Artificial Intelligence (AI) is a great tool, which has been highly adopted in financial services. It gives magnificent potential for businesses, which can deploy it with due care and prudence.
Fraud detection, algorithmic trading, best crypto exchange, chatbots, virtual representatives, and risk control are a few areas, which can actively profit by using AI.
Automation is not a new aspect of Investment Banking (IB). Many junior banking specialists working with excel can easily compose macros and help them in financial modeling. But, the process is still labor-intensive and time-consuming. Even while auto-calculating the processes, the crunching of numbers only frees up a little quantity of time. This means that an individual will waste a lot of time staring at the screen.
Advancements in AI are quickly transforming the face of the investment banking industry. In this article, let’s delve deeper and consider the ways AI is shaping the future of IB.
AI in predictive analytics
Predictive analytics applies data to foretell the future outcome of the businesses. With the cooperation of any past data, the AI algorithm analyzes the past and present actions to predict future outcomes. A French bank called BNP Paribas used an AI-powered instrument in the year 2017 called Smart Chaser to assist as well as to streamline their trade matching methods using predictive analytics. Now the instrument uses the data record of the trades made via BNP Securities Services, this further facilitates any type of pattern, which will lead to failure. This is also useful for predicting the likelihood of that special trade, which may require manual intervention in the foreseeable future. It is said that the Smart Chaser tool is able to offer 98 percent accuracy in getting relevant predictions.
AI in digitalization strategy
By deploying AI tools, as well as new technologies which automate the banker’s workflow, incremental efficiencies can be developed quickly. The complete range of processes in the investment banking industry will be affected by Machine Learning (ML) and AI. Sensibly implement AI as part of a coherent digitalization strategy. In the initial step, identify the strategy, based on that reimagining the entire process. Make sure that other employees also adapt to the AI, because it augments and complements the way people work.
AI in market data collection
A simple AI system is very helpful to remove any threat data overloads for someone working in an investment banking firm. The experts working in these firms are required to stay updated with the latest advancements. An AI system automatically helps gather data, investigate it for further market prediction.
According to a report by Qualtrics is that around 97 percent of the researchers concluded Artificial Intelligence will eventually make the role of market analysis, statisticians (95 percent), and analysts (94 percent) become redundant.
Since the AI system needs a massive amount of data to feed themselves, improvement in technology simply means that the methods can now easily auto-feed themselves with data collected from multiple sources.
AI for trade processing
The investment banking industry can leverage AI to automate trade processing for their clients. This offers faster trades, and a few solutions can identify possible investment strategies for the customer to consider. This is also able to execute trades over multiple markets.
A trade automation solution would need an ML algorithm in order to match buy/sell orders from traders to brokers, stock exchanges, or other trading systems, which can fulfill the order. Many electronic routes limit liquidity and maximize costs for the trader, but the algorithm could enhance over time to find the cheapest and safest way to execute trades.
Conclusion
With the improvement of AI technology, the IB industry can effectively focus on better decision-making with much more accuracy. Over time, it seems likely that, the way the internet invented completely new business models. AI will do the same to the IB industry.