves problems related to integration, API modification and employee training.
Despite these challenges, the benefits of automation in investment banking are compelling and warrant serious consideration.