While the whole world focused on mobile, internet, social media and rise of fintechs new innovations have shaken up the entire banking industry one more time. In 1970 to 1990, there was a big debate whether computers and internet shall make manual workers obsolete. And now there is a big debate on a large debate whether robots will make internet workers obsolete. By the way, debates are endless, and they shall continue. let us study best breed new technologies such as artificial intelligence, machine learning blockchain big data in this fourth segment. Let us now turn our attention to the use of new innovations such as art Official intelligence, robotics or say chat bots in banking.

Many times, banks struggle to identify the customer profile with gigantic data at its exposure. So use of artificial intelligence is very useful. And robots can answer many analytical questions. For example, what is the 360 degree view of my account? How is my investment pattern looking like? By the way Bank of America has created a virtual assistant call Erica to support customers over mobile phone.

Erica uses artificial intelligence, predictive analytics cognitive messaging to help customers to make payments check balances save money and pay on Deb's. She will also direct people to look for their FICO score and checkout for educational videos and other contents. Royal Bank of Scotland is developing a chat board called Lwe. To answer customers questions in near real time. This chat board uses IBM Watson cognitive tool, which means computers can learn as and when information changes. cognitive systems are designed to solve problems the way humans solve problems.

So how is it different from artificial intelligence? in cognitive computing, the system provides information to help experts decide whereas an artificial intelligence system guides experts on the best course of action to be taken. Artificial Intelligence using machine learning is a new fee for scientists and techies of banking sector, as well as technology review.com. JPMorgan will use machine learning to perform trade across all its global equities algorithm instead of relying on encoded rules developed by humans. The system called as a lo XM logarithm has learned from billions of past transactions on how to buy how to sell very fast and crucially at the best price. trials in Europe has showed that it really makes more money for them.

And also in banking, the entire credit scoring can be automated based on machine learning. These days, we also hear about blockchain concept using cryptography technology. And what is blockchain? blockchain technology in simple words can be explained as data entry done in multiple databases at a single time. For example, when a seller raises an invoice and a buyer, that invoice data can be stored in a database of a buyer database of a seller database of buyer banker database of seller banker database of any related government agency and all of that at a single time. Moreover, this transaction is safe, transparent and can be encrypted so that no third party can intercept that.

In banking, this can be very well used for various trade finance type transactions, when there are multiple parties involved at the same time and it brings more trust within multiple stakeholders. To give some different financial services industry example, Australian security exchange called as a C has become the first major board or a stock exchange to announce the adoption of blockchain technology for its stock settlement activity. It is C will use cryptography to record shareholdings and manage the clearing and settlement of all equity transactions. This will enable you saving to the cost of operation, bring more transparency and reduce the need of intermediaries. Let's discuss about internet of things for banking. First of all, what is internet of things?

In layman's term, it is a machine to machine connectivity. For example, we shall have connected cars connected homes, connected malls. In other words, all the computers, whether they are at home or in mall or in bank or the wykel. They shall talk to each other and help the customer. For example, housewife do not have to worry whether in the current week she has sufficient grocery at home. In fact, home computers will notice that it will inform the shopping mall and then If we connect to the bank to pay on her behalf, everything truly automated.

And here banking may play a major role. And that's not only for payment, but also based on the radii data. banks can now give targeted offers advice and rewards to its customer. Previously in IT sector, we have seen large projects in data warehouse and business intelligence. Let's look at an important innovation used in finance industry called as big data. Now Big Data is analyzing terabytes of structured and unstructured data including text, numeric, digital, algorithmic, video, voice, data, etc.

And what is terabytes? One gigabytes is equal to 0.000909495 TV buys and take binds in ascending order can be defined as gigabytes, then comes Jimmy bytes, then comes terabytes and then it is terabytes. As per Ingram micro invoices.com. Big Data can be used in various segments of banking for example, fraud detection, compliance and regulatory, customer segmentation, personalized marketing and risk management. So, friends Bank of America is actually experiencing Big Data projects in various areas, for example, improving customer retention, improving time and accuracy of financial forecasting. Let's look at how wise biometrics is playing a major role in the life of people as well as banks.

Nuance Corporation developed voice biometrics application for BBVA bancomer recently, and this was to strengthen their pension system by improving the process of proof of life verification. This means a pensioner can easily identify himself with just a simple phone call and computer will recognize the voice. And that can be considered as an evidence that pensioner is alive. How cool is that for our grandpas and grandmas, isn't it? By now, we have seen many innovations in banking such as desktop or mobile based internet fintechs migrations, social media in banking, artificial intelligence, robotics, machine learning, blockchain, big data, etc. However, guns Someone stop at that fancy innovation names is that what makes a dying fully digital?

Absolutely not. CEO of a bank has a huge task for enabling entire digital landscape at the front end as well as at the backend. A typical mid sized bank in US may have anything between 500 to 900 different IoT applications, and the amount of interactivity with changing technology landscape is a mammoth task. In the next segment, we shall see few glimpses of illustrative areas which may impact our digital world.