Public sector banks would do well to adopt new digital technologies
Indian banks don’t seem to be leveraging the technologies that are making global companies reap heavy advantages from the nation’s markets
Prime Minister Narendra Modi recently inaugurated 75 Digital Bank Units (DBUs) to mark 75 years of Independence. These brick-and-mortar digital banks, one each in 75 districts of India, aimsto take the benefits of digital banking to every part of the country – all states and Union Territories.
The initiative is seeing the participation of 11 public, 12 private, and small finance sector banks. These banks will offer customers regular banking services such as the opening of savings and fixed deposit accounts, transfer of funds, processing the applications for debit and credit cards, loan applications, and stop payment instructions.
While these services, adopted on a larger scale, can help a great number of bank customers in rural areas, Indian banks are still far behind in the adoption of new digital technologies including artificial intelligence and big data analytics.
Indian public sector banks, in particular, are still not leveraging these technologies as fintech companies and startups are doing. They need to catch up quickly.
According to another recent news report, Indian public sector banks (PSB) are planning to create specialised verticals for big data and analytics in a push for more data-driven decision-making. They are also planning to launch digital-only goods and services. These will have minimal data entry requirements automated checks, etc., and will be available to individual consumers and small and medium-sized businesses. PSBs’ renewed push for data-driven banking comes in the wake of the government pushing a reform agenda.
While PSBs are still following the old model of banking with a graded introduction of digital banking solutions, private sector financial institutions and Fintech startups are offering digital-only banking services and digital banking solutions for value chain financing.
The decision of PSBs to integrate big data capabilities and data-driven decision-making will help speed up the detection and mitigation of fraud.
Digital banking aims to automate the entire process of payments and day-to-day transactions from onboarding to delivery. For banking, a lot has changed over the recent decades. While PSBs may still be using the legacy software platform, private sector digitalised banking systems are using cloud-based agile technologies with effective monitoring and ongoing innovations.
It will be a wasteful idea to let PSBs continue with old banking practices. By creating separate verticals for big data and analytics, PSBs can offer better customer experience, more personalised services, and increased efficiency.
It can help them: Know the demographics of their customers, save the cost of customer acquisition, fulfillment of seasonal demand, data analytics is cost-effective, can keep an eye on competitors, and help in innovation.
Big data has great promise in the evolution of new-age banking. Security is a major focus area for all banks and financial institutions. Big data analytics can help banks prevent fraud and cybercrime. It can help identify suspicious and illegal activities from mountains of data.
Data forensic tools powered by big data analytics can provide real-time alerts of suspicious transactions. It can also help streamline data management and provide improved reporting and compliance. Banks can use big data analytics to figure out outstanding features of customers purchasing activities and anticipate their needs. It can help them target customers with personalized offers and meet their expectations.
Big data analytics can play a significant role for banks to stay ahead of the competition. Customer segmentation is a standard practice in almost all businesses. But data analytics can help further classify customers with more specific profiles. It makes it easier to reach customers with products and services that they may precisely be looking for.
The precise nature of insights through in-depth analysis of big data can help them in upselling and cross-selling. Feedback provides insights into customers' overall sentiments toward the banks and their products and services. They also reveal strengths and weaknesses. With data analytics, these disclosures can help banks identify new areas of growth. They can help tailor a more precise response to available opportunities.
Banks generate a great deal of data but Indian public sector banks, in particular, don’t use big data to their full advantage. By creating separate verticals for big data and analytics, they can transform into new-age banks with data-driven decision-making in place.
Given this background, Indian banks don’t seem to be leveraging the technologies that are making global companies reap heavy advantages from the Indian markets.
By putting user-generated data to use, companies like Facebook and Twitter are generating billions of dollars of revenue from the Indian market. These companies are able to use big data even when it comes to leveraging banking infrastructure created by Indian banking and financial institutions.
For example, the UPI that is often touted by the Indian government as a game-changer in digital banking and electronic payments system is used by Google Pay and Amazon pay.
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