3 ways the financial sector can use big data

Posted on November 30, 2017

3 Ways The Financial Sector Can Use Big Data

Australia has one of the most robust banking and financial services sectors in the world, with four of its banks among the world’s top 25 for being the safest.

The country’s financial services sector is the largest contributor to the national economy, contributing around $150 billion to the country’s GDP. The financial sector’s assets in Australia are worth $5.75 trillion, 4.5 times the country's nominal GDP.

With a vibrant banking and financial services sector, the amount of data that it generates is unsurprisingly mind-boggling. This can be gauged from the fact that, during a typical week, 27 per cent of Australians withdraw money from ATMs, 16 per cent transfer money to family or friends, and 65 per cent have electronic funds deducted from their accounts. And with such a high number of transactions constantly underway, an almost endless data trail comes with it.

The industry spends a huge amount to store customer data securely so it is only logical for the banks to utilise this treasure trove to enhance productivity, efficiency and security.

Here are three ways in which the financial sector can take advantage of the mass amounts of available customer data.

Categorisation of customers and offering personalised products

Each business transaction has a story. By analysing the data behind each of them, financial institutions can learn more about the spending and saving habits of people, their financial status, goals, and targets. This information helps to segregate customers into different categories. Based on these segmentations, the institutions can then design their marketing strategies targeted at each demographic. The result is a personalised product for customers that suits their needs better.

Forecasting customer behaviour

Effective analysis of the available customer data allows banks to forecast a forthcoming event and accordingly pitch a product. A simple assessment of a customer’s account can provide insight into their interests and what kind of a banking product would best appeal to them. Further, knowledge of customer’s personal milestones—like birthdays and anniversaries—allows the banks to increase customer engagement and to also offer them loans or other related products just when the customer requires them most.

Managing risk

Big data can help manage both technology (for instance, hacking and cyber theft) and financial risks, such as possible defaults and frauds.

The technology allows the banks to analyse and observe the transactions and behaviour of customers. Any unusual consumer behaviour raises a red flag and can allow the banks to preempt a potential cyber attack or data theft. The banks can also use the technology to observe the spending and bill paying patterns of a particular credit card customer and predict a possible default in future. As a result, they’re able to reduce their risk by controlling the lending to certain customers.

Leveraging big data involves re-thinking how and where the data is stored in a network. Customer data needs to be protected on all levels, so it goes without saying that securing it is the prime responsibility of the management. But beyond the security is availability. If services are not available to consumers who are so reliant on the convenience their institution conditions them to expect, the outcomes of a network outage can be hugely detrimental.  

So with the ever evolving nature of financial services and the increase in the depth and breadth of connectivity that customers demand, security, redundancy and scalability of network and cloud infrastructure will be where customers are kept, or lost.

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