Artificial Intelligence (AI) is a term coined in 1956 during a workshop conducted on the campus of Dartmouth College. Many of the attendees predicted that a technology which will create a machine as intelligent as human being would soon come into existence. But because of the hardware limitations, it was not possible at that time. But with latest technology and hardware, now it is possible to research and implement the artificial intelligence technology which enables the machines to learn from experience and perform human-like tasks. AI enables the machines to adjust to new inputs and develop responses for new questions. It has lesser chances of making mistakes which is a great point of advantage for organizations and allows them to rely on AI to build smart and efficient processes, simplify complex operations and create unified experiences. It is very convenient to use to perform the repetitive, tedious tasks improving efficiency of the jobs. Moreover, it can work for hours and days on the same repetitive task and still wouldn’t get bored or won’t need breaks ensuring a 24*7 work.
Using AI, the machines are able to process and analyse large amounts of data at an expedited level. This immense speed in processing data is nowadays used by financial services firms to bring efficiency to the system. AI reduces the redundant activities such as transaction processing, auditing and compliance for the financial professionals. AI can also be used by financial regulators to improve regulatory compliance and increase supervisory effectiveness reducing the possible issues and frauds.
Many financial firms are now training the algorithms using tonnes of data with information like job, salary, financial spend history, status, habits etc. to perform the customer underwriting. This has shortened the lending and borrowing procedures which have ultimately made the quick availability of loans possible for the customers. AI is being used by organizations for detection of trends which will influence the financial activities in future. The heightened and quicker customer support through the chatbots and other conversational interfaces is another use-case of AI which improves customer services and hence customer satisfaction.
However, the recent World Economic Forum report suggests that AI might destabilize the Financial System by introducing more risks and weaknesses into the system. To include and implement the latest technologies in the operations, the financial services firms need to partner with the big technology players and share the financial data with them resulting into more number people handling the consumer financial data which increases the risks of misuse of the data. Even the chatbots developed for quick and flawless customer support sometimes cannot pinpoint the consumer problems or face some new type of query for which the machine algorithm is not trained.
The implementation of AI where everything is about the network, need more networked and connected back office where zillions of data is stored. This definitely gives rise to cyber-security risks and the concentration risks. The system’s complexity is one major reason for these risks which gives major power to the one who understands it. The world has also witnessed the negative effects of the automated high frequency trading. The Flash Crash of the British Pound and the Black Swan events are the proof of the same.
These loopholes prove that technology is still far from perfection giving rise to the next inevitable question, would it ever become self-reliable? Only the time can tell the answer to this question but the scientists and technology leaders will definitely continue working to make machines more intelligent.