After the financial meltdown and the ongoing splurge of FinTech firms, it is understood that there is no run-of-the-mill approach that will work for banks and financial institutions across the world to increase their business market share. Instead, a continuous transformative journey, from an account-centric to a customer-centric approach is the need of the hour. Such a journey is only possible through deep analysis of constantly generating huge collection of structured and unstructured data (termed as Big Data) from various sources including customer touch points (like Branch, ATM, Call Centers, Online), social media, IoT sensors and financial feeds (like regulatory, events, news).

The banking industry has an advantage of more consumer data at their disposal than most other businesses. By establishing analytics as a true business discipline, banks can unravel enormous business potential. Analytics is helping banking industry becoming smarter in managing various challenges it faces. While basic reporting and description analytics continue to remain a must-have for banks, advanced predictive and prescriptive analytics are now starting to generate meaningful & powerful insights, resulting in a significant business impact.

As consumers embraced digital channels for commerce and communication, banks were among the first businesses across industries to take advantage of streams of customer data. Unfortunately, despite the vast amount of data available, the early start and formidable resources, most banks are far from realizing big data’s full potential.

Need for Business Analytics

Customers are becoming smarter

Nowadays, the customer (both consumers and businesses) are well informed and expect complete, transparent and relevant information from their banks. Customers often complain of receiving little assistance from their banks in their daily financial life despite ever increasing expectations. On the other side, banks struggle to increase customer loyalty and stay relevant, while maintaining a healthy level of customer engagement & conversion. The bank that leads the market will be the one having deep insights into customer likes, dislikes, preferences and offers products and services complementing customer’s need. Banks need to keep their customers engaged at every stage of their banking journey, not just to convert immediate opportunities to sales, but because two-thirds of the decisions customers take are driven by the quality of their experiences all along their journey.

Redefined banking through centralized data

Gone are the days when brick and mortar branch was one-stop-shop for the customer’s all banking needs. In those days, branch staff used to maintain personal touch by having a complete 360-degree view of customer’s relationship at their fingertips. However, with the centralization of data and multiple channels available serving customer’s banking needs, the personalized touch has gone down. Today’s banking environment is highly competitive with each bank launching variety of products and services. In such a competitive environment, it is crucial for banks to leverage this centralized data to their advantage.

Economic pressure

Banks across many different regions are under enormous economic pressure. Due to this, banks are trying many ways of improvements, especially through digitization and cost cutting. While these steps have marginally improved the bottom line for banks, something more refined is needed. Efforts put in for digitization underlie the need for pushing analytics. Most of a typical bank is now digitized and generating humongous customer data. While mostly manual bank would have serious difficulty using advanced analytics, for digital banks the highways are already paved for kickstarting analytics-driven journey.

Advances in technologies & availability of information

In the past few years, the amount of meaningful data generated has grown exponentially, while the size and cost of processing units decreased. One of the most interesting advances in technology is Internet of Things (IoT) enabling integration between various smart devices to communicate and share information in real time. IoT sensors can leverage the capabilities of big data, analytics and even artificial intelligence to anticipate needs, solve problems and improve efficiency. While not fully defined as of yet, there will be significant applications of IoT in financial services.

Providing actionable data insights

It is imperative that just having access to data and the ability to process this insight is not enough. Consumers expect their banks to be able to provide real-time inputs and recommendations based on changes in their financial profile. This essentially includes enhancing the ability to save money, achieve relevant financial goals, better budget spending, etc. The key aspect missing at many banks is to utilize data that currently resides in reports and analysis, and use it directly for the benefit of the consumer. There is a need to have integration and synchronization of data sources, enabling real-time determination of relevant data points for analysis, communication and decision making.

Fraud detection

Prevention and detection of fraud can be facilitated by analyzing transactional data on real-time basis against a set of known patterns. Analytics can help establish a correlation between data from multiple sources to determine fraud events. Modern machine learning algorithms can learn and keep track of customer behaviors and devices enabling early identification of fraud.

Potential benefits of analytics

  • Customers get benefit from a more personalized, contextual and relevant banking experience with recommendations directly contributing to improving their finances
  • Enables bank to boost customer satisfaction with increased engagement and usage of products & services. It also improves the effectiveness of marketing communications by delivering contextual and actionable content to its customers.
  • Enables bank to better understand consumer behavior and responding to changes in consumer taste quicker
  • Improved product design and optimization of product portfolio
  • Compliance with regulatory requirements and real-time track of fraudulent events

Way Forward

Use of sophisticated predictive and prescriptive analytics can help enhance customers’ experience in both consumer and business banking, thus improving banks profitability and competitiveness. Need for differentiated services, regulatory compliance, fraud detection, personalized cross-sell and up-sell initiatives and contextual omnichannel experience are on the rise for bank’s sustainable growth. Advanced data analytics plays an instrumental role in ensuring that these strategies are properly executed.

To sum up, the potential benefit of business analytics for banks lies in maintaining data reservoirs from various sources for a complete 360-degree view of a customer and making smart use of it to retain customer while increasing business profitability.

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2 thoughts on “Transforming banking the analytics way

  • Very well articulated!

  • The blog truly articulates benefits of analytics quite well and as rightly stated, the way forward depends on data maintenance. And this is where the problem lies. Most banks today are slaves of the data collection process and not masters of it. Silos based infrastructure often hampers smooth flow of data. It should be possible to pull structured data from all channels efficiently with efforts to minimize redundancy. Sources of unstructured data should also be correctly identified so as to optimize data aggregation efforts.

    Regulatory and budget constraints add fuel to fire. The question of data privacy and security is of utmost importance. Compliance with regulatory mandates require a firm management of data lifecycle. Approvals are required not only from regulators but also from customers for data mining purposes. Secondly, there is a significant cost associated with analytics in form of incremental hardware costs and salaries of data scientists. The return on investment is not immediate and requires patience.

    But if banks perform an honest cost-benefit analysis, I am sure that benefits with analytics outweigh the costs.

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