Artificial Intelligence in Banking

Giving brain to machines running on artificial power makes artificial intelligence. In the present scenario AI is the most needed technology where direct human intervention is less required and making us safe. If machines are able to think and make decisions as humans do then it is possible to replace humans with machines. AI is opening new doors towards converting the works done by Nurses, ticketing staff, protection force etc into machines, which are programmed accordingly and the fact is that it is already in use. The world is shrinking under AI or controlled by AI.

Some of the common technologies in which AI used are:

  • Tesla driverless car- uses AI for lane centring, cruise control, parking, lane changes, semi-autonomous navigation on limited access free-ways, and the ability to summon the car from a garage or parking spot.

  • Siri- a virtual assistant used in Apple devices which uses voice and natural language processing to give output

  • Robotic surgery- a new technology which uses robots for doing surgery. Used especially when doctors are out of station and they can do the surgery from outstations using online media.

  • Alexa- virtual assistant AI technology developed by Amazon and it is first used in echo smart speakers which can recognise sound and act accordingly.

Artificial Intelligence technology can be used in any segment of life or industry provided digital data is available. The data can be of any form like,

  • Real time sensor data- AI uses these data mainly in agriculture, water level management, industry where sensor data is collected used for making decisions.

  • Maintenance data- data needed for maintenance is used by AI

  • Historical data- for predicting future it needed to study the previous history. AI uses historical data in future prediction eg. Climate, rain etc..

The main components used in AI are Machine learning, Natural Language Processing, Speech, Vision.

Understanding customers is the tedious task in marketing today. Understanding customer needs means what is the propensity of a customer in buying next best product. Analyzing the customer nature and recommending the right product at right time through right channel is the success of marketing. Analyzing a customer and sending appropriate content is the major task. By analyzing many factors like previous buying pattern, searching pattern and so on it can be understood that on what a particular person is interested in. So accordingly messages are send or calls are made.

While considering AI it is always suggested to go for big platforms and develop models instead of working on bits and pieces. Machine learning solutions are mainly used for understanding customers.

Banks know more about you than you know yourself!!!

Banking is the major sector which uses AI for attracting customers. Once a person is registered with any of the fin tech company eg. Paytm, banks will acquire that person’s data from the user profile. Using that data, banks will predict the user needs and expenses using AI.

Now a days almost every bank is providing their banking apps where it provides their customers with easy banking transactions. But there are many other factors hidden in that. Have you ever noticed when you are reaching a place automatically you will be receiving messages indicating nearby hotels, restaurants, picnic places, hospital, banks etc. How it is done? Through the banking app which you are having the bank will identify your location, and that bank will be having a tie up all these hotels, restaurants, picnic places, hospital and banks will offer you a discounted rate also. This makes customers happy with their bank.

Similarly banks are well known about their customer income, expenses, balance etc and based on that, using AI they will give intimation about the loans which they can provide to a particular customer. Based on the previous customer searches also banks will predict what the person needed and accordingly the customer will get calls or messages.

Another area where banks are concentrating is to provide personalized customer service using AI. The moment a customer call to a banking executive the complete details of that particular customer will be available in the screen in from of the executive. It is done by using the customer phone number. So the customer can directly start speaking on the issue on which he made call instead of self introduction. The service executive can even provide suggestions on any other matters to the customer as a family friend making the customer more closer and trustful.

ATM cash optimization:

Neural networks and K-means are used to analyse which ATM is consuming how much amount of money in a particular time period. This will reduce the cost of interest in the returned cash at the time of loading cash in machine. Salary day, Sunday, weekend, holiday, location, frequency of withdrawal are taken into consideration and prediction is made on how much cash should be loaded in a particular machine. Similarly denomination to be loaded is also predicted based on the location of ATM. If the ATM is in a college the denomination will be 100s whereas in a shopping mall it will be 2000s.

Recognition of customers:

Using CCTV images in branches of bank all the people entering are noticed. If a person who is black listed is entering the bank immediately the bank manager will get a notification and can inform the banking personnel to deal that person accordingly. Similarly if a preferred customer is entering the manager will get alert and can treat that person specially.

Post covid-19 cost rationalization using AI:

Decisions like cutting down employees and no intake for next two quarters and all will ruin the company name and position. AI can be used for predicting and giving solutions on which all areas of an industry are beneficial and which all areas are loss. Based on that prediction the intake of employees can be made, the input to beneficial areas can be increased.

Artificial intelligence is an upcoming stream with lot of possibilities. Python and R are the programming languages mainly used. On top of big data if these languages are used it is AI.