Big Data Use in Banking and Financial Services.

In the world of finance,when people talk about big data they are referring to large sets of diverse ( structured and unstructered) information that are also exceedingly complex.Such information is used to solve traditional business problems that have been faced by companies providing financial services and banking internationally.This term used to be only related to technology but now it's seen as a necessity for business,not an option.Financial services companies increasingly use big data to change to their processes,organizations and even the whole industry. 

Big Data refers to those extensive datasets produced through different mean such as businesses,Organizations, or individuals.It can come in the form of structured data like financial transactions and customer records,among others while unstructured ones include social media post,pictures etc.

A report from Markets and Markets says that the world's supply chain for big data will expand at a growth rate of 10.6% annually to hit $229.4 billion in 2025 from $138.9billion in 2020.This comes as a result of a huge surge in digital banking data.

Big data in banking and institutions is all about the Four Vs:

  1. Volume,
  2. Velocity,
  3. Variety
  4. Veracity.

What does it mean by "volume"? These refer to plenty of transactional details and consumer information and analyses.

"Velocity" could be intrepreted as how quickly such new pieces come in and are used for immediate and analyses.

"Variety" would involve different kind of data sets - from figures collected during sales promotions or seasons down to feedback received from clients after buying goods/services on offer.

Moreover,veracity matters most because this is where we ensure that our findings are based on credible sources which will help us make wise decisions.

These Four Vs are like the building blocks that help banks use big data to do cool things like personalized service,catching fraud, and managing risks.

How Big Data Is Revolutionizing Financial and Banking Services

The world is witnessing exponential growth rates of technologies alongside increased  production levels of information.These two factors have brought about radical changes across various industries as well as individual enterprises' operations.It is,however,the financial services industry that is at the forefront of this revolution since,by its very nature, it is expected to generate more data than any other sector,thus presenting unparalleled opportunities for refining analysis method while making them more productive through actionable insights derived from processed information.

1.Spotting Stock Trends in Real Time

Imagine having a super powered hunch about the stock market.Big data lets computers crunch vast amount of information to predict stock trends.This helps investors make smarter choices and reduces human error caused by emotions as biases.

2.Making Investment Predictions More Accurate

Big data is like having a financial crystal ball.By analyzing tons of data,computers can now give more precise predictions about how investments will perform.This helps make better decisions about their money and manage risk.

3.Understanding You Better to Serve You Better

Major financial institutions are now harnessing big data in order to gain entirely new insights about their clients. What this means is that they can predict what you're likely to want next,suggest products that you're actually interested in,and generally just make your banking experience better all around.

4.Fighting Fraud and Keeping Your Money Safe

Real-Time scrutiny of transactions using large datasets is helping banking organizations fight against fraud effectively; tehy are able to detect any unusual behaviour,such as the use of card in a different city from where it was taken without delay.This significantly safeguards people's assets held within banks.

Real-life Examples of How Financial and Banking Institutions are Using Big Data 

Mentioned below are the most common Big Data use cases in banking and financial services:

1.Customer engagement -AI is being used by big data in financial services to identify customers who have different spending habits based on demographic information such as age,income and location.This enables banks to create marketing strategies that are more personalized for each group of clients,thus making it the best use case of big data in financial services.

2.Risk Management : Big Data is financial services allows banks and other financial institutions to use predictive analytics models to better understand the risk associated with investments or loans by accessing large amounts of historical market data.They can then make more informed decisions about how many resources they should allocate towards particular assets or businesses.

3.Portfolio optimization : When constructing portfolios for clients,portfolio managers are able to take into account a number of different things thanks to Big Data.Some of these include asset allocation strategies,diversification methods and expected returns over periods.

4.Forecasting financial trends-Predicting financial trends in advance can hugely change how leadership deals with future activities .Taking the lead may lessen the impact of an adverse financial trend as opposed to being unprepared and simply responding to it.This can also put you ahead of your rivals .Protecting supply,demand, and other essential financial touchstones provides companies with data that they require when making decisions about their goods,services or investments.It additionally enables them to guide clients in making wise predictions based on probable models for financial management. 


The use of Big Data in banks as well as financial institutions paves the way for precise results,effectiveness and tailored customer service like never before.For instance,the ability to identify real-time stock trends is just one of the many ways big data has revolutionized in the industry;it also fosters better client interaction and prevents fraud thus ensuring heightened safety measures and prosperity among all players involved