Customer Journey Towards Digital Banking

The bank branch as we know it with tellers behind windows and bankers huddled in cubicles with desktop computers, is in need of a massive transformation.

Today. most customers now carry a bank in their pockets in the form of a smart phone app, and  visit an actual branch is not really needed. But banks all over the world are still holding on to the traditional brick-and-morter branches.

Though many banks are closing these branches. In 2017 alone, SBI, India's largest bank closed 716 branches!

Today, despite all the modern mobile technologies, physical branches remain an essential part of banks' operations and customer advisory functions. Brick-and-mortar locations are still one of the leading sales channels, and even in digitally advanced European nations, between 30 and 60 percent  of customers prefer doing at least some of their banking at branches.

While banks like to move customers to the mobile banking platform, changing customer behavior has become a major challenge. The diagram shows the 5 distinct stages of customer behavior and banks must nudge customers to go along this journey.

Four Key Aspects of API Management

Today, APIs are transforming businesses. APIs are the core of creating new apps, customer-centric development and development of new business models.

APIs are the core of the drive towards digitization, IoT, Mobile first, Fintech and Hybrid cloud. This focus on APIs implies having a solid API management systems in place. 

API Management is based on four rock solid aspects:

1. API Portal
Online portal to promote APIs.
This is essentially the first place users will come to get registered, get all API documentation, enroll in an online community & support groups.
In addition, it is good practice to provide an online API testing platform to help customers build/test their API ecosystems.

2. API Gateway
API Gateway – Securely open access for your API
Use policy driven security to secure & monitor API access to protect your API’s from unregistered usage, protect from malicious attacks. Enable DMZ-strength security between consumer apps using your APIs & internal servers

3. API Catalog
API lifecycle Management Manage the entire process of designing, developing, deploying, versioning & retiring APIs. 
Build & maintain the right APIs for your business.  Track complex interdependencies of APIs on various services and applications.
Design and configure policies to be applied to your APIs at runtime.

4. API Monitoring
API Consumption Management
Track consumption of APIs for governance, performance & Compliance.
Monitor for customer experience and develop comprehensive API monetization plan
Define, publish and track usage of API subscriptions and charge-back services

5 AI uses in Banks Today

1. Fraud Detection
Artificial intelligence tools improve defense against fraudsters and allowing banks to increase efficiency, reduce headcount in compliance and provide a better customer experience.
For example, if a huge transaction is initiated from an account with an history of minimal transactions – AI can shop the transactions until it is verified by a human.

2. Chatbots
Intelligent chatbots can engage users and improve customer service. AI  chatbot brings a human touch, have human voice nuances and even understand the context of the conversation.
Recently Google demonstrated its  AI chatbot that could make table reservation at a restaurant.

3. Marketing & Support
AI tools have the ability to analyze past behavior to optimize future campaign. By learning from prospect’s past behavior, AI tools automatically select & place ads or collateral for digital marketing. This helps craft directed marketing campaigns
Also see: https://www.techaspect.com/the-ai-revolution-marketing-automation-ebook-techaspect/

4. Risk Management
Real time transactions data analysis when used with AI tools can identify potential risks in offering credit. Today, banks have access to lots of transactional data – via open banking, and this data needs to be analyzed to understand micro activities and access the behavior of parties to correctly identify risks. Say for example, if the customer has borrowed money from a large number of other banks in recent times.

5. Algorithmic Trading
AI takes data analytics to the next level. Getting real time market data/news from live feeds such as Thomson Reuters Enterprise Platform, Bloomberg Terminal etc., and AI tools can use this information to understand investor sentiments and take real-time decisions on trading. This eliminates the time gap between insights & action.

Big Data Analytics for Digital Banking

Big Data has a huge impact on banking, especially in the era of digital banking.

Here are six main benefits for data analytics for banks.

1. Customer Insights

Banks can follow customer's social media & gain valuable insights on customer behavior patterns
Social media analysis gives a more accurate insights than traditional customer surveys
Social media analysis can be near real time, thus helping understand customer needs better

2. Customer Service

Big data analysis based on customer's historical data, current web data can be used to identify customer issues proactively and resolve them even before customer complains
Eg: Analyzing customers geographical data can help banks optimize ATM locations

3. Customer Experience  

Banks can use big data analytics to customize website in real time - to enhance customer experience.
Banks can use analytics to send real time messages/communications regarding account status etc.,
With Big Data analytics, Banks can be proactive to enhance custoemr service.

4. Boosting Sales

Social media analysis gives a more accurate insights into customer's needs and help promote the right banking products to customers. For e.g., customers looking at housing advertisements and discussing housing finance in social media - are most likely in need of a housing loan.
Data analytics can accurately acess customer's needs & banks can promote right types of solutions.

5. Fraud Detection

Big Data analysis can detect fraud in real time and prevent it
Data from third parties and banking networks holds valuable information about customer interactions.

6. New Product Introduction

Big Data analysis can identify new needs and develop products that meet those needs
Eg: Mobile Payment services, Open Bank APIs, ERP Integration gateways, International currency exchange services etc are all based on data analytics

Fintech & Rise of Digital Banks

All around the world, we are seeing a new class of banks: The digital banks. These fintech pioneers are redefining the banking industry by connecting with a new generation of mobile-first consumers.

Digital banks are an online only version of a normal bank offering Savings, Checking Accounts with payment, deposit and withdrawal services – but only through web: PC & Mobile devices.

Proving low cost banking services to a new class of customers: People who are highly mobile, tech savvy and unbanked!

Digital banks offer three main services:

1. Payment Gateways

• A seller service, often provided by e-commerce store or e-commerce enabler
• Authorizes a credit card or online transfer to merchants & businesses
• A virtual Point-of-Sale terminal for online businesses

2. E-Wallets

• Mobile App used to make payments to other mobile wallets
• Digital wallet can be set up to transfer funds to/from a bank account
• Popular banking tool for unbanked.

3. Remittances

• International Money transfers between individuals
• Nearly instant money transfers and low fees to lure customers away from traditional banks
• Uses Bitcoin or crypto currencies to avoid regulatory authorities

Digitalization of Banks and How Blockchain Helps

The core of challenges faced by banking industry today are: Time taken to complete a transaction, Securing customer and bank’s internal data, Compliance with regulations & Fraud detection & prevention.

All these challenges are essentially data & compute related. Once we understand the core data issues, solving them is relatively easy. Blockchain technology is a great solution to solve many of the current banking challenges.

Current State of Digital wallets in India

This article is a follow up to my previous blogs and revisit the impact of demonetization on small businesses and common man.

It has been 18 months since demonetization and surprisingly, at the street level, India still remains a predominantly cash economy. Only the major industries have moved towards a complete digital economy for a vast majority of their transactions. 

Indian digital wallet companies mainly consists of numerous startups such as Paytm, Mobikwik, and Oxigen Services, etc. These startups along with Airtel and Jio, the two major telecom service providers have played a major role in moving the Indian economy towards digitization and the industry has crossed Rs 12,000 crores of transactions per year in 2017!

While this is a significant number, year 2018 does not seem to be a smooth sailing and I suspect year 2018 will turn out to be a very tough year for digital wallets. 

What Changed?

RBI (Reserve Bank of India) imposed one major guideline for Digital wallet services to fulfill their KYC (know your customer) information & February 28, 2018 was the deadline.

This directive unnerved India's unorganized sector and refused to cooperate and many users were willing to move away from Digital wallets back to cash based transactions. As of march 2018, only 10% of the total customers in the digital wallets industry had submitted their KYC information (which was to link their Aadhar card with the account - by providing biometric information).

This implies that nearly 90% of existing customers were willing to walk away from digital wallets!

A 90% loss in customer base can kill the industry.

But on the ground, things are really not that bad. Though 90% of customers walked away, the total volume of transactions fell by 21.3% and the total value of transactions fell by 16.7% only.

This implies that there is a strong silver lining to the dark clouds and digital wallets companies can continue to grow only if they innovate and develop newer services.

Opportunity Ahead

As per information released by the RBI, the effect of demonetization was at its peak in January 2017 and the overall number of transactions via digital wallet during this period was reportedly about 295.5 million. Despite such a significant rise in digital wallet transactions, the percentage of transactions used for purposes of buying goods and services remained at just about 29 percent, at around 86.8 million transactions and only a minor percentage of all transactions conducted with digital wallets, was used for the purpose of purchasing goods and services.

Digital wallets has now become the first step in formal banking for a whole new generation of customers. For Several young adults, a digital wallet is their first bank account!

It is the nature of this India customer base, which results in such a high skew of the results: 90% drop in customer base results in only 16.7% drop in transaction value. This implies that most customers had very little transactions.

Small & kirana business have returned to cash

Small & kirana business, especially those in small towns and rural areas adapted digital wallets in the initial days on demonetization and now have returned to cash - mainly because of high transaction costs. PayTm charges 3% transaction fees to transfer funds from PayTm account to a regular bank account. 

Majority of small & kirana businesses do less than Rs 2000 of sales per day, and paying 3% transaction fees was unacceptable for small businesses!

eCommerce accounts for a tiny fraction of retail sales

eCommerce accounts for just 2-4% of Indian retail, and only 8% of Indian retail sales happens through organized retailers (such as Big Bazaar, Reliance Retails etc). 

This means that nearly 90% of retail sales is still happening over cash and there is a good opportunity for Indian Digital wallets to win them over - only if the transaction fees are eliminated.

Impact of UPI

UPI or Unified Payments Interface developed by the NPCI. 

The disruptive effect of digital wallets was met with a rapid and effective response by the banks; they quickly launched their own mobile wallets. SBI came up with SBI Buddy, HDFC Bank launched PayZapp, and ICICI Bank offered ICICI Pockets digital wallet - all powered by UPI. 

UPI permitted real time money transfer from one bank to another via mobile phones.

This new payment interface was not available in Digital wallets and that has hindered Indian digital wallets.

Future for Indian Digital Wallets

Year 2018 will be marked as the year of "crossing the chasm" for most digital wallet providers. Companies that can innovate and offer lower cost services (when compared to traditional banks), will ultimately win the battle against use of cash for transactions.

Indian Digital wallet providers must provide an alternate banking model that is affordable, transparent & help customers from financial standpoint.

In Indian context, Indian Digital wallet providers may also have to enable independent agents to work/operate as a human interface with whom customers can talk/call/interact when they have problems. A pure 100% online bank cannot win small business owners - many of them are not fully literate or knowledgeable in digital banking terms/technology.

Use of local agent also helps in onboarding new customers, getting their KYC details and initiating new customers into the world of digital banking.

Indian Digital wallet providers have to innovate beyond payment banks and offer a whole suite of banking services - either directly or via partnering with existing banks, while keeping a sharp focus on winning Indian small businesses and kirana stores. For example offer Peer-to-peer lending services (like Monex), offer investments services: Mutual Funds, Debt funds and government investment schemes etc.

Indian Digital wallet providers have to create a completely branchless experiences. Digital wallet companies need to move beyond mobiles and embrace web banking services and offer value added services - such as international money transfers: Global money remittances, insurance, GST filing, tax planning, etc.

Lastly, Indian Digital wallet providers have to embrace cash! Customers should be able to convert their money in digital wallets into cash without transaction fees.  Though this sounds counter intuitive, there are customers who need cash for their daily living - for example: to buy a bus ticket in DTC or BMTC busses, To pay traffic fines, To pay for postal stamps, etc. There are thousands of areas where government agencies do not accept anything but cash.

Closing Thoughts 

From a business perspective, Indian mobile wallets sector is currently fighting to survive and overcome its hardest phase. The industry has to innovate and continue fighting

I believe that the effect of the KYC mandate on the digital wallet industry is limited. Over the long term, the mandate will prove to be advantageous and enable them to be more competitive with the current banking systems. New innovations will solve the problems of interoperability between different payment banks, debit/credit cards and banks.

Digital wallet industry will emerge from this crisis stronger and better. 


Read more at:

https://economictimes.indiatimes.com/articleshow/62229424.cms?
https://inc42.com/buzz/mobile-wallets-drop-users-full-kyc-rbi/
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Ten Things One Should know about DevOps

DevOps has taken the IT world by storm over the last few years and continues to transform the way organizations develop, deploy, monitor, and maintain applications, as well as modifying the underlying infrastructure. DevOps has quickly evolved from a niche concept to a business imperative and companies of all sizes should be striving to incorporate DevOps tools and principles.

The value of successful DevOps is quantifiable. According to the 2015 State of DevOps Report, organizations that effectively adopt DevOps deploy software 30 times more frequently and with 200 times shorter lead times than competing organizations that have yet to embrace DevOps.

They also have 60 times fewer failures, and recover from those failures 168 timesfaster. Those are impressive numbers and define why succeeding at DevOps is so important for organizations to remain competitive today.

As the DevOps revolution continues, though, many enterprises are still watching curiously from the sidelines trying to understand what it's all about. Some have jumped in, yet are struggling to succeed. But one thing's certain — it's a much greater challenge to succeed at DevOps if your CIO doesn't grasp what it is or how to adopt it effectively.

HPE Server Platforms for Big Data Analytics

What will Drive Server Refresh

The Digital Workplace

Today's digital workforce demands a secure, high-speed Wi-Fi connectivity. Pervasive wireless access to business-critical applications is now expected wherever users work. Wireless LANs (WLANs) need massive scalability, uncompromising security, and rock solid reliability to accommodate the soaring demand. 

Embracing a mobile first digital workplace

Designing and building a high-performance workplace needs a wireless network, and the applications that run on them, is where services from Hewlett Packard Enterprise (HPE) excel.

With Aruba wireless technology can deliver a mobile first workplace which connects to Microsoft Skype for Business and Office 365, making the transition to a digital workplace a seamless process.  

The digital workplace enables people to bring your own (BYO)-everything with pervasive wireless connectivity, security, and reliability. This enables IT to focus on automation and centralized management. The mobile first workplace will be simpler to manage and maintain. 

Benefits include:

• Higher productivity with fast, secure, and always-on 802.11ac Wi-Fi connectivity

• Lower operating expenditures (OPEX) through reduced reliance on cellular networks

• Better user experiences  

• Reduce infrastructure cost in an all wireless workplace by 34%

• Increase business productivity

• Reduce hours spent on-boarding and performing adds, moves, and changes

Artificial Intelligence is the core of Fintech

As an expert in Fintech and big data analytics, I had to write this blog - which is essentially a transcript of my talk in Hewlett Packard to group of very talented & experience folks.

Big data is THE enabler of artificial intelligence. Financial industry generates a whole lot of data and this data forms the basis for powerful analytical tools that use Artificial Intelligence technologies which automates a whole lot of decision making.

What is AI?

At its highest level, Artificial Intelligence is an intelligent technology that leverages historical data and applies what is learned to current contexts to make predictions. AI combines various related terms: machine learning, natural language processing, deep learning, predictive analytics, etc.

Fintech & AI

In the current era of digitization and customer empowerment with mobile Internet, Banks and financial services companies are coming under intense pressure to compete with new age Fintech companies.

Fortunately, big banks and financial firms have huge amounts of customer data this can be leveraged along with newer tools to create & deliver exceptional and memorable experiences using technology.

After decades of research in AI technologies, AI is ready for prime time. According to a report by AI solutions market is estimated to reach $153 billion by 2020.

Today, AI is poised to become a key enabler of modern CRM solutions to Banks. Today many banks & firms use automated communication tools such as ChatBots to reach out to customers.

80% of executives believe artificial intelligence improves worker performance. 

Lets now take a look at these new tools and technologies.

AI:  One of the key technology trends upending the financial industry

Today's data-saturated world offers immense opportunities for financial institutions that know how to put this data to use by structuring it in the right way. As a result, an increasing number of financial institutions are adopting Artificial Intelligence (AI) to better serve their customers and increase their business growth. The explosive growth of structured and unstructured data, availability of new technologies such as cloud computing and machine learning algorithms, rising pressures brought by new competition, increased regulation and heightened consumer expectations have created a 'perfect storm' for the expanded use of artificial intelligence in financial services.

Artificial Intelligence with its advances in computing power, the ability to store and process Big Data, and instant access to advanced algorithms offers many opportunities for the financial sector. Harnessing Artificial Intelligence enables financial institutions to spot nonstandard behavior patterns when auditing financial transactions or to assess and analyze thousands of pages of tax changes. AI is destined to be the perfect tool to empower financial institutions' service efforts with genuinely intelligent tools to cut the time spent on handling lending requests, providing financial consultancies or opening bank accounts. Utilizing intelligent tools enable financial organizations to provide excellent customer experience across different channels. To remain relevant in a technology-driven world, financial pros will have to learn to combine their efforts with these intelligent tools.

Use cases of Artificial Intelligence in financial institutions

The financial sector is embracing Artificial Intelligence and machine learning to stay afloat and win over the digitally native customers. Harnessing the disruptive technology offers plenty of opportunities for financial institutions including: Customer support, transactions and helpdesk, data analysis and advanced analytics, underwriting loans and insurance, repetitive tasks and  performance, automated virtual assistants and Chatbots. Intelligent tools augment the capabilities of financial pros enabling them to easily identify customers' preferences and react with insight and emotional intelligence, which is essential for the development of meaningful customer relationships.

By leveraging intelligent tools, financial institutions and banks become technologically sophisticated and capable of meeting the financial needs of digitally savvy customers. Utilizing AI allows financial pros to analyze customers' buying patterns and red flag any irregularities and take preventive measures. Aienabled tools allow for making better risk decisions and conducting more accurate risk credit assessments.

Predictive scoring

Employing predictive scoring allows financial professionals to predict credit-related behavior, defaulting on loan payments, occurring an accident, client churn or attrition. Scoring backed by intelligence empower financial institutions to recognize creditors who will pay back a loan from those who will not pay based on the credit application's data. Financial pros can effectively apply scoring in forecasting of credit risk before granting a loan or when the loan is already granted.

Banks apply predictive scoring when forecasting the risk for a granted loan or when selecting optimal debt collection activities by assessing the credit related behavior.

Also See: 

1. Decision support with use of predictive models comparing to application of common sense rules or rules prepared by expert gives profit higher by 10-30%. 
2. 35% of executives say their decision relies mostly on internal data and analytics. 
3. By adopting an intelligent-computing program, some banks have experienced a 10% increase in sales of new products, a 20% savings in capital expenditures, a 20% increase in cash collections, and a 20% decline in churn. 

Computer intelligence with human touch

With the current virtual assistants (VC) and Chatbots revolution, along with the tremendous growth of messaging and social media apps, there is a great opportunity for organizations to optimize processes and deliver better customer experiences.

Chatbots are personal assistants that leverage messaging apps or outbound messaging and can run continual analysis of the information that is needed by the customer to ensure they get the relevant information through their preferred channel. Today's intelligent Chatbots and Virtual Customer Assistants can even take into consideration the context of the discussion and provide answers to several questions while analyzing the whole communication thread.

Natural language processing (NLP) is another intelligent tool for uncovering and analyzing the "messages" of unstructured text by using machine learning and Artificial Intelligence. It allows for providing context to language, just as human brains do. As a result, financial pros can gain a deeper understanding of customers' perception around their products, services and brand. NPL can be employed by customer service agents to more quickly route customers to the information they need.

Use Case: Nina, a customer service web-assistant developed by Swedbank, processes around 30,000 conversations focusing on 350 different queries each month. Nina had a first-contact resolution rate of 78% in the first three months of its operation.

Also See

1. The use of virtual customer assistants (VCAs) will jump by 1,000% by 2020. ()
2. The virtual digital assistant (VDA) market is estimated to reach $15.8 billion worldwide by 2021 with unique active consumer VDA users growing to 1.8 billion, and enterprise VDA users rising to 843 million.
3. Research firm MarketsandMarkets predicts the NLP market will reach $13.4 billion by 2020, a compound annual growth rate of 18.4 percent. 

Next best action for financial pros

Another benefit that AI offers for financial institutions is prescriptive analytics integrated with the next best action approach. Next best action is a customer-centric paradigm that considers various actions that can be taken for a specific contact and decides on the 'best' one. The next best action is determined by the customer's needs and interests on the one hand, and the business objectives and policies on the other.

Leveraging innovative technology can provide financial pros with recommendations about what steps they should take next to achieve a specified goal, such as the highest possible revenue or the highest level of engagement.

Utilizing the most innovative predictive decision-making technology can significantly improve the accuracy and effectiveness of financial activities. Through applying analytics, financial pros are able to better understand customer needs and drive higher customer value. Tech savvy financial pros are armed with the right tools to choose the most relevant and efficient process flow and ensure that an offered product or service meets the customer's needs.

Embracing intelligent tools allows financial institutions to focus on predicting customer behavior in order to drive value, managing multichannel interactions, and operating as an insight-driven business.

Utilizing predictive analytics to better understand your customers

Artificial Intelligence provides financial pros with the intelligent tool of predictive analytics that augments their capabilities to create exceptional and memorable customer experiences. Analyzing all internal and external customer data and converting it into actionable insights allows for not only providing real-time advice and solutions, but also anticipating future financial needs on a customer level. Banking analytics, combined with cognitive computing, provides financial pros with the ability to know each customer, provide customers with personalized offers, making one-to-one relationships a possibility. It accelerates financial institutions' ability to create individualized experiences for customers and realize tangible business benefits.

Applying predictive analytics enables financial institutions to:

• Deliver meaningful and emotionally satisfying digital experiences.
• Optimize product portfolio and enable numerous cross-sell and upsell opportunities to highly refined audiences.
• Convey personalized and relevant marketing messages to a specific audience at a specific stage of life.
• Create a complete customer view (360-degree) to personalize all customer touch points, while capturing digital data on a customer's preferences.

Also See:

1. 47% of organizations across industry now use predictive analytics to support business insight for risk purposes.
2. Artificial Intelligence Will Drive The Insights Revolution - Forrester
3. How is big data analytics transforming corporate decision-making?  

Closing Thoughts  

In the age of the customer and intelligent technology, financial institutions and banks are under increased pressure to pay attention to technological developments such as AI, and are quickly adapting to these changes. Intelligent tools along with Big Data offer financial institutions a huge opportunity to deliver exceptional and memorable experiences. Furthermore, Customer Relationship Management (CRM) solution backed with these sophisticated tools provide financial pros with the right blend of technology and human touch. An intelligent CRM solution ensures the complete view of your customers, keeping all their preferences and interests in the centralized repository accessible for financial pros, and enabling them to provide exceptional customer experience. With the AI-powered tools financial pros can exponentially enhance the customer journeys with more personalized approach. Embracing Artificial Intelligence is at the forefront of propelling the financial institutions through the digital age of the customer.

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Key Learnings:

1. Artificial Intelligence can become a success enabler of modern financial institutions

2. Computer intelligence use cases financial institutions can employ to become more
Customer centric

3. AI powered tools such as predictive scoring, advanced analytics, virtual assistants and Chatbots can help financial institutions and banks win over digitally native customers

Getting your Big Data Strategy right

An expert advice on what you need from big data analytics, and how to get there.

Business and technology leaders in most organizations understand the power of big data analytics—but few are able to harness that power in the way they want. The challenges are complex, and so are the technologies. Identifying and investing in key principles will help you navigate that complexity to find the right way to tap the growing pools of information available to your organization.

There are six main factors required to get a big data analytics platform right. Lets take a look at each one of them and explain how companies can get their big data right.

1. Blazing speed

Expectations around data are higher than ever. Business users and customers demand results almost instantly, but meeting those expectations can be challenging, especially with legacy systems. Speed is not the only factor in implementing a big data analytics strategy, but it's top of the list. Customers typically need to run queries on data sets that are 10 terabyte or larger and want results in few minutes.

Typical Business warehouse solutions would take 48 hours or more, In today's high speed business world, results after 48 hours is almost useless.

Time to insight is a top priority for any new analytics platform. Companies need to invest in High Performance Computing (HPC) to get the results in few minutes. With newer in-memory analytics systems  - such as SPARK or SAP HANA, the wait times can shrink to less than a second!

New solutions are fully optimized, enabling it to provide insights on time to fuel bottom-line results.

2. Scalable capacity

Today, It's a given that any big data analytics solution must accommodate huge quantities of data, but it also needs to grow organically with data volumes. Analytics solution must be able to grow in scale as the data size increases. Today, customers can't afford a "rip and replace" options when the database sizes grow.

Business needs a system that can handle all the data growth in a  way that is transparent to the data consumer or analyst - with very little downtime, if any at all. Capacity and computer expansion must all happen in the background.

3. Intelligent integration of legacy tools

Big Data Analytics must work with legacy tools so that business management can have seemless continuity. But it is also important to know which tools must be replaced and when.

Businesses have made investments in these older tools - such as Business Warehouse, Databases, ETL tools etc. Top management is comfortable with these legacy tools. But as data size grows newer data analysis tools will be needed and these new tools will have to work along with legacy tools.

4. Must play well with Hadoop

Big data and Hadoop has almost become synonymous with big data analytics. But Hadoop alone is not enough.While Hadoop is well known, it is built on generic low cost servers, it is also slow.

Hadoop, an open source big data framework, is a batch processing system, meaning that when a job is launched to analyze data, it goes into a queue, and it finishes when it finishes - i.e., users have to wait for results.

Today, Big data analysis needs to be fast - we are talking about high-concurrency in-memory analytics. Companies will still use Hadoop - but find newer ways to run Hadoop without incurring the performance penalties. Newer implementations of Hadoop (ver 2.7.x) and Spark will allow both systems to run in parallel.

5. Invest in data scientists

Organizations must build teams of data analytics experts. Not just hire data scientists, but also invest in tools that allow them to conduct more robust analyses on larger sets of data.

The key to move forward with best possible data analysis solution is to enable data scientists work with actual data sets and not a sample subset. The data analytics development environment must have the scale and size needed to work on actual data sizes, else the answers can go wrong and also leads to longer and more iterative development process.

6. Advanced analytics capabilities

Data Analytics tools and capabilities are rapidly evolving. Newer analytical tools use Artificial Intelligence (AI) tools as businesses move toward predictive analytics.

Big data has moved beyond reporting. Big data analytics is being used to answer very complex questions based on the data in your database. Analytics are now being more predictive, geospatial, and sentiment focused.

The shift toward predictive analysis and other advanced analysis has started. Organizations now—with the way data science has become more and more a corporate asset—there's definitely greater interest in becoming more predictive and more data-science savvy in nature.

Closing Thoughts  

Globally, data is growing at a very rapid rate: 40-50 percent per year. In this environment, every business is going to struggle against an overwhelming volume of data. New technologies are there that can help manage data at that speed and scale.

But having a right big data strategy is vital for success. As new tools, technologies emerge, it becomes critical to have the right strategy to incorporate them into the existing eco-system in a seemless non-disruptive way.

In this blog, I have highlighted 6 main aspects of a big data strategy that helps organizations to get its big data strategy right. 

How Automation will change the face of Indian Banks

Today, I had to visit a SBI branch near my house. I had three banking tasks: Deposit a cheque - which was a payment received from a Postal Savings account to the bank account; Transfer funds from the bank account to Public Provident Fund Account and update the passbook to know the bank balance.

This task in a public sector bank branch took nearly 60 minutes of my time, and I had to interact with 3 clerks and one service manager!

This experience made me think on how the upcoming digital transformation will change the face of Indian Banks. As an example, the same task that took me an hour today could be done in few minutes on a digital platform and without any human intervention!

Indian banks operating in conventional systems use tedious human oriented process. I need to fill out a form - where all information is filled out twice - one copy for the bank, one for me! The form is then verified by a clerk and then re-verified by a service manager, and then it takes 3-5 working days for money to move from one account to another!

With automation, 60% of jobs in bank branches can be eliminated. Traditional jobs like passbook updating, cash deposit, verification of know-your-customer details, salary uploads are also going digital increasing job redundancies. Most of the work done at branches will be done by IT systems, and Indian banks are at the inflection point where technology will rapidly improve efficiency and replace humans from performing mundane clerical jobs.

Banking sector was among the big job creators in recent years, but in next 3 years, Banking sector in India will see a decline in number of jobs. Just like ATMs that eliminated the need for bank tellers, new banking apps will eliminate most of the clerical jobs in any bank.

Not all Branch Jobs will be Lost

While I was at the bank, I two elderly gentlemen who wanted my help in getting a "service token!" These long time users of bank accounts are still not comfortable with using digital technologies. Even simple 'self service token generation' is a tough task for them.

India as a society is still not ready for a 100% digital banking. Lots of Indians are digitally illiterate, and the complex banking rules and forms intimidate them. Therefore these users still prefer to sit across the table with a bank employee and get their banking tasks accomplished.

Size of this customer segment is still substantial, but will decline rapidly. This implies that Indian banks will operate branches for a long time to come, but for banks to be relevant and profitable, the total value of transactions per employee will have to increase. This implies that a lot of back end jobs will have to be automated, and moving customers to digital platforms.

The nature of Indian customers has slowed down the transition from people-driven to IT driven processes. However, technological development has not slowed down and constant innovation in technology has made online banking easier. This has also led to a slowdown in the hiring of  branch staff at banks, though banks are hiring people with IT skills to drive automation.

HDFC bank for example, saw staff strength fall from 90,421 in December 2016 to 84,325 in the quarter ended March 2017. At the same time, it has expanded its network to 4,715 branches, from 4,520 a year earlier, ATMs to 12,260 from 12,000.

Hire Younger Talent

As banks brace for the digital revolution, Banks will have to infuse their workforce with a lot of younger talent - who are more comfortable in embracing new FinTech solutions. Large public sector banks will be forced to re-balance their workforce by offering voluntary retirement scheme for older staff and usher in a younger, digitally savvy talent pool.

Major Savings is in Backend Processing

Banks can save lot of costs by automating high cost operations such as loan processing. Today with high speed data analytics & AI tools almost 95% of loan requests can be processed automatically, thus eliminating expensive human labor - which also aids in speeding up loan approvals - which inturn helps improve productivity.

A team of 400-500 programmers can automate house loan approval process & that will eliminate 10000's of jobs at banks. Artificial intelligence & data analytics can replace loan underwriters, the IT systems can underwrite loans on the spot. This increases employee productivity in a big way, while reducing operational costs.

Similarly, routine tasks like salary processing will get automated. In fact all low-end back office jobs in banking sector will be automated.

This transformation means all the low skilled workers do not have a bright future! They will have to re-skill or perish!

Impact on Real Estate Costs

After labor costs, rentals on bank branches form the next highest costs for Indian banks. With Automation, the need for a large number of branches will reduce substantially. Some banks do not need as many branches as they have today.

Global banks like Citi, HSBC, etc have already consolidated the number of branches. Looking at the trend in US & Europe, where number of bank branches have shrunk by 20% in last 5 years, I expect a similar trend in India - but with a difference. The reduction of bank branches will be limited to urban areas only, while Indian banks will still add new branches in non-urban areas and the size of branches will reduce rapidly. Overall, I expect the total square footage of branch space will reduce 20-25% in next 5 years, while the total number of bank branches will increase.

Even in rural areas, Branches will need smaller footprints - and the focus in these branches will be to train customers to use digital online platforms. The branch staff will help customers learn and use digital systems - i.e., marry digital technology with human touch.

Changing face of Indian Banks

New banks like small finance banks like Au Financiers, Equitas or Ujjivan will use an army of  people to expand in rural areas, but this army of people will not sit & operate in a typical branch. Instead, they will be like foot soldiers, traveling to customer locations and providing banking services via mobile platforms.

Just like micro-finance companies & cell-phone companies that changed how people borrow, these newer small finance banks will change how people will use banking services. These banks can leverage a large army of small business owners in rural areas to offer human touch to rural customers - with digital platforms.  Customers can walk to any member of this rural service army and get their banking services.

Customers will now recognize the bank by the mobile apps, rather than the physical branches or the employees.

Closing Thoughts 

Banking sector in India will thrive in next 10-20 years and will employ millions. But it will not be the same way as today. Banks will expand branches and increase the reach of its distribution network, but it will be aided in a big way by IT.

New, exciting, & high paying jobs in Banks will be in IT as Banks transform to be a IT driven, software based banking services company.

The new face of the bank will be the mobile app - from which the entire banking transactions can be completed.

Also see: 

Disruptive influence of FinTech on Indian Banks

Disruptive influence of FinTech on Indian Banks

Indian banking & financial services industry has endured a tumultuous months following November 8th 2016 announcement of demonetization.

Banning of high value currency notes and the subsequent cash shortage and financial crisis is still taking their toll on banks. Indian banks were already under tremendous pressure due to bad loans and are now facing increased demands from retail customers. Many banks are still struck with slow & archaic online payments, with users needing to type in user names, passwords, 16 digits from the credit card and more. It is no wonder that the public trust and confidence in Indian banks is arguably at an all time low.

It is no surprise that consumers and businesses alike have moved enmasse to newer financial services which are enabled by FinTech!

FinTech is a catch-all term for the nascent revolution in the financial services space. Mobile payment systems that use technology and Internet platforms to offer a wide range of financial services. FinTech now offers a genuine alternative to traditional banking and payment systems offered by financial services firms such as Visa & Master card!

Indian customers & businesses are tired of the oligopoly of the state owned banks and duopoly of Visa/Mastercard in payments services sector.

Mobile payment systems offer an exciting, democratizing development which offers tools and services needed to meet the demands of vast majority of Indian small businesses and consumers. This denotes a major paradigm shift in banking and it will disrupt existing financial systems.

Disruption

Last few months post the demonetization, Fintech based payment systems in India - PayTM, MobiKwik, Freecharge, mPesa etc., have moved aggressively to get new customers and businesses, thus loosening the vice-like grip of banks & card payments. PayTM has made a huge splash in the 2016 and has changed the way consumers view payments.

Small Merchants in India have openly embraced FinTech payment services - mainly because of ubiquity of smart phones. More and more Indians are using smart phones, which enables banking and payment transactions to be completed electronically.

This transition to mobile payments also coincided with rapid adaptation of 4G data services.  In last 4 months alone, more than 125 Million users have taken 4G data services. This enabled rapid movement to digital payments. Rural businesses & merchants are accepting mobile payment through services like PayTM, MobiKwik,  UPI, etc.

Given the increasing usage of smart devices and mobile payment methods, there will be rapid growth of FinTech industry. I think in the near future we will see everything being paid for with our mobiles– for example paying Rs 10 for cup of coffee!

The movement towards mobile payment systems with newer payment companies using FinTech is just the beginning. Eventually customers will stop using credit/debit cards or cash, opting for mobile payments instead. This denotes the first move away from traditional banking transaction.
Given the increasing usage of smart devices and other contactless payment methods to complete transactions, business to consumer growth seems a natural direction for the FinTech industry.
In the next phase, people will start investing from their mobile platforms. Mobile payments systems will evolve to offer interest bearing investment opportunities - in form of fixed term deposits, Recurring Deposits or Mutual Funds etc., which can be accessed directly from user mobile devices.

As technology and consumer tastes continue to evolve, the market for financial services must keep pace, and learn to evolve. Newer FinTech companies will lead this new revolution.

Traditional banks, insurance & financial companies will struggle to change and adapt to this new paradigm. Banks in India will particularly find it hard to change because their customer experience management, based on legacy systems and legacy thinking, is lagging behind.

FinTech companies on the other hand have no technical debt, and they design the solution based on end user experience, therefore FinTech companies will have the upper hand when it comes to building better services.
  
Closing Thoughts

In the short term, FinTech in India will evolve & grow around the consumer banking space - with focus on consumer banking, making it easier for consumers to pay, and making it easier for small businesses to transfer money to other business entities. FinTech companies will unbundle banking & financial services and pick the 'cherries out of the cake', focusing on high-margin, highly scalable product and service areas, while leaving the commoditized or low margin services to banks.

Banks have the choice of either becoming 'platform utilities' or turning themselves into FinTech companies and building up their own FinTech ecosystems via various FinTech partnership and innovation models, and corporate venturing strategies.

The paradigm has shifted. The influence of FinTech is sure to be felt for years to come. Thanks to a perfect storm of changing banking rules, market forces and business cultures, FinTech has proved to be a disruptive force in Indian banking circles, a trend which looks set to continue well into 2020.

10 Best Practices for building Analytics based Organization

Business analytics is the key for decision making in organization at all levels. Startups and disrupters are using data analytics - both traditional BI & Big data tools for decision making, and in many cases, automating decisions. Yet, there are several companies that are yet to fully embrace data analytics.
In our opinion, here are top 10 practices that must be followed to transform any organization into a data driven organization.

1. Start with Top Executives
Top executives must be the first ones to adapt analytics. Once top executives embrace data analytics, the rest of the organization will follow. Organizations can jump start this process by hiring a Chief Analytics Officer, who can create a data driven executive teams at the top, and then guide rest of the organization in adapting analytics. This will enable an organic growth and will take time.

2. Start Analytics Project which impacts Revenue
The first of analytics projects that are taken up must have a strong connection to bottom line. The output of the analytics must be connected to revenue or profits or costs. Projects which have such a deep & big impacts will have a higher likelihood for making a business impact and for being successful. Early success is essential to take analytics into other parts of the organization.

3. Consider organizational implications
Often in older, legacy bound organizations, cultural issues are the hardest to overcome. Even with executive sponsorship and proof of concepts to illustrate the value of analytics, there will be reluctance to adapting new technologies. Start with communicating key accomplishments & push the analytics message and continue to evangelize. This will take time, but with patience it can be done.

4. Think about Organizational design
Organizational structures in legacy companies are not designed for analytics based workflow. Hence it becomes important to reorganize to take full benefit of analytics led workflows and business processes. Reorganization will also accelerate adoption of analytics in business operations.

5. Consider new talent from outside the organization
Though it makes sense to build all the required talent in-house via training, Legacy organizations may need talent from outside the organization to build analytics skills. Alternatively, one can also consider 3rd party consultants to help execute analytics projects and accelerate deployment of analytics.

6. Move rapidly towards deployment
Analytics are valuable only when it is deployed to make decisions. Proof of concepts are good, but will be useless if it is not deployed. This means teams must organize to execute around these analytics. Successful organizations build rapid deployment of analytics.

7. Take control of your Data
Data analytics needs strong data governance & stewardship. Data management, protection and data quality - which goes a long way in building a trusted data pool (or data lake) which then can be used for analysis.

8. Track Outcomes
Track outcomes of all data analytics projects. During the initial stages, there will be missteps, constant debate on what the right thing to do. Having complete transparency about analytics projects and its outcomes helps accelerate adoption

9. Invest in new tools & Technology
Data analytics tools are rapidly evolving. New tools are being released all the time - which brings in new capabilities to create analytic models, faster analytics and AI based automated decision making.

10. Rapidly Adapt advanced analytics
Advanced analytics such as deep neural networks, robotics & automation are rapidly maturing. The advanced analytics tools work on unstructured data, streaming data, and telemetric data. These new types of data analytics will transform organizations. 

Fintech - Success Factors for Innovation

As a technology disrupter, challenging an entrenched incumbent, Fintech products must be innovative solutions. But just being innovative is not enough - for example, developing a new way to make cashless payments is not enough. Success depends on several other factors.

There are three common factors behind every successful technology product. Working judiciously on these factors can create a successful product. Now, lets take a look at those three factors.

Factor 1. Think 10X

To be successful against an entrenched incumbent, one has to be truly innovative. One way to be innovative is to think 10X. For example, if it takes 120 seconds to make a payment with a credit/debit card, a cashless payment system must be able to do it in under 12 seconds! In the second iteration of the product, the transaction times must further decrease by 20% , i.e., under 10 seconds and so on.

10X factor must be applied to all aspects of business. For example, how can the business grow 10X in 1/10th the time taken by the incumbent?

Unless one does not aim high and deliver on it, customers will not switch to the newer technology.

10X formula in business forces one to rethink every aspect of business, and forces innovators to solve more complex challenges of tomorrow today, instead of incrementally solving today's problems.

Factor - 2. Be very agile after product launch 

"No Battle Plan Survives Contact With the Enemy"  said the German military strategist Helmuth von Moltke. The same is true when launching a new & innovative products. A product is always designed with certain assumptions and all those assumptions must be verified on the ground - when customers are using the product.

Product development teams must be agile to respond to the customer feedback, learn what works (or doesn't) and make changes rapidly in response. A smaller "beta" release helps to make rapid iterations of the product based on customer feedback and never stray too far from what market really wants.

There are no holy cows or egos to massage. If a feature is not liked by customer, be ready to drop it. Remember that the entrenched competition cannot move as fast as the challenger, and Agility is the key for success.

Factor 3. Share all knowledge

Collaboration is essential for innovation. Collaboration happens best when everyone shares information openly and discuss it freely. In case of Fintech, there are several points of data collection and this data & the analysis must be shared openly within the organization - so that the entire organization can act on that information & be agile.

Remember, innovation thrives in a culture of openness.   

Fintech - The Success Factors

In today's changing world, for Banks to remain competitive, Banks must commit to transforming themselves into fully-digitalised businesses and must operate like a true technology driven company.  

From our perspective, 10 key aspects that have defined success in Fintech companies that Banks needs to adopt -

1. Customer experience - Fintech companies constantly focus on improving customer experience and learn from every interaction. This is the mantra of success.

2. Digitalization - Create a "stretch vision" for digitalization blue print and make CxO's accountable for it. The "stretch vision" are based on what digital outcomes and it should not be constrained by digital interactions or by current technologies or by as-is scenario. These stretch visions should become inspiration for new innovations.

3. Technology is a key enabler – Fintech's are changing the world through agile platforms and new technologies. Banks must acquire new capabilities and technologies and need to invest in promising technologies. Banks must be willing to take on technology risks and bet on emerging technologies to build new parallel solutions/services - instead of the relying only on traditional ways of relying on "Tested & Proven" solutions.

4. Talent Management - Banks must invest on right talent, if needed on a global scale. Companies have to hire people from other regions/nations & en masse. For example, Indian banks should not shy away from hiring people in Silicon valley. Banks should note that they are hiring digital skills not industry experience. To succeed, hire the right talent and change internal staffing processes to do so – if required.

5. High Performance Culture - Success in new technology development depends on having the right digital talent. Key employees must be protected from "business as usual" attitudes and teams need to be built on high performance attitude. This implies changing existing HR polices,  benefits & operating models etc. For some banks, it makes sense to up a separate business unit that nurtures Fintech initiatives. This unit operates outside the "Traditional Banks" and does not suffer from traditional organizational hierarchies and limitations. in order to increase collaboration, productivity and "mind-shift".

6. Data driven decisions - Banks must shift their mode of operations from process driven to data-driven. Data analytics drives every activity and provides insights to decisions. Data analytics and modelling will have to continually evolve and keep adding to its value proposition. Banks must embrace live testing in Fintech as they adopt agile development and work in "live-beta" environments - in order to increase the pace of innovation and acceptability.

7. Create Eco-System through collaboration - Banks must build collaboration, partnership, and open transactions to succeed. This essentially calls for a big mind-shift as Banks now need to look at the entire ecosystem and collaborate with the best in the world to create a global value chain. New regulations impose these in forms but this a great way to successes and this helps compete/collaborate with startups.

8. Agility with Zero-waste attitude- Banks must learn to manage development projects like a start-ups with complete agile process. Along with agility, zero-waste based budget approach for technology development is key. All expenses must be aligned with the value creation and not based on effort spent.

9. Scalability – Solutions built must be scalable across the organization and value chain. This implies that all new technologies being developed must have scalability built into its core DNA and solutions developed may be able to rapidly scale for success. Startup fintechs today keep scalability as key requirement and don't face downtime issues. Banks need to fast track this process. For example, PayTM was able to scale up by more than 1000% in one month after demonetization in India seamlessly.

10. Challenge Status Quo - Banks must challenge everything. Status quo is not acceptable when dealing with Fintech which impacts all functions, products, business units and locations. Banks must examine & change (as needed) all aspects of the business: embracing both customer-facing and back-office systems and processes and be more innovative.

What is driving Fintech?

Fintech has taken the banking world by storm. Customers are embracing Fintech services rapidly and wholeheartedly. Digitization and Fintech is impacting all aspects of banking, investments & finance. Fintech's impact will be huge and will fundamentally transform the finance industry.

Today, I had open discussion with a bunch of managers at HPE, a group of really smart folks with advanced degrees from tier-1 colleges, on what is driving the rapid move towards Fintech and here is what came out of this discussion.

Digitalisation is a Mega trend 

Digitalisation is happening everywhere and is going far deeper than the cost-saving potential from innovative IT or even developing new revenue streams. Digitisation is fundamentally changing people behaviour.

Digitisation is being driven by three main forces

1. Customer experience
2. Technology enablement
3. Cost Savings

1. Customer experience

Customer experience is really driving Fintech adoption. Customers love the ease of using mobile, web for banking interactions - when compared to walking into a physical bank branches. The ease and the enhanced customer experience of using technology solutions over the good old way of interacting with banks/insurance/finance companies.

Customers are really pushing banks towards  digitalisation. Customers are the leaders in embracing Fintech and are dragging banks into it. Today, customers expect a seamless multi-channel experience - be it from a physical branch or on a mobile app, A consistent service levels that are of global standards.

Customers who got used to the convenience of Fintech are judging banks in how well banks are able to meet their needs. For example, it takes 8 distinct steps to transfer money online when compared to 2 steps in PayTM.

2. Technology enablement

Smart phones and Mobile Internet is rapidly influencing customer behaviour. The ease of connectivity with 4G technology and increased bandwidth has enabled customers to access technology enabled services.

Technology is no longer the realm of large banks and upper class. Customers of all social classes are now very comfortable using mobile, Internet technology and are using it everyday. During the demonitization exercise in India in November 2016, people from all walks of life started to embrace Fintech - right from street vendors, small shop owners, handy men like plumbers etc.

Technology has empowered people and people learnt to harness the power to technology to their benefit.

3. Cost Savings

Unlike technology developments of the past where banks embraced new technology to lower costs, today customers are embracing new technology to save costs for themselves. Customers are unwilling to pay the bank transaction charges for sending money or for loan approvals etc. Customers are using Fintech to reduce their cost of using financial services.  For customers there are two forms of cost savings - time & fees. Fintech provides both benefits, it lowers transactional costs to near zero, and gives instantaneous service which saves time.

Today, Banks are at a disadvantage with their high cost structures and customers are tired of paying banks for basic financial services. Hence it is cost savings to customers that is driving Fintech.

Closing Thoughts 

Fintech can cut costs by up to 90% while rapidly improving turnaround times.  Digitalisation customers to do more with their money and increases the velocity of transactions. This implies that banks need to evolve and rapidly embrace Fintech to make best use of it - allow customers to interact often, provide new innovative services and create better customer experiences. Else customers will move to those banks or new age finance companies that gives them what customers need.


To succeed in the world of digitalisation, Banks must develop a clear strategy that puts customers first - ahead of every single internal processes and costs. This may require redsigning current processes - while looking holistically at end-to-end customer experience, and must go beyond basic regulatory requirements.

The goal must nothing short of "total customer delight", and must traverse across channels for the customer - as a continuous engagement with customers across partners in financial services.