Page 27 - Banking Finance April 2022

ARTICLE

various sources in one central location. CDPs help banks technology. Indian banks are no exception. These banks are
in achieving a single customer view, which means that applying AI for both retail customers needing a common
a customer's details such as transactional data, solution as well as corporate customers having specific
behavioural data, etc. are all made available in one requirements. AI is being employed across the following
place. Once the bank is able to fully understand a divisions:
customer, giving what he is looking for, the next course Branch Operation - Account-setup process involves client
of action is to offer personalised products and services. data being entered in a number of systems. This can be done
by a software robot equipped with Artificial Intelligence.
2. Significant profits - AI will boost staff productivity by
empowering them to delegate low value-added tasks Lending Decisions - AI-powered credit scoring tools help in
to AI and be more productive in their core tasks. This speeding up lending decisions, while limiting incremental
will help in increasing profit of the bank. risk. It also helps in preparing a credit report and drafting
3. Unique omnichannel experiences - Omnichannel legal documents.
experience is one that connects customers through all ATM Reconciliation - AI tools help in reconciliation where
methods of communication and interaction, this could balances are settled between different banks and their ATM
be texting, messaging, phone calls, emails, and apps. networks, when one bank customer uses another bank's
This can be made possible with the help of AI ATM.
technologies. Treasury - Predicting the possible direction of bond market

4. Innovation - In a time of increasing digitalization, based on historical data can be possible with the help of AI
artificial intelligence has become relevant for tools.
innovation. AI offers the possibility of simplifying certain Management of Funds - AI tools are being used for more
innovation tasks, making them more efficient with
data driven, parameters-set trading for wealth management
additional information. Algorithms and ever-increasing clients.
amounts of data allow better analysis, more precise
forecasting and decision-making with less risk. AI has Management of Fraud - AI tools are playing pivotal role in
the potential to significantly improve innovation preventing identity theft, money laundering using deposits
management or even replace human innovation teams or loan fraud.
with machines and robots. Regulatory compliance - To assist bank employees, who
may not know the entire set of rules and regulations the
RBI has for banks. Automating basic rules for determining
client classification type using Artificial Intelligence for
regulatory norms such as KYC, FATCA, etc.

As per a report by McKinney, the most
commonly used AI technologies in the banking
sector are:
Robotic Process Automation (RPA) - (36 percent) for
structured operational tasks.
Virtual Assistants - (32 percent) for customer service
divisions.
Banks are required to make AI central to their core strategy Machine Learning (ML) techniques - (25 percent) to detect
and operations, otherwise will be at risk to be overtaken by fraud and support underwriting and risk management.
competition and abandoned by their customers.
AI Use Cases AI Application in Financial Services
Globally, banking industry is the biggest consumers of 1. Machine Learning (ML)- ML works on computer
technology and among the fastest adopters of new algorithms that improve automatically through

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