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Harnessing the power of big data in the finance industry

Lately, there has been much buzz about Big Data, especially while referring to the world getting digitally transformed. In layman's terms, Big Data is an extensive collection of finite information but still growing exponentially daily. Such large data is so complex to process & analyze that none of the existing tools can be relied upon to process & store this efficiently. In simple terms, it's just an average data – but massive in size – that is ever increasing.

The current leap in digital technology has enabled us to use this data to our advantage.

Some examples of the use of Big Data could be the railway ticketing system. Millions of railway tickets are booked and canceled each day, and the data is captured & recorded for all such transactions to be referred for any future needs. Similarly, the Bombay Stock Exchange tracks & keeps records of hundreds of scripts daily so that the history of the stock of each company is available at the click of a button. All such activities require massive storage & processing capacities that should be fast, reliable & cheap.

So, Big Data is a technology that finds ways to monitor, extract & analyze the information from one or many large sets of data, which is usually too complex to work with the usual data processing technology software.

This technology is now successfully being used to benefit the finance industry (remember the example of Bombay Stock Exchange?), one of the first industries to take the most benefits from Big Data technology.

The arrival of big data & AI (Artificial Intelligence) in the Finance & Industry sector has resulted in fast-paced advancements in the development of advanced digital machines, cloud computing, fraud detection, chatbots, algorithm-based trading, and advanced predictive technologies over the past few years.

The widespread use of internet-based shopping has resulted in growing online frauds, apart from offering high convenience. It is a cause of worry in India and across the world. The banks spend millions of dollars (billions of Rupees) to fight Money Laundering practices, and to reduce the risks, the banks spend much more to implement KYC (Know Your Customer) as a good practice. Even in India, a large chunk of registered companies & millions of users has faced online financial frauds in some way or another. This is a serious problem because this makes the customers avoid using digital payment methods & credit cards etc. This is where the Big Data (combined with AI & Machine Learning - ML) comes to the rescue, as now the banks & other financial institutions can evaluate large chunks of data simultaneously and quickly detect and prevent fraudulent activity – in real-time – which is practically beyond human capacity.

Big data has also made an impressive impact on the stock markets. The traders now have access to much larger & reliable data that helps them quickly trade in the stock market. All thanks to the AI and ML. With the technology, the systems track the trends and keep evolving themselves to enable the traders to make a well-informed decisions. Algorithmic-based trading (also called automatic trading) means defining the directions as a computer program and then using it to trade in the stock market with minimal human intervention. This creates a digital platform that can predict the results quickly and accurately. This improves the chances of taking entering into & leaving from a trade at the right time to increase the chance of a profitable trade.

Big Data is also leaving an impression in faster customer service in the form of Chatbots and Robo-advisory services. This is because these are available 24x7 and can handle a large number of customers simultaneously, without making them wait – all this while maintaining a limited number of human staff.

Today, all major financial institutions, including ICICI Bank, HDFC Bank, SBI Bank, ICICI Direct, Bajaj Finance & many global banks such as Bank of America & JP Morgan Chase have their Chatbots that help the firms in improving the experience of their customers by increasing engagement, reducing downtime and by being available 24x7. These allow the customer to pay bills, generate account reports, find out the last transactions, suggest suitable investment plans, etc.

Many banks, such as JP Morgan Chase, also use the bots to closely analyze legal documentation – drastically reducing the chance of human errors.

Big Data, powered by Artificial Intelligence and Machine Learning, makes the finance sector safer, more innovative, and more agile.