Customer Experience will make Winners and Laggards

“We see our customers as invited guests to a party, and we are the hosts. It’s our job every day to make every important aspect of the customer experience a little bit better.” – Jeff Bezos, Founder, Amazon, “Online Extra: Jeff Bezos on Word-of-Mouth Power”, BusinessWeek, 2004

Our trends forecast for 2016 repeatedly talked about how quality of customer experience would determine the fate of banking institutions. As we head into 2017, customer experience remains a huge priority: the latest EFMA Infosys Finacle study reveals that creating a customer-centric organization and providing omnichannel digital experiences are priorities for 3 out of 4 banks.

However, results on the ground are yet to match intent. In a recent survey of 700 millennials, an overwhelming 75 percent said they were dissatisfied with their mobile banking experience. Banking clearly lags many other service industries in this area.

This is a matter of some concern because the customer experience conversation has moved ahead in the couple of years. The imperative is no longer about enabling a 360-degree customer view or making the “next best” recommendation, but of how to manage customer experience when there’s a machine, software or intelligent application at the service end. Customer experience will increasingly benefit from Artificial Intelligence enhancing human-machine interaction with better quality, consistency and efficiency. The customer experience of the future will be highly contextual thanks to analytics; conversational, involving humans and machines; and immersive thanks to Virtual and Augmented Reality etc. This pace of evolution will be too fast for many banks, which lack the foundation to deploy such technologies.

Those banks will increasingly fall back in the coming year. Gartner says that 89 percent of companies will compete mainly on customer experience. We agree. It is our belief that 2017 will see a further widening of the gap between those who understand how to use digital technologies to empower customers and enhance service experience, and those who don’t. This will be the year when laggards lose market share, even as winners pull ahead, faster than ever before.

So what can banks do to come out on top? First of all, they must become aware of a very significant shift in the technology-consumer dynamic, which will result in technology adapting to consumers’ personal choices rather than consumers adapting to technology changes. The arrival of self-learning systems means machines and applications will learn how to deal with people, even behave differently with different people.

So when banks think of customer experience, they must think not of one experience, but experiences for various segments-of-one. Here, analytics and artificial intelligence will play a huge role in sensitizing financial services to the unique needs of each customer in their immediate context, and fulfilling those needs in real time.

To provide unique customer experiences throughout the customer’s lifetime, banks must train their design focus on the customer journey. In 2017, we believe leading banks will try to articulate how the customer journey will evolve in future, in an attempt to add further value to their customers. They will also reimagine the organization and its various elements according to these journeys, and put dedicated teams in charge. Some banks might even reorganize budgetary allocations and reporting structures around customer journeys, instead of products or lines of business.
Last but not least, to attract and retain digitally empowered customers, more and more banks will reimagine banking business, processes, and products around their needs, and look to deliver truly personalized and contextual experiences.

Punit Chhahira Trends-17

Economics of the business ecosystem will come into play

“If banks can’t offer something more valuable than Amazon Prime, then we’re probably in the wrong business” – Bradley Leimer, Head of Innovation, Santander North America, “Empowering Lifelong Customer Relationships in a Digital World”, Money Summit, 2016

2016 saw the rise of the collaborative ecosystem as the new universal banking model, a consequence of distribution, decentralization and disintermediation brought about by digitization. We predicted that truly digital banking would resemble the digital models of highly successful platform businesses – think Uber and AirBnB. IDC says that by 2018, more than 50 percent of enterprises will create and/or partner with industry cloud platforms to distribute their own innovations or source them from others. Clearly, platform ecosystems are opening up new avenues of growth for enterprises.

2017 will bring the ecosystem into sharper focus. Each bank will need to articulate its ecosystem strategy in terms of the ecosystems it would like to participate in, and those it intends to create or lead. The first decision is relatively straightforward, calling upon the bank to identify the national, regional and global ecosystems that it would like to be part of. Being part of a strong national or regional ecosystem will help banks expand reach and penetration in local and nearby markets. This is the reason why ICICI Bank has tied up with Alibaba.com to launch a one-stop destination for trade finance for India’s small and medium enterprises. On the other hand, global ecosystems, such as those led by Google and Uber, allow access to almost unlimited customer data and insight that no bank can afford to stay away from.

The second decision – what kind of ecosystem to build or nurture – is much more nuanced. Here, banks should be looking at specific objectives considering their strengths, such as facilitating trade between customers. Deutsche Bank’s hub, where SME customers can gather to share, trade and engage, is a good example of this. Another example is a recent pilot Blockchain network for trade finance and international remittances set up by Emirates NBD and ICICI Bank, that will open up to other banks in the future.

But beyond this, banks also have to attain clarity on a fundamental question, which is linked to customer ownership. They have to choose between fighting for ownership of the ecosystem’s customer data and the customers’ share of wallet. Data shows that a minority of customers contributes the majority of profit. Hence not all ecosystems do equally well and this also determines the fate of their members. So each participant must do what it can to make sure the ecosystem profits as a whole and the share of wallet grows accordingly. The key point is that in 2017, economics must underpin a bank’s ecosystem strategy as much as other considerations.

Richard Longo-Trends-17

Moving a step closer towards autonomous banking

“Ultimate automation… will make our modern industry as primitive and outdated as the stone age man looks to us today” – Albert Einstein, Nobel Laureate

Automation is one of the prime forces in the 4th Industrial Revolution. The latest EFMA – Infosys Finacle ‘Innovation in Retail Banking’ study reveals that pervasive automation is an important priority in banks’ digital transformation agenda. This raises an important question about how automation, and technologies such as Artificial Intelligence, will impact jobs.

Our view is that the 4th Industrial Revolution, like the ones before it, will actually energize employment by creating new, exciting, higher order opportunities to compensate for the routine jobs it will take away. Contrary to fears, automation will amplify, rather than diminish, banks’ human capital by enabling the workforce to focus on creative or advisory roles. The first wave of bank automation was devoted to process automation, smart workflow automation systems and Straight Through Processing leveraging SOA-based integration across multiple, disparate applications.

Robotic process automation came next. This automated processes which were ridden with repetitive human actions, even when the supporting applications were not fully integrated.

A wide variety of back office processes that once bogged down bank workers were dramatically streamlined. By shifting these tedious, manual tasks from humans to machines, banks continue to significantly reduce the need for human involvement, making a direct positive impact on everything from performance and efficiency to staffing issues and expenses.

However, all this time, the focus has been only on automating and making processes more efficient so there would be less need for human intervention. But now, automation has taken a big leap forward into the realm of self-learning systems, which learn automatically as processes are executed and business rules are tweaked. What’s more, the processes are no longer only between people or between people and machines. We are heading into an environment where processes with machines and software at either end are bringing up the possibility of autonomous banking.

This will enable the delivery of smarter services. Cognitive technologies, which can sense, comprehend, act and learn, are already being deployed to solve a variety of problems in financial services, from threat detection to investment advice. Going forward, they will help consumers leverage overabundant data to manage their financial lives and banks to change, grow and innovate.

In future, automation will extend beyond organizational walls. A technology, such as Blockchain, will take inter-organization automation forward as it redefines and automates traditional business processes and transactions.

But one of the biggest markers of future banking automation is machine learning, which will allow banks to constantly improve efficiency, predict market trends and raise the level of service. Mizuho Bank’s use of Pepper, a robotic concierge that can detect facial expression and emotion, to assist customers in the branch and Bank of America’s chatbot Erica, hosted on BoA’s mobile app, will analyze the customers’ financial data to generate personalized recommendations, offer a preview of things to come.

We believe 2017 will see more banks driving processes to intelligent machines so that people and machines engage more productively. This will actually empower the human workforce and produce better business outcomes.

Scott Hackl-Trends-17

Security will be more pervasive, adaptive and integral

“The knock on effect of a data breach can be devastating. When customers start taking their business elsewhere, that can be a real body blow.” – Christopher Graham, Information Commissioner, United Kingdom, Advertising Association’s Leadership Summit, 2016

In 2015, 480 million customer records were breached by hackers, and the tally has already crossed 1.6 billion this year. Security attacks are becoming more spectacular in the digital age – think ransomware or the physical danger arising from the Internet of Things. And it is not just individual consumers who are at risk, because there is a rising threat to organizational security and reputation as well. Hence in 2017, enterprises should be looking to take a more pervasive, adaptive and integral view of security.

Banks need to go beyond merely securing the perimeter of their systems to securing every layer of operations and technology design. With developments, such as IoT and Open APIs taking banking increasingly digital and exposing even more data to risk, banks will have to defend themselves against the attendant security threats. This builds a clear case for more pervasive security.

But given the amount of data being generated and transferred over networks, it will be impossible for cybersecurity experts to monitor everything on their own. Ironically, the solution lies in digital technology, namely in self-learning machines with a far higher capacity to process data than human beings. These machines will use algorithms to monitor every instance of usage of data or applications and in the event of suspicious activity, will use intelligence to heighten the level of security in real-time. Adaptive is the future of security. 2017 could also herald a change in the security mindset with the entire organization, and not just IT, taking responsibility for it. Security will no longer be viewed as a compliance compulsion. Security emerging as a business priority is both inevitable and necessary given the pace of digitization and growing engagement between man and machine.

We believe that in 2017 those responsible for adopting and enhancing new technologies, designing new products and services, or managing digital channels should be thinking about embedding security within these elements. The idea should be to enable applications to secure themselves, rather than only relying on an external application for protection. The other goal should be to progress from prevention of incidents to prediction of security risk by monitoring system usage and feeding that data back to the people and machines in charge of security for early action. Progressive banks are also adding an extra layer of security with biometric authentication, voice, and facial recognition too, which are pretty hard to duplicate.

But even as banks ride these trends to secure their organizations against the growing threat, they must protect their ability to innovate and serve customers. The security team must therefore view itself as a facilitator of innovation, rather than a gatekeeper. Finding the right balance between protection and innovation might well be their biggest challenge in the new year.

You must bank on insights – every time, everywhere

“Information is the oil of the 21st century, and analytics is the combustion engine.” – Peter Sondergaard, Senior Vice President, Gartner Research, Gartner Symposium/ITXpo, 2011

Why does analytics, which has been around for years, still figure in the list of trends for 2017? It is because data science continues to evolve ferociously, fueled by the availability of ever increasing data on the one hand and affordable computing and maturing algorithms on the other. What’s more, business analytics is also benefitting by borrowing analytical advances from pure science.

Today, banks are anticipating analytics’ third wave. During the first wave, when information resided in a variety of silos, banks’ chief data challenges were of integrity and integration. In the second, the big challenge was to manage Big Data from different sources; here banks were helped by the decrease in storage costs. The third wave is characterized by fast data, and the need to gather customer, product, location and user insights, among others, and act upon it in real-time. New use cases are emerging even as known ones mature. Consider this – one financial services organization improved the way it used text analytics on incoming customer communication by leveraging algorithms that were originally built for matching DNA sequences. This helped it to prioritize and redirect messages to the right service personnel.

Heading into 2017, we expect a significant part of analytics investments taking the Open Source route. The latest EFMA Infosys Finacle study on Innovation in Retail Banking found that 66 percent of banks plan to invest big in Big Data and Analytics, which they believe are the most disruptive technologies at present. One problem though, is that most banks have struggled to achieve adequate returns on such investments in the past. But now, Open Source technologies, such as Hadoop, are bringing down the cost of analytics dramatically. So it is not surprising that 64 percent of banks in the EFMA Infosys Finacle survey are considering investing in Open Source stacks on which they can build applications.

We also look forward to analytics being available to all – partners and customers included – and not just banks’ top management. There is a dawning realization among banks that analytics, besides offering valuable input to human beings, must also feed machines and self-learning software. Now banks need to act on that realization by developing analytics models that can teach machines how to deal with complexity, and be more aware of their context.

Today, banks also have a better sense of analytical purpose, an understanding of how and where to use data, and this is leading to the implementation of more analytics models. For instance, historical information and the insights of predictive analytics are now being fed into AI for the purpose of modeling transactions and identifying the fraudulent ones among them, in real-time.

In the age of AI, banks will need to know how analytics can enable machines to learn, predict, and adapt continuously. A good example here is Google Maps, which combines a travel itinerary with traffic information to alert passengers when it is time to leave for the airport. Google page ranking, which lists various pages according to their relevance to the search, is one more.

In addition, we recommend that banks assess their current level of maturity in analytics in order to leverage it fully in their customer and operational journeys going forward. The goal should be to continually progress from a descriptive and diagnostic state – understanding what happened and why – to a state where they can predict what will happen and prescribe the right next steps for the individual user or the organization.

Next, banks must empower everyone – employees, partners, customers, and even machines – with analytics capability. This calls for an enterprise analytics strategy. In 2017, we ask banks to invest in analytics applications that work predictively and prescribe recommendations to organizations and users based on predictions.

And finally, banks must integrate analytics within the operational framework to improve and enable a variety of decisions in customer service, predictive maintenance, inventory management, credit approval etc. In 2017, we also hope to see many smart systems with inbuilt predictive analytics capability.

Empower your employees for digital transformation

“I hire people brighter than me and then I get out of their way” – Lee Iacocca, Former President, Ford, “Iacocca: An Autobiography”, Bantam Books, 1984

Almost 50 percent of banks surveyed in the EFMA Infosys Finacle study of 2016 believe that there is a high threat of disruption to the industry at the hands of technology companies and challenger banks. As banks proceed to digitally transform their own organizations in response, they are hampered by the absence of the right people, culture and structures.

Therefore, a key priority for banks in 2017 is to set this right by finding the right people and empowering them – employees, partners, customers and all – to succeed with digital technologies and the associated business strategies. So, who are the right people for digital transformation? Primarily, these are people with different skill sets, and an understanding of how to balance business, technology, and value. It goes without saying that top leaders must also possess these attributes.

Banks should also look for people with the right mindset – one that is unafraid to challenge the status quo or reimagine the tried and tested. In addition, banks must check that employees – and not just those in front office roles – are truly empathetic to customer needs. The challenge before banks is to convert rationally satisfied customers, who are known to be as fickle as unsatisfied customers, into emotionally satisfied ones. But in order to do that, they must first ensure their employees are similarly emotionally satisfied.

Digital transformation marks a massive change in the life of any bank. Hence banks need to set up a cross-functional team to anchor the changes that will impact the length and breadth of their organization. Last but not least, they have to ensure the people they hire have the technical expertise to see them through the transformation.

Clearly, finding such people amidst a talent crunch will not be easy. One way to work around this situation is to partner with Fintech firms and startup companies with the right cultural and technological fit.

The bigger challenge however, is to transform the organization’s culture for the digital age. This is a culture that values innovation, creative thinking, and total alignment with the customer. Infosys Finacle suggests that in 2017, banks take certain measures, which we have already implemented within our own and several client organizations, to achieve the necessary cultural transformation.

Our zero distance philosophy has helped many enterprises close the gap to their customers at every level of the organization. We have also introduced Design Thinking to many clients, which they have used to scale new heights of innovation to produce solutions to their customers’ greatest problems. Besides these techniques, we also recommend that banks institute a culture of lifelong learning in their organizations and instill learnability – the ability to pick up new knowledge and skills throughout one’s career – amongst their employees. The importance of doing so in a digital age where change is swift, massive, and guaranteed, cannot be overstated.

Venkatraman Gosavi-Trends-17