How Big Data is Shaking up the Finance Industry

Ask anyone in banking, insurance or consumer finance, and they’ll tell you that big data is a key driver of innovation in the finance industry.

And that’s no surprise. Not only do these organisations collect huge amounts of data – from transaction histories to market information and demographic and behavioural data – but they’re also under pressure to maintain a competitive edge.

As smaller and more agile players enter the market, regulatory constraints tighten and customers become more discerning, many have no choice but to harness technology to stay in the game.

Let’s take a closer look at how forward-thinking organisations in the finance industry are using big data to get ahead.

Harnessing analytics to make smarter decisions

It doesn’t matter how innovative or bold your company strategy is – in finance if a strategy isn’t underpinned by big data analytics, it’s unlikely to deliver results.

Big data holds rich and high-value information that can help financial services companies identify where, when and how to invest to realise the greatest bang for their buck.

Forward-thinking companies are getting ahead by combining customer data, transaction data, market trends, competitor information and endless other data sources to pinpoint and exploit opportunities that will drive growth, customer retention and profitability.  In fact, big data analytics is now so important in the finance industry that a recent survey found that 89 percent of respondents believed those without an analytics strategy ran the risk of losing their position in the market.

Make objective, automated trades

The financial services companies leading the way in big data are under no illusions about the limitations of human emotion and bias. These companies recognise that the human mind struggles to make truly objective decisions. To deal with this, they’ve developed complex algorithms to execute trades on their behalf.

Automating trade decisions uses highly complex models to mine volumes of historical data and identify where the opportunities are to maximise portfolio returns.

By taking human emotion, bias and error out of the equation and news, media and market data into trading decisions, algorithmic trading (powered by big data) is a gamechanger for driving profitable returns.

Gain a deeper understanding of customers and their needs

Research shows that customers generally behave in predictable ways. When their patterns are analysed and understood by financial services companies, there’s enormous potential for financial services companies to tailor their business model to the specific needs of their customers.

Leading banks and financial service companies are investing in big data to understand their business:

• Who are our customers?
• When, where and on what do they spend money?
• How are they making purchases (e.g. ATM withdrawal, card payments)?

These questions and more can help companies to uncover powerful insights about their customers, and in response, tailor their offerings to optimally meet the needs and preferences of their customers.

This is win-win: customers benefit from interaction with their bank or service provider that closely meets their needs, whilst companies have more opportunities to increase revenue by having the right products or services on offer, knowing when to cross-sell or simply being in the right place at the right time.

On the compliance side of the equation, big data is also a valuable asset for improving fraud prevention, detection and management, supporting reporting and compliance obligations and informing risk assessments.

What next?

Whether you’re just getting started on your big data journey or you’re a seasoned pro, Antares has the expertise to help finance companies take their analytics capabilities to the next level. Learn more about our data architect services.