We live in a world of online banking, fast credit approval, improved fraud detection and personalised service. Many of the almost constantly refined financial tools offered to us are owed to the development opportunities that big data affords the banking industry. Studying behavioural trends and consolidating them into useful information, big data plays a critical role in the future development of the banking industry and how it operates.
Understanding trends means grasping the needs of clients and allowing for changes and improvements in banking systems. This benefits the overall customer experience and builds a more positive relationship between the banks and their clients. The following is a list of three important ways that big data is changing the industry:
Optimising client offers
The first step to understanding how big data aids the banking industry in improving professional relationships with their clients is to unpack what it entails. Big data is, unsurprisingly, exceptionally large data sets that are analysed to reveal patterns, trends, and associations – particularly with respect to human behaviour and interactions.
In the banking industry, big data assists in supplying detailed information on clients, making it easier to provide more personal assistance. This information helps banks build tailormade plans that speak to the needs and preferences of specific businesses. Analysing patterns in set plans means that banks can assess situations in the future and deliver improved functionality to match client expectations.
Ian Carter, Divisional Executive of Corporate Bank Investment Transaction Services at Nedbank CIB, notes: “We are hearing more and more about Warm Digital, the convenience of automation when it comes to running a large corporate, but when something goes wrong or I need assistance with an out of the box matter, I want to pick up the phone and talk to ‘my guy’.”
Businesses that experience their banks providing them with automatic solutions for their needs – in addition to personalised assistance when needed – are more likely to give their bank favour and appreciation as existing clients. This also serves to attract interest of streamlined offerings from new clients.
Advancements of global internet use has simplified many industries but has unfortunately also made it easier for criminals to commit fraud. Every time banks plan a new way to prevent fraud, people discover ways to circumvent it. Normally, this would make tracking the person responsible a borderline impossible task. Luckily, big data provides a solution to this problem.
Through the use of analytics, financial organisations can find the difference between legitimate and fraudulent business transactions. Because big data is used for the purpose of machine learning, banks are able to identify customer history and pick up if there are obvious deviations from common behaviour. Alerts assist banks in suggesting appropriate action like immediately blocking irregular transactions before they occur.
By minimising the chances of clients experiencing loss and implementing instantaneous reactions from anti-fraud systems, businesses are able to trust that their financial welfare is secure. This, in turn, improves profitability across the board and maintains another pillar in the foundation for good client relations.
Big data provides banks with core insights into their client budgets, spending habits and patterns. This simplifies the task of establishing and understanding corporate needs. Tracked transactions allow banks to build a framework that categorises clients based on different parameters. These may include statistics like preferred credit expenditure, commonly accessed services, and net worth.
Once analysed, individual banking schemes can be drawn up accordingly and suggested to corporate clientele. When it comes to corporate investment banking, solutions need to be tailored to cater to individual requirements. Like other benefits born from the use of big data, customer segmentation goes a long way in fostering a healthier client relationship.
Although the systems that interpret large amounts of information may seem complex, the result is to offer simplicity to clients and optimise service. This is how big data is changing the banking industry and, using machine learning, will continue to offer streamlined solutions.
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