AI in investment banking24 December 2019

Leveraging AI in Investment Banking: What’s the Deal?

If investors and private companies are the two major parties involved in the investment process, corporate and investment banking are the bridges that connect these two parties. While the corporate banking sector handles short-term financial requirements of its clients, investment banking shoulders the challenging responsibility of assisting clients at the macro level. From mergers and acquisitions to underwriting and fundraising, investment banks are constantly expected to come up with novel ideas and strategies to prepare the clients for hassle-free journeys ahead. In such a scenario, should the investment banking sector be bogged down by repetitive and time-consuming manual tasks?

Enter Artificial Intelligence! In the 21st Century scenario, AI, together with its counterparts Machine Learning and data science, is rapidly taking over many redundant processes in various industries, thus enabling these sectors to escalate in their journeys. So, what is the role of AI in the investment sector, and how can this domain benefit by leveraging this disruptive technology? Here’s the deal:

  1. Predicting Future Market Trends
  2. One of the most indispensable responsibilities of investment banks is to make informed predictions on investment market trends based on detailed market analysis and research. In such situations, Machine Learning technology can help investment banks leverage this information and formulate systematic patterns and predictions based on the acquired data. Such predictions can help investors, share market brokers and private companies to come up with plausible solutions to potential investment challenges
  3. .
  4. Automating Buy & Sell Trade Orders
  5. Usually, when a trader places a buy or sell order, a backend team works to identify the right share market broker who can help the investor further in his/her journey. However, on a daily basis, hundreds of traders place buy and sell orders, and finding suitable brokers for such a large number of traders can be rather monotonous and time-consuming. As a result, employees are often hard-pressed for time and find it difficult to accommodate other more productive tasks. AI technology to the rescue!
  6. Artificial Intelligence software systems can successfully analyse buy and sell orders and find the right stock brokers for the traders who have placed the orders, thus increasing efficiency in the process.

  7. Managing Regulatory Compliance
  8. Regulatory compliance is an integral part of ensuring that private companies comply with the rules and regulations applicable to them while they engage in financial dealings. This helps to bring about considerable transparency to processes and ensures that companies carry out all transactions in an ethical manner. However, the regulatory compliance process also involves accessing and maintaining large amounts of data and carrying out comprehensive paperwork. AI software systems can considerably reduce the manual effort involved in regulatory compliance processes by integrating different sets of data and identifying any errors or discrepancies that may arise in the same.


Carrying out mergers, underwriting for companies, analysing market trends, providing financial guidance…the investment banking as a sector has its hands full with responsibilities towards private companies in particular and the investment domain as a whole. As a result, delegating monotonous and repetitive processes to the disruptive technologies of AI and ML can help investment banks to continue adding value to the finance and investment industries from a long-term perspective.


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