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Surging Use of AI in the Investment Banking Industry

AI is helping banks save huge capitals in the form of cost savings, estimated to climb as high as USD 447 billion by 2023. Majority of banks (80%) are aware of the business advantages of AI in banking through automation. Numerous banks across the world are planning to apply AI-based solutions to their financial processes, and many are already benefiting from the use of the said disruptive technology.

What Does Statistics Say ?

75% of banks with over $100 billion in assets are presently using AI-based applications, while only 46% of those with fewer than 100 billion dollars in assets use the AI-based solutions at their respective facilities.

However, the most successful use cases of AI in banking at the moment comprise chatbots for customer service at the front offices, and the AI-powered anti-payment fraud technology leveraged across middle offices.

Current Use Cases of AI in Investment Banking

Application of AI in Collection of Market Data

AI-implementation in the investment banking sector can help eliminate the fear of information overload for an investment banking professional. Associates in the investment banking industry are supposed to know the news related to the global financial markets as and when they happen, and sometimes, even before the occurrence of the happenings. An AI-powered intelligence application can help investment bank analysts collect, analyze, and classify news related to the markets in real-time.

Predictive Analysis Assisted by AI Technology

In the investment banking industry, predictive analytics play a vital role in day-to-day work proceedings. Predictive analysis is a financial affair that involves the development of computer models that can predict future trends and events. Utilizing historical data, an AI algorithm tries to forecast future scenarios and situations in the financial markets. It is considered the most target-focused division of data science.

AI’s Role in Trade Processing

Artificial Intelligence, as a disruptive technology in investment banking, can help automate online trading of stocks and shares in the capital markets. Systematic investment strategies can be identified using the said technology, and basis that, a trading system can be built equipped with routing algorithms. This way, whenever a trader will place a sell or buy order, the instilled algorithm will automatically provide the match to close a deal by running a comprehensive search across exchanges, stocks, and trading mechanisms.

Extracting Consumer Insights

Traditionally, CRM (customer relationship management) portals have not been able to ingest and process unstructured data, leading to unidentification of a lot of valuable information. But now, AI has come to rescue, and the technology is well capable of searching for trends among loads of unstructured data. This capability will particularly be beneficial for M&A activities where banking professionals will be able to unlock new market insights.

How Investment Bankers Can Leverage AI to Extract Valuable Customer Info

Investment banking professionals can add their proprietary consumer data to Thomson Reuter’s market research data, and later apply the Squirro’s Augmented Intellect Technology to it. The collected data sits centrally at one location which allows users to extract real-time insights that were not available earlier.

Now, the internal proprietary data and external market data is stored in one location that is highly secure in the CRM system of the user.

Increased Workflow Efficiency

By optimally utilizing the combined data, banks can improve considerably on workflow efficiencies. Besides, never-revealed business connections and opportunities can be tracked with AI capabilities. Remember that investment banking is primarily a connection-driven industry where business relationships do matter. As per the Squirro research carried out a couple of years ago, 87% of those asked on the impact of AI in investment banking, said that the applicability of AI will further soar high if an AI engine gets made that would use relevant data to spot events visiting which can lead to forming a connection with a potential client.

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