MSG Team's other articles

11242 Series B Funding

In the previous articles, we have already learned about the seed funding stage as well as the series A funding stage. We know that entrepreneurs raise seed funding in order to be able to build the prototype of the product. After the prototype is in place, they raise Series A funding to build the actual […]

8846 Dealer Markets vs. Broker Markets

Markets across the world can also be segregated based on the type of intermediary. Prima facie, it may appear that the type of intermediary is not of much consequence. However, over time, market participants have realized that the type of intermediaries has a profound effect on the liquidity, efficiency as well as transaction costs related […]

12485 Bond Market Conventions

While calculating present values of bonds, one may observe that some of the information required to compute the present value is actually missing from the question. However, this is not an error. One needs to understand that the examiner is in a way testing your knowledge of how the bond market works. In the bond […]

9367 Floatation Costs and Investment Banking

Whenever companies need to raise money by accessing the public markets, they have to use the services of investment banks. This is because investment bankers have a readymade network which they use to sell securities to the general public. Investment banks are the central character for a company if it needs to go public. It […]

12867 Conflict of Interest in Investment Banking

Investment banking institutions are engaged in multimillion-dollar transactions. This means that if an investment bank is perceived to be operating in a conflict of interest situation, it could severely damage the reputation of the bank. This lost reputation could end up becoming a financial loss is no time. There have been several instances where conflict […]

Search with tags

  • No tags available.

In a previous couple of articles, we have already seen how artificial intelligence is useful in the field of commercial banking. We have also seen the various advantages and disadvantages of deploying artificial intelligence in commercial banking lending. However, it needs to be understood that lending is not the only department in commercial banking that will be impacted by the use of artificial intelligence. The impact of artificial intelligence is expected to be wide and is likely to impact several other departments as well.

In this article, we will have a look at areas where artificial intelligence is used in various departments within a commercial bank.

  1. Customer Service Robots: Artificial intelligence has started revolutionizing the field of customer service when it comes to commercial banking. Customer service has traditionally been a human-intensive, expensive, and difficult to manage department for any commercial bank. However, with the advent of artificial intelligence, this has changed.

    Commercial banks have studied the various patterns which exist in the field of commercial banking. Based on these patterns, they have used artificial intelligence to create software that can assist the customer and provide the same level of customer service as a human. The idea is to automate basic customer service tasks and deploy the services of humans only for the more difficult ones. Hence, over the next few years, artificial intelligence is likely to find large-scale applications in this department of commercial banks.

  2. Process Automation: The middle offices, as well as the back offices of commercial banks, are filled with mundane and repetitive processes which need to be undertaken. For instance, processes like check clearing and reconciliation are pretty straightforward and can be automated with the help of artificial intelligence.

    Over the years, technology has developed further and even more complex processes can now be automated. Most commercial banks have annual targets to increase the level of automation in their processes. This is the reason that commercial banks will heavily deploy artificial intelligence and related technologies in this domain.

  3. Pre-Approved Cross-Selling: Artificial intelligence has the ability to streamline the cross-selling process. Right now, the cross-selling process is a process with a very low hit rate and very large overheads. A lot of humans have to be employed to continually pitch the bank’s services to the customers. The conversion rate of this process is very less and hence the process is expensive.

    In the future, commercial banks are likely to spend a lot of money in order to incorporate artificial intelligence into cross-selling and automate the process. The bank’s system will study customer patterns and based on their behavior will select the bank’s products that can add more value to the customers. This system will be linked to the lending system as well and will make pre-approved offers to the customer which they will be able to avail at the click of a button. These features have already been introduced in personal banking. However, their large-scale deployment in commercial banking has not yet taken place.

  4. Reduce Frauds: Artificial intelligence-based systems are able to crunch data at a very fast speed. This means that they are able to quickly discern the normal operating pattern of a corporate and differentiate it from a fraudulent pattern.

    Commercial banks are likely to invest heavily in artificial intelligence-based technology so that they are able to provide better security to their customers.

    For instance, commercial banks can detect transactions that are initiated from computers located in different locations as compared to the ones which are normally used by the company. Also, commercial banks can use artificial intelligence to find better ways to confirm the identity of the customer before transactions are processed.

  5. Predictive Analytics: Commercial banks have decided to go beyond the traditional definition of vendors. They now want to become business partners for their corporations. One way to do so is by providing useful financial advice to their customers.

    Corporations generally share payments and receipts data with their banks. Hence, banks are aware of the cash flow situation of a corporation.

    Banks that use artificial intelligence can compare this cash flow situation to similar cash flow situations faced by other customers in the past and the financial vulnerabilities that they were exposed to. This helps them provide meaningful advice to their clients. This advisory service could prove to be a new source of revenue for commercial banks.

  6. Spend Analytics: Lastly, commercial banks can also help their customer corporations to maintain closer control over their spending. They can do so by using artificial intelligence to monitor the spending pattern of the corporation and by drawing reports which provide details about the ways in which expenditures have been incurred and the steps that can be taken to optimize these expenses. Many corporations find such reports to be extremely valuable since it helps draw their attention to the areas in their organization that need optimization.

The bottom line is that the field of artificial intelligence is going to have a deep impact on the commercial banking industry. Its impact will not be limited to a particular vertical or department of commercial banks. Instead, it is likely to transform the way in which commercial banking functions as a whole.

Article Written by

MSG Team

An insightful writer passionate about sharing expertise, trends, and tips, dedicated to inspiring and informing readers through engaging and thoughtful content.

Leave a reply

Your email address will not be published. Required fields are marked *

Related Articles

What are Corporate Credit Cards? – Different Types of Cards

MSG Team

Types of Risks in Commercial Banking

MSG Team

Commercial Banks and Branch Banking

MSG Team