Branch of the future

The contemporary and emerging models of digital banking pose an important question to bankers: “Will the brick-and-mortar model of branches become history in a few years from now? Most of the banking transactions ranging from funds-transfers to product purchase have been digitzed and are now available at the click of a mouse or at the tap of a button on a smart phone. The waiting time for banking transactions has reduced exponentially and customers now demand to be served immediately and effectively. Traditional branches seem to be losing their sheen and the future generation seems to be more inclined to use the digital medium rather than branches.

However, a closer look at the customer and geographic segmentation tells a different story. Despite the tectonic digital shift at a rapid pace, branches still serve as one of the leading sales channels for banks. Reports also suggest that 30 to 60 percent of customers prefer doing at least some kind of banking transactions through branches. Further, services like cash deposit/withdrawal, issuance of demand drafts and deposition of cheques actually call for a physical branch or an ATM visit.

Banks therefore need to come up with a hybrid model of branches which would be a combination of digital banking technologies and analytical capabilities at a physical location. This model of branch would have fewer staff, will occupy lesser real estate and would be equipped with the latest gadgets to provide both sales and service capabilities.

Bank branches primarily serve two fold functions: sourcing and servicing. Future smart branches will provide servicing through automation and sourcing through analytics. The right mix of automation and analytics will define a smart branch of the future.

Automation will take over servicing

Approximately 60 to 80 percent of a branch’s transactions fall under servicing functions: cash deposits/withdrawal, funds transfer, DD printing, cheque clearance being the majority of repeat servicing functions. Banks today are focusing on automating these repeat servicing functions with hardware technologies like cash recyclers (cash deposit and withdrawal), kiosks (statement print, funds transfer), tab banking (service requests) and IVRS (grievances). It can be envisaged that in the coming time, almost all the servicing functions will be taken over by machines through automation technologies. This will lead to are fewer queries and a quicker resolution without any human intervention, an eventuality often termed as “quicker and fewer” in banking.

Analytics will take over sourcing

Sourcing however, will be more mobile than static. Branch staff will be able to navigate through the river of opportunities to scout for meat rather than being a static tree waiting for food to be fed. This means moving away from the traditional way of customers approaching the banks to buy products to proactively identifying the target customers through market segmentation and then pursue these opportunities by approaching these clients. This is where technologies like AI, ML and embedded analytics will be extensively used by the branch staff to identify the target market, perform customer profiling and decide the most appropriate and suitable product suggestion each customers. Not only this, analytics will also help branch staff define the probability of a customer buying a particular product at a particular time. Hence, an effective salesman will be defined not by being an aggressive pursuer or excellent communicator but by having the adeptness and sharpness of utilizing technology to the fullest. Banks will be able to perform the three critical tasks effectively: identify prospects and pitch the right product to the right customer at the right time.

Smart branches hence will be defined by the extent of automation gadgets like recyclers, tabs, kiosks and IVRS to service the customers and the by the use of smart applications for branch staff making use of technologies like AI, ML and embedded analytics. The greater the use of smart technologies and gadgets, the smarter the branch.

Size and geography – The Hub and Spoke Model

Physical presence of a branch provides an opportunity for a bank to acquire customers around an area and to boost brand presence of the bank. However, high capex and the opex costs of a traditional branch model make it increasingly difficult for banks to open several branches at a short distance from each other across the city. Smart branches of the future can potentially solve this problem by providing an opportunity to open smaller branches with lower costs at smaller distances, thereby covering a larger population and increasing the brand presence. This model will have a central hub branch which will cater to the smaller smart branches serving as ‘spokes’. Customers will have to travel less in order to reach a branch. Hub branch will provide all operational support of sales, service, documentation, staffing to the spoke branches.

Consider a hypothetical city of area 10 sq. km. A bank can open around 10 traditional branches of area approximately 1000 sq. feet. Thus, each branch would service an area of approx. 1 sq. km. An approximate calculation shows that as compared to a traditional branch, a smart branch can make opex drop by about 50 percent and the capex by around 30 to 40 percent. This means more branches per sq. km (0.5 sq km against 1 sq. km in the above example) and 2 smart branches can be opened in place of one traditional branch. Hence customers will have to travel less to visit a branch and yet get a quicker response due to shorter wait time.

Traditional model of branches

Hub and Spoke model- more branches at same cost

Staff and timings

Smart branches would have around 6 employees per branch as against 15-20 in traditional branches. Average working hours for smart branches would be 15-18 hours per day as against 6 to 8 hours per day for traditional branches. This means double the working hours at half the cost!! As stated earlier branch staff has to be adept at using technologies to their advantage to generate the best possible outcome. Whoever masters the technology will be a winner. However, it will have an increased cost on mobility of the bankers who may have to travel more to meet customers in the market rather than sit in branches to wait for deal.

Conclusion

Emotions in User Experience Design

Users today have a sea of products to choose from, often products that are similar to each other. So, it is natural to wonder, how a user/consumer chooses a product or service, based on what criteria? How does a user move from a trial-purchase to repeat-purchase to regular-purchase of a product? How does a buyer become a follower of a brand? An important aspect is “Emotions”.

Let’s ask another question – What could be the percentage of users who perform rational analysis while making an online donation or while e-shopping? Recent surveys indicate that emotional decisions outnumber rational responses online. This implies that presenting appropriate content at appropriate moment can significantly increase the probability of influencing a customer’s financial decisions. Emotions can be elicited immediately or over time by physical products, digital products and services that users come across or use in their everyday life.

Feelings and emotions are what make us human and help us use our judgement to distinguish between good, bad, safe, dangerous etc. This can be applied to the product and the user who owns and uses them. Technology does affect emotions of humans in their everyday life. For example, a website or an app helping the user to easily order food from their home can make them feel happier, whereas any trouble while booking a ticket elicits distrust and negative emotions.

Emotional response is a function of the feelings and the experience a person encounters during the interaction with the product either consciously or sub-consciously. Users experiencing positive emotional response such as joy, pride, relief, surprise, satisfaction, curiosity are repetitive users of the product or service. For example, leader boards on online course sites motivate repeat users to upkeep their rankings. Similarly, instead of the system error pages like 404, presenting smart and beautiful error pages would invoke positive emotions.

We have talked about emotion, emotional response and how they are important for a product design; but achieving it is quite difficult because emotional response might vary from person to person. Representative studies by researchers, scientists and psychologists show that there are many common characteristics of successful product design .

One such researcher is Don Norman. He mentions that there are three levels of emotional system that help predict emotional experience and create the desired emotional connection of the product with their users. They are:

Visceral level, which connects the user to the “appearances” or “first impressions”. This level of emotion is generally automatic and mostly out involuntary for an individual.

Behavioural level deals with how quickly and correctly the user is able to use the product, that is the usability of the product that makes the user feel smart by using the product. For example, usage of consistent button positioning and styles, offering voice navigation support for ease of navigation address the behavioural level.

Reflective level entails the user’s reflections about the product before and after using it. If the user is able to tell stories and advocate the product, it satisfies this level. For example, users may talk about how cool they found the one-click on-boarding process through the mobile app of a leading bank.

Focusing only on functionality is not sufficient. Designers need to understand users’ psychology, and identify what they require from the product beyond merely fulfilling functional aspects. Tools and principles like Plutchik’s wheel, Maslow hierarchy of needs, Triune brain model, Gestalt principles can help designers assess and measure the potential emotional response.

These techniques and knowledge can be used to understand how a design is perceived, and help create products to provide effective emotional design, that is, functionally correct, unique, and great looking design for compelling and engaging experiences for online and mobile app users. These experiences can lead to competitive advantage and improved business.

Reference:

Book – “Emotional Design: Why We Love (or Hate) Everyday Things” by Don Norman

About AI, ML and Payments

There has been a lot of buzz around Artificial Intelligence (AI) and Machine Learning (ML) in recent years, specifically in the areas of fraud management and customer service. The ability to assess customer behavior across social media platforms, ecommerce platforms and even browsing histories has made these improvements possible. Google with its search engine, Amazon with its product recommendations or Facebook with customer specific news feed pioneered the usage of AI & ML.

Have you ever wondered how, if you search for a product on a website, the same product keeps on featuring as an advertisement on all the other websites if you use Chrome as your browser? How Netflix or Amazon prime can recommend the movies or sitcoms to watch based on history, usage and other preferences? Have you ever wondered how your Gmail inbox is automatically able to filter spams and tag mails as social or promotions? Gmail uses a complex algorithm coupled with ML using the subject lines, links (if any) in the mail and historical handling of such mails along with user’s contact lists to filter and tag. With artificial intelligence and voice assistants such as Alexa, the same can be applied to speech recognition.

The other day I was trying to book a hotel for family vacation through one of the online travel portal apps. For the exact same room and other specifications, it showed me different prices since it used two different user IDs, and hence different past preferences, bookings and spending history. And this was at the exact same time.

While most of the above use historical data with complex algorithm and use what we call rule-based or supervised ML; for certain predictions like shopping recommendations they also use association learning or even clustering as part of unsupervised ML. Thus Gmail can apply filtering label, Facebook can customize feed, or any card management company can apply labels to any particular transaction such as “fraudulent” or “good”, based on the transaction data and history available. However, when we apply this rule-based supervised machine learning to complex scenarios where the data may not be clean or where the data is huge and sourced from multiple places online or offline, with no specific labels available, un-supervised ML using auto encoder neural networks which can self-learn, needs to be applied. This is specifically beneficial in reducing false alarm rates which plague the card transaction industry where transactions originate from multiple sources like e-wallets, e-commerce platforms, m-commerce etc. As per a study, around 35% of digital card transactions through large retailers flagged as fraud were found to be false positives resulting in loss of customer trust and business. It cost USD 8.6 Billion of declined order cost to the merchants in 2016. Such false positives can be greatly reduced using the cognitive approach to ML which does not require labeling of datasets, can consider new data on the fly and learn and predict with higher accuracy.

AI and ML can also be effectively applied to traditional payments, be it domestic or cross border through local payment schemes or global schemes like Swift.

Consider the scenario from a fraud detection perspective where a person planning for a foreign destination vacation transfers money in foreign currency to two different vendors where each foreign currency transaction amount is just below the local regulation threshold. Similarly, another person does the same keeping the transaction value below the threshold to deflect and discourage any suspicion and scrutiny that might reveal that the payment is being made for money laundering purposes. A rule-based machine learning system based on historical transaction data may not be able to pick such differences and may tag both transactions as fraud/AML in which case the first payment transaction would be a false positive. However, an unsupervised ML based AML system along with AI which can continuously learn, could provide real-time prediction with higher accuracy and may be able to differentiate between the two transactions.

As part of a Finextra survey with a partner, respondents highlight inefficiencies in handling repairs and 48% highlight inefficiencies in handling investigations. A whopping 62% of respondents highlighted that they have not applied any AI till date to exceptions and repairs.

A combination of cognitive and rule-based supervised machine learning can be applied to any inbound or outbound payment not just for fraud or AML management but also for cases of repair or data enrichment while processing any payment. Most likely causes of a payment failing validations and going into repair queue are incorrect or missing information in the message like BIC address, special characters, incorrectly formatted remittance information, incorrect identification details of customers like account etc. These digitally enabled checks are particularly important to maintain high STP rates. It’s critical as the industry is moving towards immediate and real time payments and settlement of funds, and not only are the costs of manual intervention and repair significant for banks but they also cause significant delays specifically in a cross border scenario. Another research attributes 80% of the processing cost of transactions to exceptions and repairs. It suggests that with an average rate of exceptions at 20%, a single point decrease in exception rate can decrease the cost by 4%.

One important underlying factor in using AI and ML is that data is key and especially the richness of it from a payment processing perspective. The data format of a payment instruction should have sufficient information for any of the AI and ML models to assess and derive value for banks and Fintechs. Adoption of ISO2022 as the global standard for payment messages would facilitate this since extensive information related to remittance can be embedded in the rich data fields it supports.

While the jury is still out on the significance and the scale of usage of AI and ML, and on the most effective way to harness these technologies in banking and financial services, the possibilities and probable benefits that these technologies offer are immense.

References:

Payments in the Open API world

APIs are not new to the banking universe; they have been in use for a long time now. APIs were traditionally used for integrating the different systems in the bank with each other or for providing services through customer channels like internet and mobile banking.

Evolution of technology and changing regulations, and market changes in line with these developments are now opening up new avenues for API usage. One of the primary differences between traditional and current use of APIs is that now API access is defined more stringently as they are exposed to the external world. By publishing open APIs, banks allow Fintechs or third party developers access to the data and provide innovative services which was impossible earlier. Who consumes the APIs and how they create value using them has become exceedingly crucial. Earlier usage was restricted to within the bank for integrations, but now public APIs have opened up many more interesting avenues.

This trend is global and as per Infosys Finacle Efma Digital Banking Report 2018, 65% of the respondents consider open APIs as the top technology impacting banking. In this blog, we will primarily focus on how the payments space is slated to change with APIs coming into picture.

Current payments landscape:

Currently, most of the payment systems in the world are either file based (Traditional Clearing, ACH, SEPA etc.) or message based (SWIFT, RTGS, IMPS etc.). This is primarily due to the times in which these evolved and the technology/communication infrastructure available to the market players at the time. The emergence of real time rails like SEPA Instant Payments and RTP by TCH have allowed the possibility of back-and-forth message transfers between various constituents in the payment landscape. With the adoption of ISO 20022, there is now a global standard which can be used for each and every payment system. A lot of payment systems have adopted the standard already and others are following suite. The fact that such a standard exists and open API itself is based in part on it helps set the ground for an API revolution in the payments space.

Emerging trends and Future state:

With the advent of real-time payments and its rise around the globe, we are now seeing major technology and retail companies also eying an opportunity to leverage them. Regulations like PSD2 are enabling new services and faster payments. Most of the real-time payment systems are ISO 20022 based and involve back-and-forth messaging. A sample flow is shown below:


Source: SEPA Instant Payment – Credit Transfer Rulebook

Such flows can be better supported using an API-based system. There are already API-enriched traditional message flows like UPI in India which is an overlay on the IMPS payment system. API calls are used to identify the payer account, bank etc. from the virtual payment address. There are other examples as well where the API revolution has already transformed or is transforming domestic payments. Federal Reserve in the US is currently deliberating on launching its own faster payments real time rail and technology giants such as Google, Amazon etc. are asking for an API-based ecosystem which will enable 3rd parties to offer new products and services.

However, this is not limited to domestic payments and the effects are visible in cross-border remittances as well. SWIFT is currently working with banks to launch a “pre-validation” service which allows banks to call a pre-validation API to check for accuracy of information provided before the payment is sent. This will avoid payment failures for conditions like wrong account number, mismatch in name or other such errors which currently cause failure, though all the participants in the chain will incur a cost for it. A few other examples of emerging trends in this space are listed below:

  • API Exchange from Joint Electronic Teller Services Ltd: Hong Kong’s JETCO launched an exchange with more than 200 APIs which helps simplify cross-border trade and payments
  • UnionPay International launched a developer portal which opens up its cross-border mobile payment product APIs.
  • US’s Cross River Bank along with UK’s open banking platform Railsbank Technology Ltd. is providing an API interface based banking-as-a-service (BaaS) platform.

Banks and industry players have been trying to transform cross border remittances and a major shift is on the cards where APIs are expected to play a major role.

IoT in Banking

We live in a “smart age”; Internet is ubiquitous, data is fast and cheap, everything is connected. Whether phones or watches, television or lightings, home automation systems, security systems, household devices or any appliances, they are all becoming “smart”. The idea of calling a TV (hitherto named “idiot box”) a “smart” device would have been absurd a few years ago whereas it is a basic expectation today. The underlying technology which makes it all possible is the “Internet of Things”, defined as “the interconnection via the Internet of computing devices embedded in everyday objects, enabling them to send and receive data”.

While all the emerging technologies are powerful in themselves when looked at in isolation, the real game-changer is their combination or synergistic effect. For example, IoT and big data combined can be a powerful game changer to the banking industry. In this blog, we will look at some of the applications of IoT in Banking.

Some of the examples of the application of IoT in a bank’s existing process/products are listed below:

The potential of IoT in combination with the other technologies is immense. As illustrated above, IoT can be used in any aspect of banking which involves a “field visit” or where information is required on the status or whereabouts of a person or device. Whether it is a site visit to ensure the veracity of documents or tracking goods sent across the oceans or current/predictive output of a farmer etc., to name a few. With the upgrade in technology, lighting data transfer, faster devices etc., the application of IoT is expected to see significant uptake in the coming years.

Digitization in Corporate Banking

Over the last few decades, banks have largely focused on digitization of retail banking. There has been very limited focus on digitization of corporate banking. Now, because of the increasing demands from corporate customers and the overall innovations happening in the space, banks are forced to relook at their corporate banking services and accordingly define their strategy for the future.

Banks looking to enhance their corporate banking solutions and services will have to undergo a complete digital transformation covering both front end (channels including mobile) and back end systems. As part of this journey banks should focus on some of the below mentioned areas:

Digitize the Customer Journey

Digitizing the customer journey will change the way relationships are managed giving relationship managers more time to focus on other value added services like advisory.

Banks should look at straight through processing reducing the turnaround time, resulting in operational efficiency and reduced cost for banks.

To summarize, banks must invest in digitization and have a differentiated offering for their corporate customer. They need to formulate a clear strategy to have an edge over other banks in the corporate banking space who are their traditional competitors and also FinTechs trying to foray into the space.

When Will My Product Look Like Facebook?

It is the question we hear every time we start a re-imagination journey for any module. Will it ever become pretty, and provide a standardized and consistent “wow” experience? Will it be like Facebook or LinkedIn?

First, deciders aren’t users

It is like the first bicycle that my dad bought me – I couldn’t test ride since I didn’t know how to; I couldn’t choose because the money wasn’t mine and I couldn’t argue the choice, because between the two of us I was clearly not the bigger or the older one.

In the business world, the experience that fascinates purchase decision makers like CXOs/IT heads might not be the same that eases the life of an employee. Some colorful dashboards or fancy features are ‘Wow’ for CXO demos, but the IT specialist might want all validations covered everywhere. Unfortunately, the wow of an easily executable simple feature doesn’t often translate into good business metrics to impress buyer decision makers. Moreover, the rare and few usability tests that are done, are conducted with existing users who have probably found a way to perfectly execute simple things in complex systems.

There is no Skip button

Facebook tries to sell stuff to me and I can conveniently skip it. I can be really annoyed about sponsored search results in Google, paid posts in Facebook and ad breaks in the middle of YouTube videos, but I have an option to never click the sponsored links.

It is not the same for enterprise app users though. The most simple and intuitive flows for the end-user might not be great for the company’s bottom-line. ‘Skip Customer Insights’ is a good option for me as a teller with a long queue, but then, there is a loss of a conversation or cross-sell opportunity that is bad for business.

As much as we claim them to be seamless, force-fitting interventions in the flow is often a pain. Smart users might find shortcuts to skip them and find new ways of using the product. The not-so-smart ones may get highly skilled with a nasty application flow and then even resist the change in this pattern.

And then there is the exact opposite of this – enterprise applications that are purely meant for task completion. Everyone sees everything and all kinds of complications are part of the same flow; which brings me to the next point:

It is not the same thing for everyone

There is only ONE version of the product in most B2C products, except for few customizable preferences. But enterprise users often in a specific role do the same set of things over and over again and don’t touch the bulk of the rest of the application. And it is totally different from another set of users using the same product in the same bank.

This reflects in the way performance is measured as well – a higher page load time may be acceptable for the back-end user if system does more validations. This might be an annoyance for the frontend user frantically searching for the customer’s open service request when a customer is standing right in front of him.

And hence the standardization question – Why is this flow not the same across channels/roles? Quickly creating a prospect is highly important when a customer expresses interest in a product on the Internet; but no customer walks into a branch to give just their name and phone number! We need to judge how much of the paper application form we really need to capture right away in the system to create intelligent prompts.

Legacy OR the big elephants in the room

Sometimes ‘Digital Transformations’ are not as pretty as we would want them to be –enterprise applications don’t change dramatically overnight. The earlier transformations might have just moved things from pen and paper to a system and retained the exact same process. There might be hundreds of costly systems in the bank that haven’t moved at the same pace. And unlike android updates, the upgrades don’t come for free and banks don’t change hardware every 2 years. There will be older versions, older integrations and older customizations.

Do we refuse to even get inspired?

Of course not, but replicating elements needs much deeper thought and understanding of the real user. And if we do understand our users, we need better ways to articulate it to those who make decisions for them!

Artificial and human intelligence – Striking the balance

Imagine that I own a company that can manufacture babies. The babies can be delivered in the color as preferred by the customers. It will have all the organs as human beings and will have artificial intelligence. It can learn from the environment using Neural networks and can make decisions using Fuzzy Logic and Decision Trees. Some Artificial babies can become sports persons and some scientists. It all depends on the environment and learnings given to the babies by the customers. Can this imagination become reality? If yes, then what will be the value of a baby manufactured from the company? Is it in a million or a billion or even more? The answer is priceless because it is only imagination at this point in time. The take-away from this imagination:

There is no doubt that the financial services industry is in a period of technological transformation. There are a lot of statistics that highlight the potential risks of artificial intelligence (AI) and automation related to the job market. There is a prediction that one-third of the jobs in the financial sector are under threat due to the advances in AI and automation. Instead of viewing these emerging technologies as a threat, it is far more productive to view them as an opportunity to add strategic value to the business. Even an e-auditor can reduce human intervention but cannot remove human intervention.

Human intelligence also needs changes in thinking to adapt to automation and strike the right balance with Artificial Intelligence. The major problem with Human intelligence is that sometimes it is not able to list down the solution as a step-by-step process. For example, my mother is good at cooking and can make delicious food ‘n’ number of times with the exact same taste, but she is not good at documenting her recipes. If recipes are not there, then cooking cannot be automated. The solution for this problem is Algorithmic Thinking.

Algorithmic Thinking provides a data driven approach to come up with innovations. Historically, a ‘computer’ was a device that performed mathematical calculations. The word was used this way until the early 20th century. The study of algorithms and computer science has deep roots within the study of mathematics. This made human intelligence to adopt Algorithmic Thinking for solving problems.

One common misconception about algorithmic thinking is that it is the study of computers and requires an understanding of coding, programming, or the user of a computer. Algorithmic thinking does not require these – it is essentially being able to arrive at a solution to a problem via a series of clearly defined steps. It’s not necessary to have an understanding of technology. Human Intelligence needs to develop an algorithmic thinking mindset to solve a problem and it helps defining the problem clearly. In my above example about recipe for cooking, if we have the correct recipes then it is easy to automate the cooking .

To strike a balance between Artificial and Human Intelligence, our thought process requires changes. We should not consider automation as a threat but an opportunity, and adopt changes in the thinking process. Adopting the change in thinking process for Artificial intelligence will help us accelerate the evolution of automation.

Reference :

Re Imagining Customer Experience

Every one of us would have interacted with a banking institution either to open an account, request for a service, technical help etc. Banking experience has evolved from branch-based interactions to servicing most of the customer requests on a device carried by the end customer. Evidently, customer experience with a banking institution has come a long way.

Consumers of today’s world have embraced digital lifestyle completely.
Companies who can interact with consumers and offer personalized services based on their need are preferred over their traditional counterparts. Right from ordering groceries to planning an investment, consumers prefer more digital and personalized services.

Banks have now understood the importance of digital mandate and the need to acclimate quickly. Many of them have already made investments in Omni channel, particularly in streamlining transactions. To up the game further, banks are now looking at improving the personalized experiences being offered to their consumers, and deliver the right experiences to the right consumers. Interestingly banks already have the right data being captured in their system as part of user’s activity.

Solutions enabled by Internet of Everything (IoE) can help banks in this journey. With internet of everything, banking institutions are expected to do more. Banks are no longer viewed as a pure financial institute which supports online transactions, etc. Banks are viewed more as an advisor with respect to their investments, spending, planning, and so on.

Let us assume our banking applications have the following capabilities

Bank as an advisor

Today’s banking applications with the help of Analytics can leverage the potential of data captured as part of user actions and have the spending pattern analyzed for a consumer. With this information banks can alert a consumer about his missed payment deadline or cash not received on time etc. Furthermore, banks can advise end user with the options available and complete them with his response. These actions can either be completed in the form of an actionable alert or notification in their mobile app.  Banks are also expected to monitor the cash inflow and outflow and subsequently predict his/her periodic spending and advise the consumer about saving schemes or recurring deposit plans to meet their requirements.

Bank as an investor

Imagine we have a banking application which has the capability to invest on behalf of the user. The user can only act as an approver for the selected schemes. Banking application takes care of identifying investment schemes, selecting one of them based on user’s preference and suggesting the ones which will have better returns. Users can define limits for such investment schemes. Will it not be a great value added service to the consumer?

Bank as a Doctor

When we are talking about banking applications providing personal experiences, it cannot get more personal than understanding the health and well-being of its consumers and advising them. With the help of smart devices, banks can now monitor the key health indicators of their consumers and advice. Banks do have access to the spending data towards health reasons, and with this information banks can advise users on insurance schemes, suitable diets, doctor appointments, etc.

In essence, banks can no longer afford to be reactive in their approach and operations. Banks are expected to be proactive in their approach and alert the consumer about an event even before its occurrence or non-occurrence and plan subsequent actions. Banks are expected to plan investments, savings and even vacations for the user.

With the right data already being captured and with the help of solutions enabled with Internet of Everything, Analytics, etc. banks are already sitting on a gold mine. Banks will just have to embrace the new order and change the way services are being offered to their consumers.

Constant is the Only Change

“A customer is the most important visitor on our premises. He is not dependent on us. We are dependent on him. He is not an interruption of our work. He is the purpose of it. He is not an outsider of our business. He is part of it. We are not doing him a favor by serving him. He is doing us a favor by giving us the opportunity to do so.”

Scene 1:

Year 2002: India is a BPO Hub, the business terms for outsourcing mundane – repetitive, time consuming tasks to low cost resources. All peppy and youthful offices that operate in night shifts mostly, 5 days’ job and more than decent packages. You have catholic aliases, Lakshmi is Cathy and Deepak is Jack. These were of course true, but, to me, they were the only ones offering a job
Location, Mumbai, Call Center for an International Internet Service Provider (henceforth referred to as ISP)

Characters: Me as Call Center Agent, Unknown Customer

One Day, just another call:

ME: Thank You for calling ******* ISP. My Name is Dennis; you have reached the sign-up by phone service of ****** ISP. How may I help you?
Unknown Caller: My internet is not working; I need to get it to work.

ME: Of course Sir. You have reached the sign-up by phone service, I will need to transfer your call to the technical services.
Unknown Caller: I chose this option on the phone because this is the only option where you get to speak to someone human, even though your accent is GRRRROOOSSSS

Scene 2: Fast forward in time

Year 2018: Lots of things have changed in life
World GDP grew from 33 trillion to 135 trillion USD
Indian GDP grew from 0.4 billion to 2.9 trillion USD
2008 Lehmann happened
Technology disruption and magnitude of it was exponential.
Net browsing changed to googling
People moved on from cable TV to Netflix, from Walmart to Amazon
From downloading pics taking minutes to online streaming high definition movies

And me? Well, I grew a few pounds (may be feeeeewww), moved jobs, got married, had kids and …..

Character: Me again, but I am the customer this time. Got notification for the insurance premium renewal of my car (yeah, I have a car now). Saw the premium amount was a tad more than last year’s and was aghast as to how a depreciating asset (realize the irony when you try to impulsively resell your car), can be charged more premium than the year before. I desperately wanted to talk to someone and know the details. Tried calling the call center (the call center experience deep down) but got lost in a maze of IVR options. Then realized that there are new ways of interventions and tried the trending chat bot feature on the service providers web site.

Me (chatting): Hi, I want to know the details of my car insurance premium
Chat: Hi. Sure. I will need some details from you to help you out, are you looking for a new policy or existing renewals?

Me: Renewals
Chat: May I have your policy number please?

Me: XX/XXXX/XXXXXXX
Chat: Your renewal premium amount is Rs.XXXXXX.

Me: I want to know why this is more than last year’s premium.
Chat: I am sorry, I did not understand.

Ok, this is indeed technology and I tried what my customer did to me years back
Me (chatting): Hi, I want to know the details of my car insurance premium.
Chat: Hi. Sure. I will need some details from you to help you out, are you looking for a new policy or existing renewals?
Me: New
Chat: Hi I am Chandrakanth, your insurance advisor, how may I help you with your new premium?

In both the scenarios above, the business intends to deliver service to the customer on alternate channels of service delivery. The motive in both the scenarios is cost reduction and the business is investing in the latest available technologies and service options. There are 3 points that I would like to discuss about the two interactions described above, taking place more than 15 years apart from each other temporally.

Has the customer experience changed?

The technologies in use for the service alternatives were pretty in vogue for the reference time period. But in both the cases the customer is left with a foul taste due to the following few points:

Who / what is the prominent driver for the solution?

In either of the scenarios, if you take a closer look at the process definition, it has been tuned for immediate action for new business opportunities (Me, in sign-up by phone, focused on new sign-up, and Chandrakanth, who magically took over from the bot, spotted a new policy-related opportunity). It is obvious that the priority of the business is new acquisition which in itself is not wrong but it leaves the existing customers lurking between the IVRs and Chat responses for options.

Who is smarter?

The service providers have of course deployed smart solutions of smart business acumen, but the customer did outsmart (that includes me), the system in both of these scenarios. But the critical question that business needs to ponder over is that in today’s digital age, where customer is spoilt for choice and nothing is a monopoly, will there be enough persistence to bother about an insensitive service delivery system no matter how much technical alternatives you provide?

I started the blog with a quote widely attributed to Mahatma Gandhi, which I saw while waiting for my turn in the reception of a hospital. I was intrigued and wondered why Mahatma Gandhi (at his time and struggle) would quote on customers and business. So I “googled” and of course there is a contention on this quote being attributed to Gandhi. We can dwell on that debate in some other conversation but it is accepted largely that this is a pre-independence quote. So the fundamentals of “the customer being at the center of a business” are by no means a new-generation business geek’s discovery. It does not matter what technology we use to action our business models or the technology we build them around, it is very important that the solution is focused on the customer and the experience delivered each time, every time.