Digital transformation is impacting businesses far and wide, but you could argue that none are being impacted more dramatically than banking. Over the course of the past few decades the manner in which banks interact with their customers has changed significantly, and more changes are on the horizon.
How has banking changed?
The first bank account I had was a passbook savings account when I was very young. The bank gave me a little booklet where my banking activity was recorded. Whenever I wanted to make a deposit or a withdrawal I took my little booklet to the bank where the teller recorded the transaction in the booklet. No booklet, no transaction.
No bank today could get away with such a requirement! These days, I almost never write a check myself anymore, instead I pay my bills online through the bank’s web portal. If I want money I go to the ATM. And with my mobile banking app I can check my balance any time of the day or night[1]… and even take a picture of a check to deposit it into my account. I don’t even need to give the check to the bank to deposit it.
Those are substantial changes. My young self would not recognize many banking transactions today.
But the transformation continues. Even the inside of the bank is being modified to enable more automated transactions. How so? Well, I usually go inside the bank to a teller to deposit larger checks. For some reason, I just cannot get used to taking a picture of a large check or just pushing it into an ATM. But banks are working to change even this relatively uncommon activity. Recently, I went into the lobby of one my bank’s local branches to deposit a check. But things had changed. There was a grandiose ATM with a bank employee there to guide people to the ATM instead of going to a teller.
This seems to be working, since U.S. News & World Report’s number one banking trend for 2016 is that “fewer people will head to branches.”[2] How does this impact IT? Of course, automated IT processes are necessary to drive the customer interfaces to the ATM and the online banking portals. All of which must be maintained and improved as new techniques arise. For example, an entire different set of expectations and interfaces are demanded for mobile banking than for internet banking. And likewise for internet banking over traditional banking. But each method of interaction relies on the crown jewels of data that mostly reside on z Systems mainframe computers. So banks frequently need to deploy mainframe modernization solutions that preserve the existing mainframe heritage while exposing it to modern interfaces.
Furthermore, as the local branch becomes unnecessary, the way in which customers interact with the bank fundamentally changes. It becomes easier for customers to switch to another bank if everything can be done online. Indeed, according to Accenture Consulting’s recent North American Consumer Digital Banking Survey[3], millennials switch from their primary bank at a pace nearly double the average of other consumer groups. 18% of millennials switched their primary bank within the past 12 months.
Given this shift, which banks have encouraged to reduce cost and streamline processes, a different way of interacting with their customers is required. Part of this is to make the banking experience as seamless and as simple as possible. This is done with compelling technology and features. The other part of it is to better understand customers’ needs and behavior patterns. And that requires analytics. But what is analytics?
Advanced analytics is a business-focused approach, comprising techniques that help build models and simulations to create scenarios, understand realities, and predict future states. Advanced analytics utilizes data mining, predictive analytics, applied analytics, statistics, and other approaches to allow organizations to improve their business performance.
Encompassing a wide range of applications, from operational applications to strategic analysis (such as customer segmentation), advanced analytics goes deeper than traditional business intelligence activities. It works on uncovering the “why” of the situation, and delivers likely outcomes. By allowing business managers to be aware of likely outcomes, advanced analytics can help to improve business decision making with an understanding of the effect those decisions may have in the near future.
Analytics are often discussed in the context of big data because patterns and behaviors can be difficult to uncover when using traditional methods on large data sets. As data complexity and volumes grow[4], so does the cost of managing the data and building analytic models. Before real modeling can happen, organizations with large data volumes face the major challenge of getting their data into a form from which they can extract real business information. One of the most time-consuming steps of analytic development is preparing the data. In many cases, data is extracted, and a subset of this data is used to create the analytic dataset where these subsets are joined together, merged, aggregated, and transformed. Appropriate tools for extraction, transforming and loading the data are required. As are different new data analysis and storage tools such as Spark, Hadoop, R, and others. But they all need to work in conjunction with the most important data in the bank—and that typically resides on the mainframe.
How will banking continue to change?
Another significant banking trend, touted by The Financial Brand[5], is the “platformification” of banking. The general notion here is that banking and financial technology (FinTech) companies have many complementary points of synergy. Instead of being competitors, the predicted trend is that more banks will partner with FinTech companies to deliver a cohesive platform for banking and financial services to their customers. The goal would be to create platforms for banking in much the same way that Amazon is a platform for retail goods.
For this to come to fruition, the new platform must be able to leverage banks’ legacy systems that deliver high-speed, properly secured transactions, along with the modern interfaces for mobile computing that today’s banking consumer expects. To achieve successful integration of these techniques requires new tools, skills, and technologies.
In the same report from The Financial Brand, the number three trend uncovered is “Making Big Data Actionable.” Being able to not just collect and maintain large amounts of data, but also to be capable of leveraging that data to understand and better serve consumers, can be an important differentiator when trying to build new relationships or to bolster existing ones. This gets back to the need for financial institutions to improve their advanced analytics capabilities.
Putting the customer at the center of everything in terms of data collection and analysis is an important step for achieving customer loyalty. A financial institution (or platform) must be able to access data about all customer interaction points (branch, website, mobile, phone). The data should be integrated and accessible for analytics to better understand the customer and deliver services that match his or her desires and requirements.
But reality lags behind the need. According to a consumer banking survey conducted by NGDATA[6] only 20 percent of banking customers are very confident that their bank understands them. This must change to improve customer loyalty, which is needed because the same survey reports that more than 47 percent of customers are not very loyal to their existing bank.
Looking a bit past the immediate year, the Accenture Consulting North American Consumer Digital Banking Survey[7] is informative about trends that could shape the future of banking. One key point addressed by the survey is that customers see banks as transaction processors, not as providers of information or advice. The survey results indicate that “customers will expect banks to be intuitive, intelligent and individual.” To transform from transaction processor to trusted advisor requires the information that can be gleaned from advanced analytics on big data sets. Until banks can deliver on this requirement, customers will likely continue to view them just as transaction processors.
This transformation needs to be done with a firm understanding of the security and privacy rights that customers expect for their important financial records. The good news is that 86 percent of banking customers trust their bank to securely manage their data. But banks cannot take their eye off the ball. The level of trust that exists between banks and their customers is a big plus that needs to be maintained. As banks continue to open up their mainframe systems—traditionally well-protected and secured—to more open platforms, care must be taken to ensure that mainframe-quality, security and privacy practices continue to be deployed.
And finally, an Ernst & Young[8] study with the purpose of “Building the Bank of 2030” identified some interesting trends that somewhat fly in the face of the current trends. For example, although current trends show an increase in millennials and their reliance on newer, usually mobile technology, this study indicates that different demographics will drive the future of banking. Specifically, there will be eight billion global inhabitants that are older and more urban. That means that banks will need to be sure that they are capable of effectively serving an aging, and increasingly urban, demographic. Of course, this aligns with some of the earlier trends discussed here, such as increasing reliance on internet banking, so long as the urban area has reasonable internet connectivity.
Synopsis
Perhaps it is a trite cliché, but the only constant is change. Banks must be adaptable, with the capability to serve new customer requirements while at the same time meeting the exacting demands of the customers they have served for ages. This means finding ways to integrate the new with the tried and true.
Mainframes drive the banking industry and they will continue to do so well into the future. But what a mainframe is has changed too, … and they will continue to morph and add new features and new technology advancements along with it. That means that banks can continue to rely on the decades of investment and reams of data stored in their mainframe systems. And that new technologies can be married to those systems to ensure that the data is accessible, optimized for quick access, and properly secured.
Understanding all this can help to ensure that your bank will be prepared today and into the future to meet the challenges of modern IT systems.
[1] According to Board of Governors of the Federal Reserve System’s report, Consumers and Mobile Financial Services 2015, “The most common use of mobile banking is to check account balances or recent transactions (94 percent of mobile banking users).” www.federalreserve.gov/econresdata/consumers-and-mobile-financial-services-report-201503.pdf
[2] LaPonsie, Maryalene. “10 Banking Trends for 2016.” U.S. New and World Report, January 7, 2016. https://money.usnews.com/money/personal-finance/articles/2016-01-07/10-banking-trends-for-2016
[3] North America Consumer Digital Banking Survey 2015, “Four consumer banking trends show new future of banking.” www.accenture.com/us-en/insight-trends-banking-consumer-future
[4] According to a CSC study, the annual amount of data being generated will increase by 4300% during the existing decade (ending 2020).
[5] Marous, Jim, “Top 10 Banking Trends and Predications for 2016.” The Financial Brand, December 21, 2015: https://thefinancialbrand.com/55952/2016-top-banking-trends-predictions-forecast-digital-fintech/
[6] NGDATA Consumer Banking Survey. www.ngdata.com/resources/guide-ngdata-2014-consumer-banking-survey/
[7] North America Consumer Digital Banking Survey 2015, “Four consumer banking trends show new future of banking.” www.accenture.com/us-en/insight-trends-banking-consumer-future
[8] Ernst & Young, Building the bank of 2030: top eight global trends. www.ey.com/GL/en/Industries/Financial-Services/Banking—Capital-Markets/8-trends-shaping-the-bank-of-2030
Regular Planet Mainframe Blog Contributor
Craig Mullins is President & Principal Consultant of Mullins Consulting, Inc., and the publisher/editor of The Database Site. Craig also writes for many popular IT and database journals and web sites, and is a frequent speaker on database issues at IT conferences. He has been named by IBM as a Gold Consultant and an Information Champion. He was recently named one of the Top 200 Thought Leaders in Big Data & Analytics by AnalyticsWeek magazine.