HomeData EngineeringData NewsBig Data – a powerful tool for the Finance industry

Big Data – a powerful tool for the Finance industry

Big Data has been garnering lots of attention recently, especially when it comes to the digital transformation of the world. Simply put, Big Data is a broad collection of finite information that is still growing exponentially on a daily basis. Data so huge is very complex to process and analyze, and as a result, the existing tools cannot be expected to process and store this effectively. In layman’s terms, it’s just average data that’s getting bigger and bigger.

We can now use this data to our advantage thanks to recent advances in digital technology.

A significant example where Big Data plays a vital role is the railway ticketing system. There are millions of ticket bookings and cancellations daily, and all such data transactions are recorded which can be used in case of future requirements.

Similarly, the Bombay Stock Exchange tracks and records hundreds of scripts every day so that the history of each company’s stock is available at the click of a button. All of these activities necessitate massive storage and processing capacities that must be fast, dependable, and inexpensive.

So, Big Data is a technology that identifies methods to monitor, extract, and analyze information from one or more large sets of data that are typically too complex to work with traditional data processing technology software.

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

Over the last few years, the Finance and Industry sector has benefitted greatly by using big data and AI (Artificial Intelligence) resulting in rapid advancements in the development of advanced digital machines, cloud computing, fraud detection, chatbots, and algorithm-based trading, and advanced predictive technologies.

Apart from being extremely convenient, the widespread use of internet-based shopping has increased online fraud. It is a source of concern in India and around the world. Banks spend millions of dollars (billions of rupees) to combat money laundering practices, and banks spend even more to reduce risks by implementing KYC (Know Your Customer) as a good practice.

Even in India, a large number of registered companies and millions of users have been victims of online financial fraud in some form or another. This is a serious issue because it discourages customers from using digital payment methods such as credit cards. This is where Big Data (combined with AI and Machine Learning – ML) comes in handy, as banks and other financial institutions can now evaluate large chunks of data at the same time and quickly identify and prevent fraudulent activity – in real-time – which is practically beyond human capacity.

Another industry now being benefitted from Big Data is the stock market. With AI and ML, traders now have access to much larger and more reliable data, which allows them to trade in the stock market more quickly. With technology, the systems track trends and continue to evolve so that traders can make informed decisions. Algorithmic trading (also known as automatic trading) is the process of defining trading strategies as a computer program and then using them to trade in the stock market with minimal human intervention. This results in a digital platform that can predict outcomes quickly and accurately. This increases the likelihood of entering and exiting a trade at the optimal time, increasing the likelihood of a profitable trade.

Big Data is also making an impact on customer service through Chatbots and Robo-advisory services. This is because they are available 24 hours a day, seven days a week, and can handle a large number of customers at the same time without making them wait – all while employing a small number of people.

Today, all major financial institutions, such as ICICI Bank, HDFC Bank, SBI Bank, ICICI Direct, Bajaj Finance, and many international banks such as Bank of America and JP Morgan Chase, have Chatbots that help the firms improve their customers’ experiences by increasing engagement, reducing downtime, and being available 24 hours a day, seven days a week. These enable the customer to pay bills, generate account reports, view recent transactions, and recommend suitable investment plans, among other things.

Many banks, including JP Morgan Chase, use bots to closely analyze legal documentation, greatly reducing the possibility of human error.

Big Data, aided by Artificial Intelligence and Machine Learning, makes the financial sector more secure, innovative, and agile.

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