Digitalisation in banks started in the 1980s with the need to improve services and record-keeping. Initially, banks used “personal computers”, which were new at the time. Later, they introduced Local Area Networks (LAN) to connect multiple computers for better communication.

However, in the 1990s, India's economy opened up, and several private and foreign banks entered the market. This increased competition within the banking industry, and to stay competitive, Indian domestic banks started increasing their computerisation efforts.

Eventually, they moved to “Core Banking Solutions (CBS)”, which made it easier to perform day-to-day operations such as opening accounts, processing loans, and handling cash deposits and withdrawals. Notably, CBS also allowed to do “branch banking” and provided round-the-clock access to banking services. Using it, customers could now do "Anywhere and Anytime Banking".

In this article, let’s better understand the concept of digitalisation in banks and see how these institutions have progressed over the years.

• In the 1980s, Indian banks started getting digitalised through the use of basic personal computers.
• Gradually, they first shifted to LAN and then to more advanced technology like Core Banking Solutions (CBS).
• The Indian government is also promoting digitalisation in banks through initiatives like UPI and BHIM.
• Nowadays, banks are implementing AI and data analytics in their operations.
• This implementation allows them to offer more personalised services and reduces their operational costs.

Over the years, Indian banks have adopted newer technologies which have made banking more user-friendly for customers. For banks, “e-banking” has specifically reduced operational costs and expanded customer bases. Moreover, digitisation in banks has also minimised human errors. Below are some key technological advancements that have been adopted by Indian banks:

• MICR cheque processing
  This technique enhances the security and validity of cheques. It uses Magnetic Ink Character Recognition (MICR) technology.
• Electronic fund transfers
  Allows customers to transfer money between accounts without visiting the bank.
• ATM channel
  Enables customers to perform transactions anywhere without needing to visit the bank branch.
• Branch interconnectivity
  It refers to a common software that connects bank branches. Such an interconnectivity improves decision-making and access to data.
• Payment system strengthening
  Central Bank initiatives have improved the security and efficiency of payment and settlement systems.

The Indian government is actively promoting digitisation in banks. Initiatives like the Unified Payments Interface (UPI) and Bharat Interface for Money (BHIM) have significantly transformed the banking system.

For the unaware, UPI allows users to transfer money instantly without repeatedly entering bank details, while BHIM offers a cost-effective way of making payments. These innovations are also reducing the reliance of people on cash and helping India become a cashless economy.

In addition to UPI and BHIM, several other electronic payment systems have become common across India. Some common examples are NEFT, RTGS, mobile banking, and card-based payments.

Furthermore, many banks are also introducing new features to attract more customers. This not only boosts their revenue but also simplifies banking for customers. Now, with more ATMs and digital tools available, we can say that Indian banking has become more accessible and user-friendly.

Artificial Intelligence (AI) and Data Analytics are the latest techniques that are helping banks improve their customer experiences and even improve profitability by managing risk. Also, these technologies allow banks to offer personalised services and manage data safely.

For more clarity, check out certain key benefits of AI and Data Analytics:

• AI provides tailored services and customer support. It enhances user experiences.
• AI reduces operational costs by automating tasks. This saves time and resources.
• AI helps banks minimise risks by analysing data to predict fraud or bad loans.
• Data analytics processes large amounts of data in real time.
• This improves decision-making and overall financial performance.
• Data Analytics helps banks to strategically manage priority sector loans (agriculture, housing, education).
• By performing deep data analyses, several banks have successfully reduced their costs and expanded customer bases.

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