Harnessing the Power of Big Data in the Financial Industry
There has been a lot of buzz around Big Data lately, especially with reference to the digital transformation of the world. Simply put, Big Data is a vast collection of information that is finite, but continues to grow exponentially every day. Such massive data is so complex to process and analyze that none of the existing tools can be used to process and store it efficiently. Simply put, this is just an average data – but massive in size – that keeps growing.
The current leap in digital technology has allowed us to use this data to our advantage.
Some examples of the use of Big Data could be the railway ticketing system. Millions of train tickets are booked and canceled every day, and data is captured and recorded for all these transactions to be returned for any future needs. Similarly, the Bombay Stock Exchange tracks and keeps records of hundreds of scripts daily so that each company’s stock history is available at the click of a button. All of these activities require massive storage and processing capacities that must be fast, reliable and cheap.
So, Big Data is a technology that finds ways to monitor, extract and analyze information from one or more large sets of data, which is usually too complex to work with the processing technology software usual data.
This technology is now being used successfully for the benefit of the financial industry (remember the example of the Bombay Stock Exchange?), one of the first industries to make the most of Big Data technology.
The advent of big data and AI (artificial intelligence) in finance and industry has led to rapid progress in the development of advanced digital machines, cloud computing, fraud detection , chatbots, algorithm-based commerce and advanced predictive technologies over the past few years.
The widespread use of Internet shopping has led to an increase in online fraud, in addition to providing great convenience. It is a cause for concern in India and around the world. Banks spend millions of dollars (billions of rupees) to combat money laundering practices, and to reduce risk, banks spend much more to implement KYC (Know Your Customer) as a good practice. Even in India, a large portion of registered businesses and millions of users have faced online financial fraud in one way or another. This is a serious problem as it saves customers from using digital payment methods and credit cards etc. This is where Big Data (combined with AI and Machine Learning – ML) comes to the rescue, as now banks and other financial institutions can simultaneously assess large amounts of data and quickly detect and prevent fraudulent activities – in real time – that are virtually beyond human capability.
Big data has also had an impressive impact on stock markets. Traders now have access to much larger and more reliable data that helps them trade quickly in the stock market. All thanks to AI and ML. Thanks to technology, the systems keep up with trends and continue to evolve to enable traders to make informed decisions. Algorithm-based trading (also called automatic trading) involves setting directions as a computer program and then using them to trade on the stock exchange with minimal human intervention. This creates a digital platform that can predict outcomes quickly and accurately. This improves the chances of entering and exiting a trade at the right time to increase the chances of a profitable trade.
Big Data also leaves an impression of faster customer service in the form of chatbots and robotic consulting services. Indeed, they are available 24 hours a day, 7 days a week and can manage a large number of customers simultaneously, without keeping them waiting, while maintaining a limited human workforce.
Today, all major financial institutions including ICICI Bank, HDFC Bank, SBI Bank, ICICI Direct, Bajaj Finance and many global banks such as Bank of America and JP Morgan Chase have their chatbots which help businesses to improve the customer experience by increasing customer engagement, reducing downtime and being available 24×7. These allow the client to pay their bills, generate account reports, know the latest transactions, suggest suitable investment plans, etc.
Many banks, such as JP Morgan Chase, also use the robots to closely analyze legal documentation, greatly reducing the risk of human error.
Big Data, powered by artificial intelligence and machine learning, makes the financial sector safer, more innovative and more agile.
This is a joint publication.
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