India
Axis Bank reaps benefits of data analytics in the cloud
Data analytics is a key driver of efficiency and customer experience for financial institutions, and Axis Bank has emerged as a leader in data-led transformation. Axis Bank—the third-largest private-sector bank in India with over 20 million customers and more than 4,500 extensive branches—uses big data and data analytics to boost profitability, manage risk, and improve operations. In response to a soaring demand for digital banking, Axis Bank has been able to deliver and transform banking experience for individuals and companies.
New digital services prompted a strong data culture
To stay competitive in today’s data-driven financial services environment, banks must take advantage of the vast amounts of data available at their disposal. As digital became the primary means of availing banking services for Indian customers, Axis Bank sought to expedite transformation to data-driven operations in order to address changing customer needs.
As a first step, Axis Bank needed to improve its ability to understand which data was required and what business problems it could solve using that data. Simply collecting, storing, and managing data would not have yielded the right results, and the bank knew that the data collected without an underlying strategy or business objective would not create any real value.
To meet these challenges, Axis Bank decided to start building a strong data culture that would replace past experience or gut feeling based decision making with one that is purely driven by data.
We believe in a ‘customer-first’ approach, and we aim to use this data for good,” said, Balaji Narayanamurthy, Head – Business Intelligence Unit at Axis Bank, about the bank’s ethos.
A robust hybrid data technology stack
A few years ago, Axis Bank began supporting its digital transformation journey, and realized that scalability challenges arise when an organization remains on-prem only. Although Axis Bank had moved some business applications to the cloud during the early part of the COVID-19 pandemic, the bank had difficulty integrating on-prem data with its cloud apps. Similarly, ad-hoc analysis requirements for machine learning and artificial intelligence teams couldn’t be facilitated by on-prem systems, which led to a longer lead time in provisioning necessary resources for data processing.
Axis Bank has since made significant investments in technology to securely meet today’s data-driven demands. In order to have an all-in-one solution for Axis Bank’s entire data lifecycle needs, Cloudera has proposed solutions on Cloudera Data Engineering, Cloudera Data Warehouse, and Cloudera Machine Learning to improve their multi-cloud flexibility, security compliance with SDX, and provide consistent experiences for on premises and public cloud.
Axis Bank’s core systems now collect application data, transaction-level data, and collections information across each customer’s lifetime, enabling the bank to generate insights for providing best services and products focused on enriching the customer’s banking experience.
The Cloudera cluster currently integrates and analyses 750 terabytes of data from several sources in Axis Bank’s systems, such as Oracle Exadata ED. The result is a strategy moulded from its huge database. Cloudera’s hybrid data platform solutions are well-suited to help Axis Bank align its data strategy with larger business objectives.
Success through personalisation
“Data mesh, AI models, real-time insights, and analytics on the cloud are some of the distinctive capabilities any analytics organisation should invest in to move from small wins to significant victories,” said Anish Parulekar, Head of Data Science at Axis Bank.
Axis Bank’s digital affinity is now demonstrated by the huge array of services (250+) offered on digital channels and with over one crore (more than 10 million) monthly users on the mobile application, making it one of the top-rated players in mobile banking.
Cloudera provides Axis Bank with a modern, multi-cloud data platform that enables the bank to analyse more than half its data and gain deeper business insights across its retail and commercial business units, including savings, lending, investment and exchange services.
Axis Bank’s move towards adopting a data mesh mindset will enable a new level of analytics. That includes, building alternate data platforms to enable score-based underwriting of a large cross section of lendable population, as well as more than 10,000 “nudges” developed and deployed via a custom cloud native serving layer to encourage customers to use additional services. The bank is deploying use cases across credit, fraud, and marketing analytics on a cloud decisioning platform that gives business teams’ self-service access to data. In addition, the bank has developed multiple machine learning-based credit models, which consider 2,000 different attributes and have achieved a more than 40% improvement in its custom credit score models over generic bureau models.
Axis Bank is now setting up a best-in-class personalisation engine to deliver a distinctive customer experience via two key capabilities—data and recommendation engine. Those capabilities take into account a number of data categories, including customer demographics, nature of customer interaction with the bank, the banking products and services they use, and information provided by ML models.
