Magic of AI in Banking

Banking has been so much easy nowadays, when compared to an old-traditional time consuming processes banks have found a lot more improvement. Technology should be thanked for this transformation, there are several factors that acted as pioneer in bringing technology and banking sector under the same roof. One of them are when Amazon company initiated the online e-commerce trend, the online payments started from there, the site Amazon.com inspired many such sites to evolve in market. Things from there started working to change the world to what it is today. Every online banking activity today which is instant yet secure has been possible because of the intellectual, tight, protective and proactive codes and algorithms supported by Artificial Intelligence.

Let us see the most risk sensitive factors of Banking to which AI is serving protection, stability and security.

Hassle free security services:

Several glitches could be seen in the Banking field, one of the most troublesome is the machine and technical glitch which will cause lot of inconvenience by stopping the flow of processes. Like for an example, cheques will be generally stopped from being issued if it contains error or if it is unapproachable, but some cheques will be abandoned by machines even if it is error-free, it will be stopped from reaching to the concerned party. This issue was a hassle to the banks as it was time consuming to verify each and every abandoned cheques. But now the issue is resolved by the programmed AI which will analyze abandoned cheques, if any of them are eligible to be passed, it will notify the respective bank official regarding the concern. Further actions will be taken by the bank management.

Fin-tech and banking sectors had another major issue which were underwriting and distribution issues. These two processes involves the rights upon the clients finance, if any one step is missed in calculation the client might have to lose their assests. Now AI has taken up its place in the field by managing to work as rule-based decision making, accuracy in predictions and having the sure shot information about the industries in the field, it provides the accurate suggestion of deal based upon the financial, personal, medical history of the client. AI underwriting is already included in many well known banks it isexpected to evolve much bigger to severe much more. 

Cyber crime and detection:

Cyber crime is a threat since the start of the internet, it is definitely not any non-introduced peril to the banking but AI is helping greatly regarding this matter. The algorithm of AI used in this case will pensively look upon the transactions of every customer by which it keeps a general transaction expectation from each customer. If the transaction varies even to slight abnormality the AI quickly catches such transaction, investigates about it and notifies the concerned people if it is required. 

Algorithmic trading:

The process of trading of offers which used to happen in the early days by the help of a middle man is now all digitalised, no more manual hustle is required. Algorithmic trading uses computer programs to trade at high speeds and volume based on a number of preset criteria, such as stock prices and specific market conditions. As an example, a trader might use algorithmic trading to execute orders rapidly when a certain stock reaches or falls below a specific price.

Credit risk:

Credit risk is an inevitable risk that has to be faced by every bank, this is the act in where banks will help their customers by crediting loans when required but the risk in here arises when the customers does not pay their debt, this is another crucial issue banks are scared of. This process is risky to handle because it is difficult to judge each customer if whether they are capable of paying back the debt or may not but, there is no more threat for the banking sector regarding this issue because AI's intelligent program has an absolute solution. The program of AI is designed in a way to cautiously look over the transaction limits of each customer to make a track limit of their regular income, expenditure, deals, shopping history and savings. If a customer seems to have a sustained source of income he/she will be offered for credit loans, such customers will also be allowed to various loans. The accounts that has unstable transactions will be listed separately to whom loan opportunities will not be offered easily. It will also be very vigilant regarding the track of transactions of an individual, if any irregular suspicious transaction is found it will instantly alert the concerned officials regarding it. Through this technology banks have been largely benefited in terms of security, intelligent alerts and accurate predictions. 

Business strategic risk and liquidity risk:

Banks must keep up their game in strategy of providing helpful and useful services to their customers, technology in bank will keep on evolving in various technical concepts. When a bank adapts an emerging technology other banks will be seen following the same, but the one that did it first will gain lots of attention and fame by customers hence it is important for the banks to keep up their game with useful technologies. Machine Learning along with the help of Big Data will help in this regard by keeping constant track of current market trend and will help to understand what is necessary to get updated. 

Liquidity risk in banking is the situation of not being able to pay the bills in mandatory and important places of business. This occurs when the bank doesn’t pay enough attention towards the outcomes of the investments and shares. Big data and its algorithms will keep the track of the finance, it could sense danger and predict the future of an investment. This way banks can always be updated and never fear of liquidity risk.

Relation with customers:

Since the era is of net banking, people expects most of the work to be settled online, even their issues and queries. Manually to solve the queries of customers will require an assistant to look after them, who may sometimes not understand the issue or may delay in solving. Chatbots are the technical solution for this problem, chatbots basically interacts directly by messaging the customers, since it if of machine learning it learns and evolves itself from the experience of interaction with the customers. It has natural language process ability which processes the general language of customers and understands the variety of it. It can conclude and understand the variety of it. It can conclude solution in the matter of seconds which saves the time of customers and keeps them updated of their issue. Maintaining a friendly relation with customers is important to every bank, chatbots promises to do it perfectly.

Learnbay based in Bangalore is one of the best place to study Artificial Intelligence and Data Science, because its course covers all the essential concepts of the subject, helps aspirants to effectively understand and practice the concepts. Learnbay teaming up with IBM is striving to flash the opportunity of effective and easily affordable courses to the technical aspirants.