The artificial intelligence (AI) effect now hits most of the enterprises, not even sparing the financial services.
AI is a powerful tool that has been widely adopted in financial services. It offers great potential for companies that can deploy it with proper care and prudence.
Alpha generation, fraud detection, algorithmic trading, chatbots, and virtual assistants, and risk management are some of the areas that can actively benefit from using AI.
A 2018 survey commissioned by Greenwich Associates said a mere 17 percent of investment professionals are currently using AI within their processes. While 40 percent of the respondents from the same survey said budgets in AI deployment are likely to increase in the future. While another report from February said that the U.S. banks have started rapidly advertising for posts related to AI.
Automation is not a new concept in investment banking (IB). Junior banking professionals working with excel can easily create macros and help them in financial modeling. However, the process is still labor-intensive and time-consuming. Even while auto-calculating the formulae, the crunching of numbers only frees up a little amount of time. This simply means that one still spends a lot of time staring at the screen.
As of 2017, BNY Mellon is said to use over 250 robotic process automation (RPA) system to reduce the time taken to do a manual job and automate tasks. Around 220 from 250 have already been developed by Blue Prism, this is the bank’s partner firm. Implementing RPA has proven to improve the processing time by 88 percent while 66 percent of the time was improved in the trade entry time.
Advancements in AI are rapidly changing the face of IB firms. Therefore, for you to stay relevant in the industry obtaining a banking certification is highly recommended.
Nonetheless, we will further delve deeper and discuss the other advantage the technology offers to the firms.
AI in predictive analytics
Predictive analytics uses data to predict the future outcome of businesses. With the help of any past data, the AI algorithm analyzes the past and present behavior to predict future events.
A French bank named BNP Paribas used an AI-powered tool in 2017 called Smart Chaser to help them streamline their trade matching processes using predictive analytics. Now the tool uses the data record of the trades made via BNP Securities Services, this further helps identify any type of pattern that will lead to failure. Then the system is used for predicting the likelihood of that particular trade which may further need manual intervention in the foreseeable future.
The Smart Chaser tool is said to provide 98 percent prediction accuracy of making relevant predictions.
AI used for market data collection
For someone working in an investment banking firm, a simple AI system can easily help remove any type of threat information overload.
Professionals working in these firms need to stay updated with the latest news or in certain cases before it could happen. An AI system automatically helps gather data, analyze it for further market prediction.
A report by Qualtrics and Amazon said that around 97 percent of the researchers believed AI will eventually make the role of market research, statisticians (95 percent), and analysts (94 percent) to become redundant. Since the AI system requires a large amount of data to feed themselves, advancement in technology simply means that the systems can now easily auto-feed themselves with data gathered from multiple sources.
Such systems have become highly advanced that they can now autonomously verify and cross-refer these data inputs for the maintenance of high data quality. These will help them remove any type of anomalies present.
Besides this, artificial intelligence is widely used for trade processing and regulatory compliance.
