Page 42 - Banking Finance December 2021

ARTICLE

intelligence models which learn by taking input from can be used to verify documents, Optical/Intelligent
several sources of variation in financial markets and Character recognition (OCR/ICR) technologies to digitise
sentiments about the entity to make investment scanned documents, and Natural Language Processing
decisions on the fly. Reports claim that more than 70% (NLP) to make sense of them.
of the trading today is actually carried out by automated
artificial intelligence systems. 7. Decision Making: AI can be of great use in areas where
decisions are based on available structured and
4. Fraud detection: Fraud detection is one of the fields unstructured data. For example, it can predict potential
which has received massive boost in providing accurate loan defaulters and offer risk mitigation strategies too.
and superior results with the intervention of artificial Another use is AI determine the best time to approach
intelligence. It's one of the key areas in banking sector a customer to sell a new product. AI based smart
where artificial intelligence systems have excelled the environments can collate data from multiple sources
most. Starting from the early example of successful and drive an inference and enable SMEs to take
implementation of data analysis techniques in the decisions. Also can improve straight-through using
banking industry is the FICO Falcon fraud assessment intelligent Automation to automate repetitive processes
system, which is based on a neural network shell to that need decision making.
deployment of sophisticated deep learning based
artificial intelligence systems today, fraud detection has 8. ATMs: Image/face recognition using real-time camera
come a long way and is expected to further grow in images and advanced AI techniques such as deep
coming years. learning can be used at ATMs to detect and prevent
frauds/crimes.
5. Customer recommendations: Recommendation
engines are a key contribution of artificial intelligence 9. Risk management and security: specially designed
in banking sector. It is based on using the data from the products can be given to clients by looking at historical
past about users and/ or various offerings from a bank data, doing risk analysis and eliminating human errors
like credit card plans, investment strategies, funds, etc. from man-made products. Suspicious behaviour logs
to make the most appropriate recommendation to the analysis and spurious emails can be tracked to prevent
user based on their preferences and the users' history. security breaches.
Recommendation engines have been very successful and
a key component in revenue growth accomplished by 10. Robots in banking: Artificial Intelligence humanoid
major banks in recent times. applications (Robots) can be used for customer
interactions at branches that reduces cost and increases
6. Digitisation of processes: Digitisation of KYC processes efficiency. "Lakshmi", India's first Robot launched by
eliminate the need for physical document submission City Union Bank can interact with customers.The other
and verification. AI based computer vision technology robots in Indian Banking industry are, IRA of HDFC Bank,
Mitra and Candy of Canara Bank. ICICI bank has
deployed Industrial 'robotic Arms' for note sorting at its
currency chests. Pepper isprobably the most popular
robot in the banking industry. The robot is able to
recognise human emotions and adjust to it. Pepper's
developer SoftBank uses this robot in 140 stores in
Japan. Pepper also works in restaurants, hotels, hospitals
and stores all around the world.

Artificial intelligence has transformed every aspect of the
banking process. AI technologies are making banking

42 | 2021 | DECEMBER | BANKING FINANCE