An experience to remember – Taking the friction out of banking

Friction in customer experience is defined as “interactions that inhibit people from intuitively and painlessly achieving their goals within a digital interface”. Author and marketing thought leader Don Peppers says that when customers talk about excellent experience, what they actually mean is “frictionless”.

He demystifies frictionless experience by distilling it down to four attributes:

Reliability: The offering should perform as claimed without breaking down.
Value: The customer must receive fair value for the price paid.
Relevance: The provider must remember customers’ individual needs and preferences.
Trustability: The provider should be proactive in disclosing information, and put customer interest first.
But before banks can design frictionless customer experiences, they must identify the source and location of friction. And who better than the customer to turn to for help? There are two ways in which banks can gather their customers’ perspective on friction, namely through dialogue and engagement, and observation of the customer journey.

Using dialogue and engagement to identify points of friction:

Relevance is one of the four essentials of frictionless experience. Today’s customers expect their banks to recognize their individuality and respond with products, services and experiences that are personalized to their unique needs. Since digital interfaces, such as mobile apps, are increasingly responsible for experience delivery, they should be adaptive, personalized and contextual. For that, applications need to be able to continuously engage customers in dialogue in different channels (or take feedback in other ways), gain insights from those interactions, apply it to update (individual) customer knowledge, and revert to their customers with contextual, personalized and relevant offerings.
Australian financial services group, Macquarie, takes a direct approach by conducting a “propensity survey” to understand what it is about the engagement experience that leads customers to recommend their services. Apart from undertaking such initiatives, banks should be looking out for points of friction in every customer interaction. For instance, if a customer with impeccable financial behavior calls yet again to request a temporary increase in credit card limit, the bank should learn from this and proactively raise the limit once and for all.
It goes without saying that customer-facing employees have a key role to play in delivering frictionless experiences. Clear communication and prompt resolution by attentive staff can take most of the rough edges off.

Observing the customer journey to identify points of friction:

A great way to locate experience-killing pain points is to observe customers as they go about their business, or better still, undertake the journey oneself. How convenient is it to use a digital interface, such as a bank’s website? Does the bank impose a whole lot of technical and financial jargon – banking terms, network availability and characteristics, ISO codes etc. – on users, who while literate are not exactly financial wizards? Does it ask customers to choose a network, implicitly forcing them to reckon with things like cut off time, limit, type of processing, fees and charges, and so on? Here’s yet another example of friction-ridden experience design – when queried, does the website display account balance in all its components, such as clear balance, lien amount, sanction limit, and drawing power, none of which make any sense to the lay customer?
Most times, the answer to these questions is yes.
The reason for this is that banks have always designed the usage experience from their – and not their customers’ – perspective. Thus a payment transaction starts by asking customers to click the “fund transfer” menu option and choose a payment network, rather than asking whom they would like to pay (which is essentially what the customers care about). The way to mitigate friction of this kind is by taking a “lifestyle” view of experience – for instance, enabling a customer to finance a purchase in a manner that fits best (loan against FD, sale of equity, credit card, and so on) rather than giving a tedious presentation on loan products. This principle applies equally to basic customer experience elements, such as user authentication.
Banks should validate customers in a process that is an extension of their regular lifestyle as far as possible – for instance ask for biometric verification instead of multiple passwords, and a mobile phone-based second factor of authentication instead of a physical security token.
A global technology research and advisory firm says that 89 percent of marketers expect to compete on customer experience this year. This offers banks an opportunity to learn from the kind of user experiences provided by industries that lead this race, such as hospitality and entertainment. For instance, some of the top hotels in the world are now allowing privileged customers to choose rooms, check in and even open the door, over a mobile app.Disney’s Magic Bands have given millions of visitors to their theme park in Orlando an experience that is not only smooth but also personalized to their taste. Banks that draw inspiration from these companies and go on to create industry-leading experiences will gain a competitive advantage that will be hard to beat.

Analytics: From Delphi's prophecies to scientific data-based forecasting with the use of analytics

Man’s desire to know what the future holds is nothing new or out of the ordinary.
7th century BC:  In ancient times, such a human need can be first seen and best exhibited by exploring methods the ancient Greeks adopted to answer their questions for the future. Historian Herodotus mentions in his work at least 18 temples (e.g Delphi) having a shrine providing prophecies for public and private affairs. All of the prophecies were vague but in some cases they turned to be true making people believers. Several stories show the confidence that people of that era had in prophecies. One instance where Delphi’s prophecy proved to be authentic was in 480 BC before the battle of Thermopylae, when king Xerxes and his Persian army were plotting against ancient Greece. The Spartans consulted Pythia (Delphi’s priestess) regarding the outcome of the battle. She indicated they were doomed but also prompted them to hear their fate. Doing so all Spartans lost their lives, but created a piece of history and gained immortal fame. It sounds like Pythia was right, doesn’t it?
21st century AD: Using data, numbers, technology and statistics we have now evolved from prophecies and indefinite speculations to scientific data-based forecasting with the use of analytics. Analytics is also well-established within business helping organisations to improve business performance. Data contains the history of your organisation and analytics is definitely trying to tell you something.
Analytics consists of four pillars as introduced by Gartner’s analytics maturity model. To make these analytics pillars sound familiar and applicable to your financial institution, we can give you lots of intellectual or simple (but not simplistic) day-to-day examples. These four pillars indicate how your organization can go up the maturity curve in leveraging analytics in your business.
Let’s take up a scenario where your organization suffers from customer attrition, you can use the analytics pillars to:

  • Pillar I, Descriptive Analytics: As a starting point, you can measure the attrition rate and quantify your losses. You can realise the magnitude of the problem and prioritise it among other business pains you may have to deal with and give it the proper attention.
  • Pillar II, Diagnostic Analytics: This pillar will help you examine a complex topic and decompose it into smaller parts that can be better understood. You can diagnose the most significant dimensions of customer attrition or the parameters that gave it a rise. Such dimensions can be geographic regions, branch ids, the time period of the year, channel types, product types, or customer segments where you observe the highest attrition rate. Using these observations you can learn a useful lesson from the past and you can then apply a relative corrective action in the future. But still, this pillar allows you to take re-active actions, after having first suffered the losses.
  • Pillar III, Predictive Analytics: Analytical predictions won’t produce an unquestionable future statement, but they will help you arrive at what is most likely to happen based on previously observed and statistically validated patterns. This is feasible by exploring and discovering hidden correlations between data, uncovering customer behavioural patterns, market trends, highlighting sequences of events that can lead as a domino effect to what you ‘re trying to predict, or by applying statistical modelling processes like Logistic Regression, Decision Trees etc.

    Predictive behavioural models can calculate the probability (0% to 100%) of each of your existing customers to leave your brand in the next few months, so as to take pro-active actions before it is too late. You can also define a threshold of churn-pressure score which is considered to be high enough to trigger your actions and direct your retention campaigns to, supplying you with a sufficient window of opportunity to retain the customers at churn-risk.
  • Pillar IV, Prescriptive Analytics: This pillar will help your organisation to perform and explore numerous business simulations and assess the anticipated outcome of a certain business scenario you are exploring to apply, before you actually decide to deliver it to market, e.g.
  • How much can you expect to decrease the churn rate if you manage to migrate customers from a traditional channel to a digital one?
  • What is the promotional offer and incentive that can make a customer at churn-risk stay?
  • What is the Next Best Offer you can make to each individual customer?
  • Can services or product personalisation help you retain more customers? How much?

The intelligence derived as outcome of analytics is the right piece of technology to arm your business with. The four analytics pillars can be used to help financial institutions respond to various business challenges, such as customer attrition, customer acquisition, cross-sell, up-sell, customer lifetime value, asset utilization, non-performing assets, fraud-risk, credit-risk, default-risk, reputational-risk, market-risk, performance management and many others.
Analytics can lead to improved operational efficiency, better customer service, more effective marketing, competitive advantages over rival organizations and better P&L statements for your organisation. The objective is always to improve the business by gaining knowledge which can be used to guide decision making, suggest changes, make improvements, recommend next best actions, or even exploit analytics for innovation.
Financial institutions can also expand the use of analytics to benefit not only their organizations but also their own customers, ecosystem partners, or their customers’ customers. In this way financial institutions can become more customer-oriented, create better services and act like truly trusted partners of their customers helping them grow.
While banks understand the importance of analytics, many of them struggle to realize meaningful returns as the initial investment costs are significant. One way to counter this would be to leverage advanced analytics solutions that use banking data models, new-age open-source technologies and built-in intellectual property to rapidly develop actionable insights. This way can make a difference and help you realize high returns on small analytics investments, while discovering meaningful customer behavioural patterns collecting and integrating data from structured data sources (bank’s internal systems), semi-structured sources (ATMs and corporate website navigation logs), or unstructured sources (data coming from social media or other news feeds, machine sensors IoT).
Finally, could we symbolically claim that Pythia was operating in analytics Pillar III? We can definitively spot 3 pillars in the pic below, the Oracle of Delphi…

The Oracle of Delphi

Banking App Experience – Moving from Fractured to Frictionless

In 2015, Exicon, a mobile solutions provider and app developer, estimated that between them, the world’s 15 largest banks had spent close to US$80 billion on developing 606 mobile apps. Citing app proliferation among banks, a well-known research firm says some have built more than 20 apps to fulfil a range of customer needs.Yet, mobile banking apps lag many others in innovation and quality of experience: an analysis of 140 apps from 35 top retail banks found that they were strong in basic functionality, but distinctly lacking in innovative features, such as personal financial management tools, chat and messaging.
Customers, meanwhile, are quite frustrated at having to switch between multiple apps.
When surveyed recently, 75 percent of 700 millennials said they were dissatisfied with their mobile banking experience.
Banks are clearly in a difficult position. The retinue of apps costs a lot to maintain, but currently yields little or no return. Worse, because the apps are usually not integrated, they cannot match what customers enjoy with other providers – a unified, consistent, seamless and convenient user experience. A great example here is Uber, which has taken the API route to integration with a number of travel and hospitality apps, from Google Maps to Trip Advisor to United Airlines, to provide a complete travel experience to users.
Banks should accept that the future model of success is one of distribution, decentralization, and disintermediation, and adapt their app strategies accordingly.
If the ultimate goal is to eliminate friction in the banking experience, then banks need to ensure the following:

  • Apps are consolidated differentiated and highly personalized
    A provider of mobile and Internet banking in the United States says that banking policies, procedures and (inadequate) communication are responsible for 70 percent of negative customer feedback on mobile banking apps.
    Rather than offering the same apps at everyone, banks must target different apps to suit the needs of individual segments, for example salaried professionals and small business owners. This may well increase the total number of apps for the banks, but it would do the opposite for customers.
    As banks are looking at increasing mobile capabilities to provide frictionless experiences, a new crop of users have become more commonplace. People who were not well-versed with smartphones earlier, are now increasingly choosing smart virtual assistants (SVAs) as a means to interact with their mobile phones. Banks are already looking at this channel as a means to offer products/services for these customers, and this channel holds a lot of promise for the future. For example, OCBC Bank has integrated Siri to offer banking transaction services through smartphones.
  • Apps provide functionality beyond transactions
    Banks need to look beyond core functionality, such as account views and payment methods, at innovative add-ons that are a natural appendage to banking services. These add-ons could be financial in nature, for example wallets, or non-financial, such as educational content. The idea should be to fit the bank seamlessly into the various activities that a customer goes through in a day – shopping, product research, event planning etc. – at every life stage. Currently, very few banks do this.
    A benchmarking survey of mobile banking functionality among 46 leading banks found that only six had installed an app-wide search engine to make it easy for customers to find what they needed.
  • Apps integrate with third-party providers in the ecosystem
    In many parts of the world, regulators are encouraging open banking with directives such as PSD2 and UPI, which will open up banks’ data resources to the ecosystem. This will create an opportunity for banks to partner with service providers, and in the process, access more customer data that they can use to personalize offerings and differentiate experience at the level of the individual customer.
  • Apps are compatible with a variety of mobile touchpoints
    Today’s customers move between a number of mobile devices and operating systems and expect their apps to follow. Hence banks should make sure their mobile banking apps work on different touchpoints, including wearable devices and tablets, and their respective operating systems. Here, they can draw inspiration from China’s WeChat, which even caters to those who do not own smartphones.

The goal should also be to make it easier for customers to access even offline touchpoints, such as nearby branches and ATMs via geolocation apps. Here it is worth citing the example of an app from a leading U.S. bank, which has an inbuilt option to call the bank’s representatives.
To conclude, banks must consolidate and integrate their mobile banking apps from a customer perspective, offer innovative additional functionality, integrate apps with other providers, and make them work on as many touchpoints as possible. But even as they make these changes, banks should not lose focus on earning a return on their app investments. Since apps are costly to maintain, banks must clinically eliminate those which do not perform, and balance investments between a limited set of successful apps and a strong mobile web, which would be cheaper to run. It is a good idea to invest small to begin with, and deploy further funds after figuring out what works and what doesn’t.

Banking Development Takes a Tech Turn

Computer Science has developed by leaps and bounds over the past decade. With every passing year, computing speed has been increasing at a phenomenal pace. About 15 years ago, we could not have imagined handheld Internet devices. Bill Gates, in his 1997 book titled Business@Speed of Thought, predicted about 15 Internet and software-based ideas, that includes Internet-based handheld devices, automated price comparison services, constant video feeds, and travel booking websites that doled out offers. Thanks to Apple’s Steve Jobs, for their innovative iPhone with a memorable launch in June 2007, Internet-on-device is now hygiene with almost every individual using it. Gates must indeed be happy to witness so many of his predictions come true.
Over the past few years, there have been rapid developments in wearable devices as well, with high speed computing capabilities, such as Apple Watch and Microsoft HoloLens. These devices provide mobile phone or tablet-like capabilities – chatting, browsing, financial transactions and can also be used to monitor various health parameters such as heart rate, physical exertion and sleep patterns. They are undergoing miniaturization to the extent that they could be implantable in the near future and may provide augmented virtual reality. A leading British science magazine ‘How It Works’ reports that by 2045, scientists will develop the capability to link neocortex of the brain with the Cloud through Wi-Fi, allowing us the ability to multiply our intelligence. Sounds like science fiction? Even the Internet and Internet-based handheld devices were science fiction decades back.

  • Technology development in banking sector
    Banking being a customer-facing business, any innovation that helps to enhance customer experience will need to be quickly embraced. Disruptive innovations in computing technology are creating value to range of services offered by banks and enables remote banking operations possible. Mobile Banking Apps are classic examples for this.
    Digital Banking is becoming vital for banks to offer diverse tools to customers and enable them to make smarter decisions. Even bank’s internal processes are undergoing transformation. Bots or software robots are helping banks to automating routine tasks and run processes without any error or monitoring. This coupled with Artificial Intelligence (AI) powered by machine learning, natural language processing and cognitive computing, can enable banks to handle complex tasks that are difficult to be managed by human beings.
    Augmented Reality (AR) is another area, which is generating interest among financial institutions. Citibank, Santander Bank and Paypal have done extensive proof-of-concept using Microsoft HoloLens, Google Glass and other AR devices. Some of the use cases being tested includes banking transactions, investment banking, ATM locator, location based merchant offers and tracking of customers in an area. With location-based-services, sensor capability and AR application, even smartphones can be turned into virtual display devices.
    Of-late, crypto-currencies or digital currencies have been gaining prominence in financial transactions, alongside fiat currencies. Making headway during 2009 with Bitcoin following the financial market collapse, they envision a shared, decentralized and peer-to-peer network, which is free from any centralized sovereign regulatory mechanism – A path breaking development for value transfer. And they have partially succeeded, as demonstrated by Bitcoin, Ethereum, Ripple and Litecoin. However, banks and financial regulators are not very comfortable with this idea, as they would not be able to control them. Further, these currencies do not provide information on real identity of the person transacting on the network and are in the limelight for wrong reasons, the recent ones linked to Wannacry and Petya ransomware attack. Though banks and regulators are not supportive of crypto-currencies, their underlying technology, that is the blockchain framework, is gaining great traction with financial services and other industries. Hundreds of use-cases are being piloted by banks and regulators across the world in areas such as payments, trade finance, KYC/AML, syndicated lending and many others.
  • Challenges in the journey ahead
    The advancement of technology in banking sector has its advantages and challenges. A major issue emerging in recent years is the firewalling of banking data and protecting them from digital hackers. Banks are investing heavily in continuously improving security technology.
    The other major issue is regulatory compliance. Over the years, banks have come under increased scrutiny by local/global regulatory bodies and increased capital requirements. The ever-changing compliance framework is putting huge pressure on banking compliance and profitability. In comparison, technology companies and fintechs are not subject to the same norms and enjoy huge operational advantage.
    Disruptive ideas are a greater threat to the banking sector than technology changes. Banks are facing innovation threats from technology companies and fintechs such as Google, Apple, Alibaba, Affirm and LendingClub, who have introduced banking services in payments and lending, mostly peer-to-peer. These have the potential to dent the income sources of major banks. Technology companies are also enhancing their capabilities in areas of financial planning, investments and bill payments, which were dominated by banks earlier. Many more futuristic services are expected to follow from technology companies with efficient models. Realizing the opportunity, some of the leading banks have started engaging with fintechs for futuristic services.
    Social media is another area which is changing the face of many industries, with its sheer reach and participation. For example, Facebook with about 1.4 billion active users, is making its presence felt in banking arena as well, by offering payments and investments through them. Sometime back they had signed agreements with American and European news organizations for direct publication of news, undermining the very existence of print and broadcast media.
  • The way forward
    The banking sector is set to undergo a dramatic shift in the near future with technological development. The quest for new applications and solutions will continue to trigger further disruptions, as it had happened in the past. However, this time it is the speed, spread and disruptive nature of innovations, primarily driven by software technology that is a differentiating factor.

Banking on Analytics

From a sluggish economy to disruptive digitization, banks have managed to survive and evolve along with the current environment. Most of it has been possible due to progressive banks showing the way and adapting to the environment for a truly digital transformation. Of all the major trends for banking transformation, analytics has made a consistent appearance year after year. As the hype surrounding big data and analytics has matured, banks are looking at ways to implement technologies to be more effective in terms of return on investment (ROI) and business value generated from analytics.
I believe that there are three factors – consumers, technology, and insights for all – that will be the drivers for the next wave for analytics implementation in banks:
Consumer expectations and technology advancements will drive banks’ analytics investments
As a result of the rapid digitization, consumers have become used to a fast-paced life and they expect personalized, contextual products or services instantly. The challenge that banks face at this point is that they can no longer depend on descriptive or diagnostic analytics to dwell on the whys. Now banks have to shift their focus towards the “hows” and use fast and real-time data that can predict the consumer journey and provide its consumers with relevant products or services.
With the latest technology in the form of AI or smart devices banks can look to provide personalized consumer experiences based on context and life-events to please even the ficklest consumers.
A simple use-case for personalized customer experience may be in the form of banking apps that most millennials access from their mobile phone to carry out payments and other transactions. When a user logs in, analytics helps the banking application understand what the consumer is most likely to do, and creates a user experience on-the-fly that is optimal for this consumer at this point in time.
Themes based on personas can be another use case for analytics implementation for customer experience.
Analytics helps with understanding the life events of consumers. This is used to determine the optimal user experiences for them at a certain point in time.

  • Technology will be powered by analytics
    It has started to dawn on banks that while analytics offers valuable inputs to humans for business decisions, there is a certain section of technology that benefits from it as well. And insights powered by data and improvement in automation have made sophisticated AI technology easily accessible – more so for institutions that weren’t able to implement it initially due to lack of internal resources and dearth of R&D skills. With analytics and process automation as the driving force behind it, the modern AI platform has the ability to transform traditional banking institutions for the digital era. Progressive banks are already looking to effectively leverage data and advanced analytics modeling that will put them in a position to capitalize on newer technologies such as machine learning and automation.
    For example, Wealthfront utilizes AI capabilities to understand how consumers are investing or spending, and then provides pertinent financial advice to them. Sentient Technologies continuously uses AI powered by insights to create investment strategies for users. Banks such as RBS have implemented AI in the area of customer service in the form of Luvo. It is a smart assistant that supports service agents who are answering customer queries. Luvo can search at higher speeds through a database to provide faster answers; it can also continually learn over time from gathered data to be more efficient with each interaction.
    Banks also have to be aware of the fact that it is not only the internal processes that need a facelift in the digital era.
  • Insights for all – every time, everywhere
    Till recently the insights derived from data were available to only the top management. But with changing customer behavior and technology that is driven by data, it is important that data is made available to all for optimizing internal as well as external processes. This in turn means that everyone should be provided with significant data management capabilities, and a talent base within the organization that will assist in deriving insights from data. For example, a few bank leaders came together to find solutions for difficult policy issues through a crow-sourced effort to use new data sets. The Bank of England has hired a Chief Data Officer, and has established guidelines around the instatement of an advanced analytics group and a bank-wide data community within the organization. It has also created a data lab to understand how these various streams of data can be combined to form actionable insights.
    And it is not only internal processes that can be improved with analytics. A case can be made for making analytics capabilities available for customers too. US Bank’s Payments division had created an application, InfoApp, that allowed their small business customers to analyze their expenditures and other corporate payments. It provided the small business owners with a consolidated view of their finances, as a result of which this app was an instant hit.
    This just goes to show, how democratization of analytics is just another avenue for providing a differentiated and personalized customer experience; and this in turn allows banks to stay relevant in today’s digital world.

Indeed, banks will look towards gaining the competitive edge through investments in big data and analytics. While previously the cost of investment was one of the barriers for enterprise wide analytics implementation, it no longer is the case with open source technologies, such as Hadoop. As these open source stacks bring down the cost of investment, banks will start to see effective ROI with these investments in analytics. But it does not end with investments in analytics alone; banks will have to cultivate a robust, analytics driven culture within their organizations and foster a bent of mind that will be insight driven. The success of these implementations will of course depend on the competent execution of technology, employee empowerment, and democratization.

Banking reimagined

New technologies are overwhelmingly changing the strategic context of the business world across industries by altering customers’ behavior and expectations, the structure of competition and business conduct. The banking industry is no exception. It is forced to evolve not only to secure existing sources of revenues but also to find new ones.
To achieve growth, banks need to use digital assets and capabilities to create new value for their customers and partners. In particular, banks have the opportunity to monetize their privileged position in the value chain by providing proactive, cross-business offers and services in real time. In addition to focusing on life events, banks can actually engage with and add value for their customers at almost every moment in their daily life, and through the customer lifetime journey.
While the rapid evolution of technologies is one of the key forces disrupting the prevalent business models of incumbents. We believe, banks can leverage the very same technologies as a catalyst to drive sustainable growth. Let us briefly hark back to the previous section, which started with the two aspects of digital business evolution. Those two aspects, namely optimization and business creation, tie in neatly with the Infosys Renew and New strategy, which says that to succeed, organizations must renew their existing systems, processes and landscape to improve efficiency, while investing in new systems, processes and technologies to build unprecedented value. Banks will hence need to carefully balance this approach of renew and new to reimagine banking with technologies.
Looking back at the customer journey and the prospects of digitization, we see that banks must integrate seamlessly into the life experience of their customers. Transactions and interactions must become smooth and invisible. Banking must be simplified to the point where it becomes abstract. In essence, it should move from the current ‘Straight Through Processing’ standard to the next-generation ‘Touch Through Processing’. Integrated platforms can also facilitate access to products and services beyond financial services, as well as to peer-to-peer advice and activities, engaging and creating value for customers.
In addition, core banking products must become simpler, modular, and transparent. Customers are looking for products they understand, that they can buy without worrying about the small print, and that they can change easily (and without penalty) as their personal situation evolves. New value-added services such as wallet solutions or peer advisory can then uplift those products.
Another crucial element is the notion of proactive advice. Customers expect banks to help them manage and optimize their cash and investments. For instance, when some money is left dormant in a low-interest rate account, banks should spontaneously suggest transferring it to a higher yield account. Suggestions should be accompanied by a clear simulation of the expected gains and based on the customer’s profile. Similarly, customers expect to be informed of unnecessary fees or redundant product combinations. Notably, in most cases these proactive suggestions can be fully automated and should be offered in real-time, taking into account context and location. Further, to enable the bank to visualize and become a part of the customer journey, banking activities need to be increasingly integrated.
Banks will use technologies to create a differentiated customer experience that reflects their brand and values. This means offering more accurately personalized and contextualized services to customers beyond mere products through the smart use of customer data.
An example of differentiated and personalized customer experience:
Identity & Property Document Management: Barclays offers cloud-based document management system in which customers can upload and store important personal and business documents, such as bills, birth certificates and passports. Barclays is also rapidly moving with biometrics and voice recognition.
New technologies pave the way to componentize the banking business. This componentization may result in more independent business activities that can be more freely mixed and matched with each other (or with the services from third party providers) to create a whole host of personalized products and services. This approach is akin to the service-oriented architecture (SOA) concept in and may eventually culminate in new business models that disrupt long-standing approaches.
The Time has come when Banks would not limit technology usage to address their own business pain points with the customer having to adapt to new technologies – but increasingly newer technologies and practices are adapting to customer needs and preferences – This is the Digital Age Mantra for growth and competition.

Banks and BOTs – the way forward

BOTs by virtue of their design, cannot replace humans completely. Today, they are being looked at as a cost effective means to achieve efficiency in the system. Hence, a clear strategy on how to implement BOTs for increased customer centricity and efficiency is key to success, as it is not just about a machine answering some FAQs. BOTs by virtue of their design, cannot replace humans completely. Today, they are being looked at as a cost effective means to achieve efficiency in the system. Hence, a clear strategy on how to implement BOTs for increased customer centricity and efficiency is key to success, as it is not just about a machine answering some FAQs.
Most banks today are structured by business verticals with few functions that cut across as a horizontal, which is reflected in most touch points.  Chatbots provide flexibility for banks to deploy them either horizontally or vertically. A hybrid approach can also be adopted.
It is also quite logical to assume that chatbots are in the continuous mode of learning and thus, practitioners of chatbots recommend that there should be hand-off from a chatbot to a staff of the bank, based on certain patterns observed while conversing with the chatbot.
Banks need to decide the best way to utilize bots effectively. These decisions will be driven by the banks aspirations, digital readiness and most importantly current and future customer profile.
Below are some suggestions for banks to look at in terms of making these decisions.

  • Vertical or Horizontal
    A vertical bot would focus on purely banking function, while a horizontal bot would focus on multiple areas – perhaps including banking, shopping, travel and so on.
    Banks need to decide whether they would like a horizontal play, with them playing the role of orchestrator and having access to the complete value chain or whether they would like to stay within the banking arena.
    A horizontal play offers advantages such as access to extensive customer data and greater control of the value chain. On the flip side, it requires extensive ecosystem and AI capability across verticals, which banks do not possess today.
    A horizontal play would work when a bank is a part of a conglomerate offering many other services. For example, Reliance Jio (which is a part of a larger Reliance Group) could offer a BOT which allows customer to shop from its retail stores, recharge its mobile bills, make payments from its payments bank and so on.
    Having said that, our suggestion to banks is to start with a banking vertical-based bot, which can be built easily, and will play on their strengths. Once the BOT is established, it can be extended to the ecosystem to provide a seamless experience.
  • Pure AI or hybrid approach?
    It is essential for banks to identify the processes that will be addressed by bots based on the level of complexity and the degree of automation required. Banks have the option of automating some very simple processes (for example, displaying balances or the last few transactions) on a completely NLP-based system. At the other end of the spectrum lies a hybrid, where a conversation starts with a bot but is handed over to a human later. For example, in the case of a customer dispute, a bot may gather the basic information, but hand it over to a human being for resolution.
    If there is a fraudulent transaction on a consumer’s credit card, consumer would like to block the card first and as per human emotions, would like to get connected to another human to describe the situation and seek assistance- a clear case of hybrid approach.
    A BOT at this moment might not be trained enough to spot a cross/up sell opportunity which clearly requires a skilled staff of bank to take it forward.
    Hence, a holistic approach needs to be taken with a clear and deep understanding of all the existing processes.
    We suggest that banks look at the low hanging fruit of pure AI to enable simple processes to start with. As the efficiency of the AI system improves, more complicated scenarios can be included and the relevant process hand-offs designed.
  •  Identify Use Cases
    As with most technology, Banks need to identify appropriate use cases with target segments in mind for chat bots. Where a bank would use a chat bot would be driven by the priorities driving the bank. For example, if streamlining internal processes is of high priority, bank may look at automating time consuming, repetitive tasks being performed by employees. For example, JPMorgan chase launched a bot to read and analyze complex legal documents, which saves over 360,000 hours of manpower.
    If providing a digital, 24/7 customer service is a priority, then a messenger bot on a customer’s most used channel would be a good fit for use case. This is one area where banks have forayed into extensively, as can be seen in all the examples provided earlier.
    The decision would be purely driven by the bank’s strategy, priority and readiness of the surround systems for “Botification”.

Bots have the capability to connect the dots and enable the banks to expand their ecosystem and provide a truly meaningful and profitable digital experience. Hence, we recommend that banks should start their journey with BOTs by identifying a good a business use case where they can provide the differentiation.
Quick movers have advantage in that their BOTs will start learning earlier than others, and will therefore evolve faster as well. Hence banks do not have the luxury of maintain a wait and a watch approach any more.

Bots: What’s in it for banks?

The growing interest of banks in the BOTS technology from a customer viewpoint can be largely explained by evolving preferences. Today’s digital users are well connected and have tons of information but what they want is timely, useful and non-intrusive advice and analysis.
Organizations have been chanting the automation, personalization, and digitization mantra for a while now and chat bots clearly fit that story. Used effectively, they can bring significant cross/up-sell opportunities and cost benefits.
Automation, AI, customer experience are the buzz words that banks live by today. BOTs provide banks a happy confluence of the three – enabling automation of tasks through AI, while providing exceptional customer experience.
Here are some of the reasons banks need to look at BOTs –

  • Engage customers and prospects
    Today’s customers prefer chatting over speaking to a human executive, and emoji’s over words. They want to communicate on their own terms and at a time of their choice. Banks can take a cue from these pointers and start engaging customers through chat. A more engaged customer will mean more business. Several banks have now understood that they have to meet the customer where the customer spends most time, in place of expecting customers to open banking apps to do their banking. We are noticing a slew of banks launching chat bots on Facebook messenger and Twitter. Examples include MasterCard and Yes Bank. With chatbots], banks ca given a contextual customer experience that makes banking frictionless. A good example for this is DBS which has introduced a chatbot based on Facebook messenger.
  • End to end value chain access
    Customers want to know more than their account balance; for instance, they may like to know how much more they can spend without overstressing their budget. To this end, a bot can play a role of an aggregator to serve as a one stop shop for all customer queries. For example, such an aggregator bot can in turn call the expense manager bot and so on. Overall, the bank profits from automation and customer centricity brought in by this.
  • Automation tool
    Bots, being able to take actions on behalf of customers and their employees, are of significant interest to banks. To enable this, chat commands from users are tied at the back-end to trigger specific actions. An example of this is that a chat request for stopping paper statements should trigger the relevant instruction to the reporting system. This should then be followed up by relevant questions based on the availability of customer information for electronic statement delivery.
    Additionally, BOTs can help banks in automating their internal processes. JP Morgan uses a Bot to streamline its back office operations, which helps in handling common IT questions like resetting passwords.
    BOTs deployed internally to help bank staff with faster and better connectivity with other important functions such as Finance, HR and administration. It also provides better access to the bank’s existing knowledge base.

Bots have the capability to connect the dots and enable the banks to expand their ecosystem and provide a truly meaningful and profitable digital experience. Hence, we recommend that banks should start their journey with BOTs by identifying a good a business use case where they can provide the differentiation.

Fintech Alliance Assessment: Four Criteria that Matter

A fintech alliance plays a significant role in a bank’s digitalization strategy. Digital banking, combined together with fintechs’ complementary capabilities, results in a digital ecosystem that can give a bank an edge over rivals. However, bank executives usually don’t have the same insights and visibility of a fintech solution as bank’s internal systems. The success of a fintech partnership traces back to a very early stage of the alliance: the Know-Your-Fintech stage.
In this article, we have identified 4 key fintech assessment criteria: novelty, complementarity, compatibility, and viabilit). A combination of these 4 should give a bank a balanced view of the fintech alliance value contained in a particular partnership.

Criteria 1 Novelty

Novelty is the quality of being new or following from that, of being striking, original or unusual.

  • Being original
    Fintech, by definition, is an industry composed of companies that use new technology and innovation with available resources to compete in or complement the marketplace of traditional financial institutions. Banks hope to have more access to new ideas and strengthen their capacity to implement the same. One way to score novelty is in terms of its originality: be it technology, use case, or business model
  • Digital strategy alignment
    Some financial institutions may err on the side of being too original. There are other factors to calibrate novelty. In circumstances where a bank is taking a progressive approach to digitalization. The less aligned the fintech is with a bank’s overall digital strategy, the greater the chances of the partnership creating undesirable outcomes.
  • Customer experience
    Novelty should be evaluated not only from a technology perspective but also from a customer experience standpoint. Customers are the lifeblood of an organization, and a unique customer experience is maybe the most important way by which a business can truly differentiate itself from competitors. On the other hand, technologically new and original doesn’t necessarily translate into a positive customer experience.

Criteria 2 Complementarity

Complementarity is a relationship in which the fintech company and the bank can improve each other’s qualities in digitalization.

  • Functionality
    In any review of a fintech product, a visible and simple metric is the presence of complementary functions. Nevertheless, bank executives should assess the startup’s functional fitness within the broader context of a digital ecosystem, rather than solely based on the bank’s existing business capacity.
  • Use case
    To make an effective partnership assessment, the bank should define a priority list of use cases where a fintech can add value based on the bank’s needs and the fintech’s capabilities. This is particularly important for fintechs that are use case neutral. Lacking focus and a sense of priority in use cases – and this happens often – may waste both effort and investment.
  • Product roadmap
    It is also worth pointing out the importance of understanding the roadmap of both banking and fintech products. Banks and fintechs are both organic organizations that change constantly. An outline of future plans is a guideline to examine any overlap of mid-to-long-term goals between a fintech and a bank.

Criteria 3 Compatibility

Compatibility is the state of being compatible in which fintech and bank are able to work together in combination without conflict.

  • Market match
    Compatibility with the fintech firm is a significant factor in leveraging the business potential of the alliance. Market segmentation is a starting point for evaluating compatibility. Bank executives need to have a clear idea of what customer segmentation the fintech targets.
  • Regulation and compliance
    Innovation comes together with risks.
    Banking is probably the most regulated industry in the world. Although regulation usually does not subject banks to certain technology requirements or restrictions – it focuses more on business guidelines – they need to make adoption of any new technology transparent, especially when there is an impact on customers. Bank executives should also conduct due diligence as per corporate IT policy, for instance, in the use of open source tools and public cloud.
  • Access to resources
    A partnership is nothing but to access each other’s knowledge and resources, in terms of communication, discussion, engagement, and implementation.
    Bank executives need to assess the fintech’s capacity before signing an alliance deal: For instance, how many projects are they running? How many banks are they working with? What are their available resources? And what is their human resources plan? A delayed response from the fintech firm in the early negotiation stage could be a sign that it may not be able to commit its efforts to the future relationship.
  • Integration architecture
    Fintechs are often designed based on the latest architecture, for instance, service-oriented architecture (SOA), RESTful API, and micro-services. The flexibility enabled by these modern, componentized architectures explains why integration with fintechs is usually less of a concern for bank executives. Bank executives should assess integration not only from the organization’s point of view but also from the ecosystem’s perspective.

Criteria 4 Viability

Viability is the ability of a fintech to survive or do business successfully.

  • Funding
    There is certainly no one-size-fits-all rule to select an appropriate fintech based on funding. Fintechs in early incubation stage may be too small to offer a mature and approved solution. Fintechs that have passed Series C or even E funding may be too independent to rely on banks for business expansion. The bottom line is the company should be financially healthy with reasonable cash flow to support its daily business, regardless of whether it is self-funded or funded by VCs.
  • Business model
    A report on revenue and cost is an effective touchstone for understanding a fintech’s “real world” business. In spite of the fact that many fintechs are still in the growth stage with negative net profit, and not able to provide detailed financial reports, understanding the business model properly is an alternative to analyzing business potential. Be it a monthly subscription model based on the number of customers, software license model, or fee generation model, a proper and clearly articulated business model is critical for understanding how the revenue stream is generated and how revenue could be split between the bank and the fintech, and importantly, for assessing any financial impact to customers who use the services: a fintech alliance relationship is fundamentally a commercial contract between two parties.

Recommendation

There has been a strong growth in fintech across the globe, sparking a digital revolution within traditional financial services. Banks have started partnering with fintechs to address these challenges. To select the right fintechs to work with, bank executives should:

  • Make sure fintech candidates align with the bank’s digital banking strategy. If they haven’t got one yet, it is time to create it first before forging a fintech alliance.
  • Assess the value of fintechs based on the four key criteria discussed: novelty, complementarity, compatibility, and viability in the context of the bank’s business focus.
  • Carefully review the customer list of fintechs as a strong reference of the assessment criteria.
References:
Infosys Forrester Research http://www.experienceinfosys.com/bedigital
Finacle Connect: Truly Digital Banking: https://www.edgeverve.com/finacle/finacleconnect/trulydigital-banking/
Wikipedia https://commons.wikimedia.org/wiki/File:Startup_Financing_Cycle.png

New Principles to Explore Banking Blockchain Use Cases Effectively

A new breed of blockchains are being developed to become identifiable, controllable and asset-agnostic. This evolving architecture demands new rules to explore use cases in the financial industry. Here we outline three use-case principles for bank CIOs that can potentially guide their blockchain investments in 2017.
FIs are cautious by nature. Blockchain technology has the potential to revolutionize financial transactions but several challenges have to be overcome – one of the fundamental question from FIs is where to start for ‘proofs of concept’ of blockchain use cases.
In 2016, Moody’s published a whitepaper that identified 25 important use cases from over 100 use case candidates, most of which are still valid in 2017 – but a collection of 25 use cases is still far more than sufficient to give a clear view of exactly which use case fits most to a bank’s business. The new blockchain architecture – identifiable, controllable, and asset-agnostic – demands FIs to explore further what are the right use cases. In this chapter, we introduce three fundamental principles to help identify best-fit blockchain use cases, so that FIs can move forward to operationalize the technology and integrate it into current processes and systems.

Principle #1: Non-Monetary

In an era of cybercrime and stringent regulatory requirements, blockchain regulation is a gray area in the financial industry, creating some uncertainty around its implementation. Regulators are keeping an eye on blockchain technology, especially in the area of:

  • The basic tenets of a KYC/AML compliance program (for instance FINRA 3310) require the customer identifies (who, where, and which organization) must be traced by blockchain payment system
  • The general ledger integrity must be assured – all distributed ledgers that reflect account changes must be reconciled to bank’s enterprise GL

In such a context a blockchain, when tied to fiat or virtual currency, creates extra complications with compliance and legacy integration. Instead, documents, records, financial instruments and even private equities carried by blockchain could be an ideal way forward to avoid the compliance hurdles and regulation uncertainties.
However, central banks are catching up quickly. In countries where regulation supports blockchain innovation – for instance, the Monetary Authority of Singapore is testing blockchain for a new payment transfer project – FIs could adopt an aggressive approach to try blockchain payments in sandbox environments.

Principle #2: Contained

R3 CEV, as one of the largest blockchain consortium, stated early on, that the initiative will, ‘seek to establish consistent standards and protocols for this emerging technology across the financial industry’.
However, the question for financial firms is whether they should work together on a standardized consensus model that everyone agrees on or work independently on different versions and let the market decide. The other side of the coin is it takes time for a consortium to reach an agreement, and extra efforts to implement – any initiative of this scope to harness a standard in a fast pace environment is definitely not easy, and sometimes a road block not a catalyst to innovation. What happened to R3 in recent year has shown the difficulties of building an ambitious consensus among a large group of key stakeholders.
Therefore, FIs could first look at use cases that could be implemented inside the organization, or within a much smaller scale of consortium – it enables them to test the technology in a time-to-market manner, and start small with niche-market use cases. Most FIs are interested in blockchain but have not participated in major consortiums – for instance, regional and small-medium-size banks. Such FIs can go ahead with this light-weight approach, and even global multinational banks could run a bi-model strategy to try both contained and consortium relevant use cases.
Having said that, a bank should consider all these factors in a local context to determine the best-fit approach. There are exceptions where agreement can still be efficiently made among a group of banks. It could be achieved by a powerful centralized organization, for instance, a financial holding company that includes a family of banks, or a strong state-owned banking association that represents a group of local credit unions.

Principle #3: Distributed

It is essential to understand that from a business perspective, blockchain doesn’t fundamentally change how payment or money market works. However, blockchain as a technology platform can be adapted to a business context – and potentially transform the whole process and operations.
The dispute of the pros and cons between a centralized database and decentralized database has been continued for decades. Centralized system has approved its efficiency in many business scenarios to handle mass volume transactions, for instance, core banking. On the other hand, although no formal benchmark released to indicate any serious capacity issues for blockchain, efficiency (for instance network scaling problems) is a general concern to not just blockchain but many other types of distributed databases – where significant overhead or replication associated with these protocols exists.
However, blockchain, by its nature as a distributed record-keeping database, could demonstrate its true value, especially in a collaborative, distributed business environment. Typical scenarios include trade finance, international remittance, and syndicated loan. For these use cases, and with careful planning, FIs should have the confidence to deploy a scalable blockchain solution not only in a sandbox environment but also in a production environment.