How Digital Wallets can help Banks

In my previous article, I had mentioned how Digital wallets are disrupting banks. Profitable retail banking operations such as credit cards are at risk from being disrupted by digital wallets.

From a strategy perspective, the best way to counter this disruption is to offer a digital wallet service as part of basic banking services to both retail and commercial customers.

Customer Behavior Shifts

The millennials are changing the rules of engagement for banks.. This generation was born with Internet and are tech-savy. They are more socially active online and need tools that reflect their digital lifestyle. Millenials prefer using technical interactions on mobiles over face-2-face banking interactions.

Millennials are willing to source multiple financial services from different banks - based on the banks digital capability. This implies that banks will now have to built newer digital platforms to cater to the needs of this new generation.

Digital wallets are being embraced by this new generation faster than any other demographic group. Financial crisis of 2007 has eroded the trust in traditional banking and assets. Younger generation are more willing to rent rather than own. This implies more dynamic & frequent transactions - where digital wallets have an advantage over traditional methods. Going forward, this trend is likely to continue and older customers will drop off.

While this generational shift represents a big challenge, it also offers the biggest growth opportunity for banks.

Strategic Implications of Digital Wallet

Millennials are technology savvy. Millennials generate huge amounts of data using smart devices. Banks need to make sense of this data. Post 2007 crisis millennials are trading down, deleveraging and seek long term financial planning.

To win the loyalty of this millennials, banks need to compete to offer customized services on time. A delayed offer is a wasted offer.

Use real time analytic tools on data gathered from mobile devices, digital wallets, social networks etc. can generate crucial insights on products and services that can be created & targeted to this generation. Banks can use this for instant feedback and look for spontaneous opportunities to offer personalized products or services in credit or investment services.

For example, if a customer receives a cash gift, bank can instantly offer investment products.

Tracking financial transactions - based on time, geographical location and social networks, and then running realtime data analytics on this data can also feed into marketing communications.
Instead of using traditional print advertisements or Internet adwords, Banks can create a multi-channel customized banking communication experiences. This will improve customer experience and provide marketing information to customers at a much lower costs.

For example, banks can offer foreign exchange services via the mobile digital wallets, when they know the customer is traveling abroad, offer travel insurance etc. (vs now waiting for the customer to call the bank for foreign exchange of currencies)

Realtime analytics of all financial transactions - based on time, geographical location and social networks also aids in fraud detection. Banks get know what is happening in real time.

Knowing the network of transactions occurring in real time, and the nature of transactions can prevent fraud from taking place. Fraud detection must go beyond historical data, and must combine with realtime data to analyze possible fraudant transactions and predict scenarios that can help decision making.

Digital data trails from different transactions, different digital systems - such as locational information, purchase history, and network of transactions will help improve risk analytics across risk types and business units; implement predictive risk management systems.

Understanding risks in real time helps banks comply with new regulations and offer risk weighted services.

Conclusion

Digital Wallets presents the greatest threat to traditional banks - but it also provides a great opportunity for new growth, lower costs and increase profitability by offering personalized services to customers.

Fintech Disrupts the Personal Cheque Book

When was the last time you wrote out a cheque? I asked few of my friends and relatives around. Almost all of them had a difficult time to recall when they last wrote a cheque.

As digital wallets become mainstream, the first casualty is the personal cheque book. Currently about 75% of consumers are using smart phones, it will be short time when users will completely stop using cheque books. The current trend lines points that by 2020, the percentage of bank customers using cheques will fall to nearly 0%.

If handled properly, this disruption is essentially a good one for the banks. When almost any kind of payment can be done electronically, Banks will save costs by eliminating cheques.

Figure-1: Digital wallets along with online eBanking tools such as IMPS, NEFT, RTGS (in India) are clearly is on way to replace personal cheques.

However, I don't think cheques will never go entirely extinct - at least in India. While it is technically feasible to make all payments electronically, there will be a small & shrinking set of customers who will still prefer to write out cheques - mostly out of pure habit or due technological challenges or due to fear of hacking. (My parents for example, will never get on to eBanking)

Eventually, digital wallets will replace all credit cards, debit cards and personal cheques.

Benefits for Banks

If banks can leverage this new technology, Banks can lower operational costs by eliminating branch operations of handling cheques and paying out cash.

Essentially banks will have to partner with digital wallet service providers or technology providers, and start their digital transformation into a pure digital online banking operations. This will help banks to lower operational costs and help compete with newer financial service providers.

How Fintech will Disrupt Banking Industry

The banking industry for a long long time enjoyed strong barriers to entry. It was difficult for new banks to start - licensing and regulation kept new entrants away. As a result banks enjoyed  low customer switching, which in turn, allowed it to earn high returns on capital over extended periods. Banks could easily get 16-18% returns.

Fintech  is now changing this industry. New Fintech startups are launching discrete banking products that disrupt that particular segment of banking services. For example, Digital Wallets is disrupting credit/debit cards.

Lets take a look at how Digital wallet is disrupting credit cards. In India, Digital wallets such as PayTM, Mobiwiki & others are at a stage where number of transactions over digital wallet will exceed the number of payments done on credit & debit cards.

The rise of digital wallets is changing the industry's dynamics. By 2017, more number of transactions will be done over digital wallets than with the older credit or debit cards.

As digital wallets gain preeminence, digital wallets can morph into credit cards, and offer credit to customers and even merchants who accept digital wallet payments.

Today most consumers who use digital wallets such as PayTM also use credit/debit cards to transfer money from their credit/debit cards to their wallets & having a credit card like facility available on their digital wallet will make them stop using credit/debit cards.

Digital wallets uses cloud computing and captures all the transaction data to analyze customer or merchant usages. Based on this transactional information, a credit score can be developed and against which loans or business lines of credit can be issued.

In short, digital wallets will completely disrupt and swallow debit & credit card business of the banks.

Hiring Analytics

Recently my wife asked me about hiring analytics. Though I am not into HR analytics, I had read enough of IBM Watson Analytics and Hadoop, Spark use cases and in my MS course in Texas A&M, I had studied Neural Networks - and I had wide range of data to talk about Hiring Analytics.

So, I could wing it off in a discussion and I decided to write what I said in this blog ( My Wife's suggestion to blog this)

Why use Analytics for Hiring?

In today's fast paced economy, companies tend to hire people with relevant skills from outside. For example, a bank is willingto hire a business analyst from a manufacturing sector - rather than train a banker in analytics.

In short, hiring is critical to build capabilities quickly. Therefore it becomes important to hire employees who can meet its requirements and fit into its corporate culture. There in lies the challenge: "How to hire someone from outside - who has relevant knowledge needed in banking and who will fit in with the existing corporate culture."

This challenge can be solved by using data analytics during the selection process.

Today, every individual creates tonnes of digital data and also leave a wide digital trail behind. By looking at this digital data trail, and other digital data, one can develop fairly sophisticated analytics tools for hiring.

The two most popular tools in Hiring Analytics are:

1. LinkedIn Talent Solutions 
   Ebook on using LinkedIn Talent Solution can be seen here:
   
2. IBM Watson for Hiring 

The benefits of hiring right candidates are well know: Will more likely perform better and stay longer.

What goes into this Analytics

Hiring Analytics works best when we use standard verifiable Biometric Data - things that can be verified:

• How many jobs the person had till date?
• How long they stayed in those jobs?
• How many promotions they had? 
• Level of Education?
• Photos of the candidate on Internet.
• Industry relevant skills?
• Public records.
• Frequency of continuous learning and development.
• Affiliations to various organizations - cultural, political etc.
• Cultural Background

In addition to basic resume, Data from Social media: Facebook, Twitter, and LinkedIn are used for this analysis. The Business insights from this analysis can provide insights on candidate sentiment on various organizational factors such as productivity, business growth, or other objectives.  

For a particular role, say for example a system architect, a company can then set a basic set of requirements which defines the basic talent pool. Once this requirements are collected, automatic tools from Monster, LinkedIn etc. can be used to scour through millions of profiles and each matching profile, all the relevant data points can be collected and modeled or numerically analyzed with various analytics tools - Sentiment Analysis using MapReduce, Skill level analysis using Recursive Neural Networks, Cultural fitment analysis using RNTN etc.

The results of this analysis can then be used to short-list a set of potential candidates from a large pool of potential candidates.

During the interview process, further information regarding the candidate can be captured using a basic survey or psychometric tests or other testing tools. Data from these tools can then used to identify & rank candidate based on company specific parameters such as:

• Willingness to Join
• Time to Join
• Onboarding process
• Skills & training development needs,
• Retention schemes 
• Cost to Company, (level of Salary expected by candidate)

The main objective of hiring analytics is to automate hiring process as much as possible and provide hiring managers with necessary information about the candidate - so that they make the right hiring decision.

Apart from actual hiring, Hiring analytics can also be used on existing staff or new staff - to know the retention ratios and plan for future hiring as well.

Closing Thoughts

Information Technology is rapidly transforming hiring process. Industry had come a long way from the days of placing recruitment advertisements in newspapers. Today companies can rapidly analyze millions of profiles and short list potential candidates - not just based on key word search, but based on candidates digital data trails - which gives a bigger picture than just the standard resume.

Hiring analytics is still in its infancy and company is still taking small baby steps. The power of analytics is enormous. Technical advances in data-driven analytics is being used for hiring. Companies are adopting predictive analytics to make hiring decisions and HR strategies. Data analytics can be used for other HR functions such as attrition risk management, employee sentiment analysis, employee skill training plan development, etc.

Someday in future, the analytics tools will themselves find & hire the right candidate - with no human involvement.

Recall the movie "Gattaca" -where companies use DNA analysis to hire candidates!
While the technology for DNA analysis exists today - it is not used in standard hiring, however, I guess agencies like NASA, NSA, CIA may be using it today but in secret!

Future of Business IT : APIs

There was a time when one had to walk into a secure facility to access a computer - it was called as the mainframe era. Today all computing power is available on a mobile devices over the Internet via APIs!

Mobile Apps and Web apps rely on APIs to connect, communicate programmatically over Internet. Google's recent purchase of Apigee underscores the need for application programming interfaces in today's connected economy.  In this new world of mobile apps, APIs are used to connect different systems via APIs. The constant exchange of data between systems powers the app economy.

For example when you open a Flipkart mobile app and browse a particular product supplied by a vendor, the app  in your mobile interacts with retailer's catalog via APIs and retailers site will also gather pricing data and other shipping data from vendor's side via another APIs to provide you a complete picture.

In short, Data is the new currency in the App world! The data is made available over API.

The Importance of APIs

As apps proliferate, the life-cycle of apps can be as low as few weeks!

In such a short life-cycle, it makes more sense to use APIs to collect, collate, present information to users and also transport information back to main IT systems. In short, APIs become more than just an interface, the APIs are the central hub of the applications.

APIs make business processes simpler and smoother by connecting firms' customer-facing apps to different back end IT systems. For example, one can launch a web site with uses facial recognition API from Clarifi to authenticate users, and present stock data from Bloomberg over another API and enable trade with another API.

The ability to integrate multiple APIs to create a seamless user friendly services is the need of the day. APIs allows firms to expand into new markets that was not possible before. For example, a bank in Vietnam can offer global investment services via APIs - which was not possible few years ago.

APIs enable interactions/transactions between a business and its customers across multiple devices, apps, social networks, business networks, and cloud services.

A Growing Market for APIs

Today, it is estimated that there are 15K - 20K APIs. This will grow into several millions by 2020. The market for paid API could exceed $3 Billion in 2020.

The size of the market implies that APIs are no longer a novelty. APIs are becoming he preferred way to interact with IT systems, exchange information/data and thus build valuable new products in the app economy.

Its no wonder that companies like IBM is offering open access to Watson, its AI platform via APIs. This allows IBM to attract new customers globally and develop an unprecedented range of new services.

Closing Thoughts

APIs as not just a technical concept. It is the preferred way to offer new, valuable services. Soon APIs will be the only way customers will interact, and APIs will be the way companies interconnect and interoperate.

Fintech Needs High-Performance Computing

Newer Fintech companies are planning to disrupt financial markets. According to Accenture, the newer Fintech companeis are targeting ever faster settlement times.

To compete, current incumbents will have to match the turnaround time of the newer Fintech companies. In order to get to such fast turnaround times with existing workloads - companies will need High Performance Computing (HPC)

Historically, Financial companies have been first adaptors of advanced computing technologies such as Mainframes in 1960's Unix servers in 1990's. Today, activities such as high-frequency trading, complex simulations and real-time analytics are built on dedicated data centers filled with a diverse set of HPC systems.

These HPC systems are used to gather, parse, analyze and act on huge amounts of data - often several Petabytes/day. Having greater computing power increases competitive advantages in the market.

Let us see how HPC aids in building competitive advantages.

The only way for financial companies to address challenges is to use HPC solutions. 

Now, lets look at what constitues  HPC systems. 

From a hardware perspective, HPC systems has four components:

Market Outlook

It is clear that HPC provides competitive advantages to financial companies. According to IDC, total global revenue for the HPC market (including servers, storage, software and services) will increase from $21 billion in 2014 to $31.3 billion by 2019!