Month: June 2019

The Silent Disruption: Artificial Intelligence

by ICBlogs4 Comments on The Silent Disruption: Artificial Intelligence

It is said that human brain is capable of doing and achieving whatever it can think or imagine of. So what stops it from doing it? There are just two factors, access/availability of resources and time available in one’s life span in completing what can be imagined. AI is an attempt to finish tasks in a shorter span which brain may take longer to complete. This is possible by teaching machines over a period of time because life of a human is finite while of a machine is infinite hence continuity can be achieved by making machines learn.

Stephen Hawking once said that AI (Artificial Intelligence) could be the biggest event in the history of our civilization. We hear everywhere about work being done on artificial intelligence but is our understanding of the same is right?

Artificial Intelligence can be simply understood as:

  • A method which can help machines & its creators to function in an intelligent manner
  • Making machines intelligent so that they can think which is not natural hence artificial
  • Analyse data and share information for the decision makers to save take and take informed decisions

As some of the explanations suggest AI is typically any process/method which helps humans in acting efficiently and saves on time by eliminating mundane/routine job. Each one of us knowingly or unknowingly has adapted Artificial Intelligence in daily life.

Understanding AI

Let us understand in detail about AI and its layers:

Machine Learning provides system the ability to learn from data, automates the process of building analytical models. The learning from data could be of supervised, semi-supervised or unsupervised. So what does it mean? It means that machines categories the data into various sets (having some correlation, pattern, similar nature etc.). Supervised machine learning always has an end objective and it is suggestive in nature i.e. typical prices of a commodity may be used as raw data to predict the future prices basis historical trends and events.

Deep Learning may be called is a subset or next steps of machine learning which may be based on neural networks. Deep learning is capable of learning in unsupervised manner the data which may be unstructured or unlabelled.

The fundamental difference between machine learning and deep learning is the manner in which data is presented to the system. Machine learning algorithm always needs structured data while deep learning can handle unstructured data which relies on neural networks.  

If you are still not clear the below diagram shall clarify it:

Machine learning can make decisions bases on what it has learned. Deep learning has capability to create artificial networks to make decisions on its own without any past learning.

Natural Language Processing as the name suggest is capability of a computer program to understand languages spoken by humans as it is.

Computer Vision is a science field and integral part of AI which deals with dealing of computers with digital images and videos. This fields extracts all existing information from any image or videos and correlates it with real world situations. A typical example of the same is LBW decision making by third umpire in cricket where the projection of the ball helps in determining whether ball was to hit stumps or not. A 3D imaging from a 2D image, completion of a torn picture/scene recreation are other most used applications of this field.

Neural Network is series of algorithm to identify, analyse find out relationship between data in the manner human brain operates. The brain has neurons which have and transmit information to next neuron. Neural networks are mostly used in pattern recognition due to inherent ability respond unexpected inputs.

What’s happening today?

Most of the business across the industries i.e. retail, energy, financial service, automobile, technology, marketing & manufacturing have already started adopting AI in one or other business functions.  AI today is critical function to stay ahead of competition and succeed in business. This is evident from a research data published by Statista in 2017 enquiring businesses about the reasons they adapt AI. As per their survey 84% of the respondents answered that they are adopting AI to stay ahead or have competitive advantage.

Source: Statista

The large corporates are investing heavily in AI across the world. The underlying assumption is that it shall help in various tasks which shall help in reducing costs, provide humans and machines the efficiency, boost customer experience, boost returns from the business.

According to the market research firm Tractica, the global artificial intelligence software market is expected to experience massive growth in the coming years, with revenues increasing from around 9.5 billion U.S. dollars in 2018 to an expected 118.6 billion by 2025. Between 2018 and 2019, the artificial intelligence market is expected to grow by 154 percent, reaching a $14.7 billion market size.

While all the countries are focusing on AI, China and US are leading the terms of number of AI companies present and working of research and development in this sector. China is leading in deep learning reach as per a report published by White House, National Artificial Intelligence Research and Development Strategic Plan.

In terms of investment in the sector from 2013 to the first quarter of 2018, the amount of investment and financing in AI technology in China itself accounts for 60% in the world, valued at $27 billion in 2017. The numbers are as per a report published by Tsinghua University in September 2018.

In terms of investment in the sector from 2013 to the first quarter of 2018, the amount of investment and financing in AI technology in China itself accounts for 60% in the world, valued at $27 billion in 2017. The numbers are as per a report published by Tsinghua University in September 2018.

As per the study by EY and Nasscom it is predicted that around 46% of the workforce will be engaged in entirely new jobs that do not exist today, or will be deployed in jobs that have radically-changed skill sets by 2022.

In February 2019, it was announced by a minister that Indian Government is taking investment in AI seriously and planning to launch a national program on AI soon.

The critical factors:

All efforts being put in AI is dependent on data. A confidence level of an outcome of artificial engine is completely dependent on integrity and accuracy of the data used by the engine. Adaptability of AI is also completely dependent on availability of big data. Hence collection of data by all the business is priority today. The firms also need to focus equally on quality and integrity of data.

Apart from data the availability of skill set amongst people to develop, supervise and control AI research and development is essential. Large corporates are making it possible by hiring the best of talent in the market, re-skilling their existing employees.

How the future looks like?

While answer of the same is whatever can be thought be achieved as well. The movies have even shown extremes of AI where machines start controlling humans. While the same cannot be denied but at the same time cannot be digested so easily.

In today’s life we see usage of AI mobile assist, voice assist, auto computation of distance vehicle can run on fuel etc. These application with continuous development may take user experience/interaction from initial search levels to the next level in future.

Some of the typical examples may be as below:

Smart home devices may soon become integral part of our daily life. It is capable of monitoring our routine, respond to our queries and even integrate with our shopping needs. Recent generations (including mine) have already adapted smart watches, google home, Alexa which are tracking us 24×7. Amazon has already started the above application of AI through Alexa, where an item can be added to e-shopping cart by just telling Alexa. Though order placement is limited to adding orders in an app managed within Amazon’s ecosystem, it may soon integrate with popular local application for shopping.

Smart automobile can respond to riders on their queries. It can also connect with users emotionally basis historical behaviours. The precautionary measures can also be suggested by the devices.

The devises may be able to run diagnostic tests on itself and report malfunction in a particular component/part.

The above represents application of AI, where chat bots are able to understand language, interact with customer, accept applications, process basis client profile, accept/reject basis assessment result and adhere to policy requirement. It can also reduce lot of back end operations by completing routine tasks and also pitch for next level of relationship by assessing client profile more than what’s required for the product to be processed.

In financial sector application of AI has huge scope. Already many Banks, Insurance firms are deploying AI methods across compliance, operations, customer acquisition, fraud management etc.

AI in financial sector frees up humans from robotic tasks and enables them in focusing on better valued, complex and creative work.

Growth & the Control

Success of all the efforts in AI is possible when Governments, Corporate, Social Institutions focus on long term investment of data, develop a common understanding for data which is essential for development of AI. The future looking organizations need to promote skill development needed for them to grow. The re-skilling of existing human capital is critical for growth and to say competitive but knowing potential risk and its mitigation are equally important.

Majority AI programs suffer with a bias of their source who is developing them. These biases can be specific to individual, culture, organizations. All for profit firm shall always focus investment in AI which shall ultimately results in higher returns.

The sectors where governments may need to focus more are on healthcare, education, defence. Whether private or public whatever is the source of investment in AI, critical role here is to be played by Government in developing a culture, developing enabling policies which is conducive as well as adaptive. Stringent laws related to application of researches is needed. From time to time it is required that Government keeps assessing the existing policies to gain from the true potential of AI while keeping humans and humanity at the centre of decision-making.

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What’s this buzz about the Payment Banks?

by ICDid You Know?Leave a Comment on What’s this buzz about the Payment Banks?

The first thought of a payment banks intrigues most of the people as what’s big deal about it? Why do we need a bank which shall only facilitate payment, collection that too with deposit cap of INR 100,000? Why would anyone open account with any Payment Bank if they can’t offer loan when I need it?

For the ease of understanding it will be detailed in two parts i.e. background/regulation and potential/ future outlook.

It was sometime back in 2016 when RBI gave licences for differentiated banking licences in the name of Payment Banks (PB) and Small Finance Bank (SFB). Most of the so called financial experts criticized this move citing ailing condition of some of the domestic Banks whether public or private, when country already had differentiated banks i.e. Universal Banks, Regional Rural Banks, Local Area Banks, Cooperative Banks.

If we look at finer aspects/characteristics of a payment Banks, we find that most of the regulations are similar to a Scheduled Commercial Banks i.e. capital measurements, risk management (except credit risk which is not applicable given these Banks cannot participate in risk based products/instruments), Cash Reserve Ratio, Governance etc. The fundamental difference between a payment bank or any other bank is with respect to PBs not being allowed to undertake credit risk. This means, a payment bank cannot extend loans to its customers i.e. no personal loan, credit card, home loan, business loan etc. These Banks have to open at least 25% of their access points in rural areas and should focus more on technological solutions to on-board a customer and encourage online transactions.

The guidelines also restricts the investment classification and norms for payment Banks. These Banks need to deposit 75% of their demand deposit balances (Deposits that we put in Banks with premature withdrawal option) in Government securities or treasury bills eligible for Statutory Liquidity Ratio (SLR) maturity up to 1 year.

These Banks can’t even undertake para banking activities unless specified and approved by RBI. You may read more about para banking activities on RBI site by visiting https://m.rbi.org.in/Scripts/BS_ViewMasCirculardetails.aspx?id=9837

So do you think payment Banks make any sense in today’s world as they are restricted by even activities i.e. by placing money to give returns to the customers?

While my thoughts were not very different from critics when heard about this concept kept my hopes alive from these new age Banks give they could be my future employer as well .

Fortunately being part of a core team gave me the opportunity to work on a comparison between the two new types of Banks as well as the differences with a Universal Bank and analyse it better.

While as a common man we may feel that PBs are just one more type of Bank, the investors may look at it as another business opportunity. Many of us may have observed the rise in the number of wallet service providers and the reasons are changing payment behaviour of Indian consumers and opportunity in this space. While Foreign Banks got the concept of Credit Cards, Debit Cards in India, acceptability of electronic payments was limited given, a) Cash transaction behaviour promoted by buyers and sellers to evade tax, b) Non-availability of digital collection/payment infrastructure. Hence after series of events i.e. demonetization, stringent GST norms for small & large businesses and rise of service providers for digital money collection has given boost to digital collection and payment market.

This was the well thought of plan of having Payment Banks in Indian market to fill the gap that universal banks have not been able to. Directionally RBI and Government also want to have enablers in place to grow digital economy. The regulation asking payment Bank relying on technological solutions for payment, collections, transactions, access of accounts are evidence of the same.

Is payment bank a lucrative business model and can earn revenue? The answer is probably yes and below may be brief benefits and potential business area PBs may get into:

Zero Balance Accounts:

The consumers shall have advantage of opening a zero balance accounts and ease of operating accounts on technological advanced and simple platforms i.e. mobile apps. The penetration of mobile technology and network to the remotest area shall be a true enabler for this. Also these banks can offer higher interest rates given limited infrastructural cost which can be beneficial for both consumers as well as Payment Banks

Security and Ease of Access:

Most of the Banks today are ensuring that the transactions done on their mobile app are safe and secure by way of authentication of app at the time of installation and with pin/biometric at the time of login. Banks are also using OTP options selectively depending on transaction amount. Hence the transactions are considered to be safe unless either service provider does not ensure safety while developing app or the user does not ensure safety of their phone. Most of the applications installed on phone today ask for various permission, one needs to be mindful of giving permission against usage of the app.

The ease of access of Payment Bank is the biggest advantage. A bank having large distribution network/ customer touch points shall be able to serve maximum number of customers. These banks can also make local retail stores i.e. mobile shops, kirana (grocery) stores, courier agencies etc as their touch points where one can open account, deposit/withdraw cash as well.

While for population living in posh urban area of metro cities i.e. Mumbai, Delhi, Chennai may not find ease of access is a big differentiating factor, the people living in outskirts or slums of metros, tier 2 tier 6 cities may find this as a biggest advantage.

Fee based products:

The payments Banks can become distributors of Mutual Funds, Insurance, can have tie up with e-commerce sites and negotiate offers for their clients. They may also actively engage with corporates with cash intensive business, offer cash management solutions, payment gateway services etc.

Conclusion:

In Indian context where we’ve huge scope of eliminating cash and areas to payments and collection where digital disruptions are possible, payment banks are of great importance. Given nature of business these banks can do and with the set of target customers, it presents a good investment options for the new age investors as well. While Pay TM Payment Banks as on date has strongest presence in the segment it would be interesting to see how business of Airtel Payment bank, Jio Payment Bank (SBI being one of the investor) and India Post Payment Bank tread on this path and bring disruption in the way payments/collections are managed as on date.

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