Disadvantages of Artificial Intelligence in Commercial Banking

In the previous articles, we have already seen what artificial intelligence is and how it can be applied in commercial banking. We are also aware of the various advantages of artificial intelligence. These various advantages are the main reason that artificial intelligence is being adopted by commercial banks all over the world at a breakneck speed.

Multinational banks as well as regional banks have all introduced some sort of a program that is aimed at incorporating artificial intelligence in a large part of their operations. As a result, hundreds of billions of dollars are now being spent with the aim of creating an artificial intelligence-based future-ready banking system.

However, it would be naive to believe that artificial intelligence provides only benefits and that there are no disadvantages associated with it. In this article, we will have a closer look at the various disadvantages of artificial intelligence in commercial banking as well as their impact on the overall banking system.

1. Expensive: Artificial intelligence is a very expensive technology to implement! It needs to be understood that right now, technology is at a nascent stage. Hence, it is considered to be a rare commodity in the technology space. There are very few vendors who can enable banks to use these technologies. However, among these vendors as well, there are very few which are capable enough to execute large-scale transformations.

   Since the technology is futuristic as of now, the products and the personnel which are associated with it come at a premium.

   Banks that have tried to implement artificial intelligence have had to invest billions of dollars upfront. Also, since the personnel which can enable the development and maintenance of these systems are in short supply, banks have to hire this personnel at very high salaries. As a result, banks that are implementing artificial intelligence are actually losing money in the short run. However, they are still continuing with their investments since they believe that the technology will place them in a superior position in the market in the near future and all their investments will pay off.

   The high expenses make artificial intelligence an unviable technology for smaller commercial banks as of now. They will have to wait for a few more years so that the technology becomes more commoditized and hence more affordable for them.

2. High Cost of Error: Not only is artificial intelligence very expensive to implement, but the cost of errors made by it can also be very large. This is particularly true for the field of commercial banking.

   Commercial banking loans often have a ticket size of millions of dollars. In the current process, these loans are carefully evaluated by humans, and systems are used as an ancillary tool. With the advent of commercial banking, this situation is likely to be reversed. Hence, systems will play a major role and humans will play the ancillary role. Therefore, if the system makes an error like disbursing a loan to a counterparty that is not creditworthy, the consequences will have to be borne by banks. To overcome this issue, commercial banks are first implementing this technology in areas where the ticket size is small. This will enable them to implement the technology in a more controlled manner.

3. Reduced Loyalty: At the present moment, commercial banking systems are based on human networking. Companies do not necessarily take loans from the bank which offers them the cheapest finance. Instead, companies take loans from banks that they consider to be a business partner and have good working relationships with. Relationship banking plays a large part in this process.

   At the present moment, commercial banks witness a large loyalty from their customers. However, with the advent of commercial banking, this loyalty is likely to be decreased. Commercial banks will end up commoditizing their services. This is because if there is no human connection involved, then there is no differentiating factor for a commercial bank. Corporations will be encouraged to look at commercial banking in a commoditized manner.

4. Unemployment: Commercial banks are planning to implement artificial intelligence on a large scale. This means that a lot of the tasks which are currently done by humans are likely to be automated. The end result would be that banks will require a lot less human workforce. This means that banks will not replace retiring employees and will have fewer recruitment drives. This also means that a large number of workers are likely to face early retirements or even layoffs. This could create discontent amongst the employees of major commercial banks leading to productivity losses which will partially offset the gains created by the technological advancement.

5. Opaque: Lastly, artificial intelligence-based systems are made out of deep neural networks. They take data from a wide variety of sources. The sources of their data as well as the process is undertaken to arrive at a decision can be quite complex and may not be completely transparent to a layperson. Hence, the end result is that some of the decisions made by the system are incomprehensible to humans.

   For instance, the system may deny a loan to a long-time customer of a commercial bank and the reasons may not be easy to decipher. This opacity could create problems in the day-to-day operations of the commercial bank.

The fact of the matter is that artificial intelligence will be implemented in commercial banks on a large scale. Hence, individual commercial banks also have to follow the trend. However, it is important for them to understand that artificial intelligence can also have several disadvantages. Any proposed gains should be measured against the possibility of losses before steps are taken to roll out this technology on a large scale.