Big data has been one of the tech industry’s most popular buzzwords for a few years now. But as the number of data sources grows and technology to process it becomes more powerful, the trend is changing from a nice-to-have addition to becoming an essential part of any company’s offering.
In the banking sector, there’s an expectation that this technology could fundamentally change how firms make decisions and interact with customers. Indeed, some banks are forecasting that it could affect how they operate throughout every part of their business. For example, Marco Bressan, chief data scientist for BBVA, explained last year that the financial institution (FI) has reorganized itself to more closely resemble a software company rather than a traditional bank, in order to fully take advantage of the potential data can provide.
So what does the implementation of big data mean for everyday banking activities, and how can companies ensure they’re using the technology in compliance with legal and ethical considerations?
For the banking sector, one of the most appealing promises big data holds is its ability to transform their fraud detection and prevention activities. For instance, big data offers banks the opportunity to delve much deeper into customer behavior with activities such as pattern analytics in order to spot red flags that are outside the norm.
The amount of details banks now possess on consumers’ transaction histories – how much they withdraw and deposit and when, what they spend online, whether they apply for loans or other services, etc – can be used to build a complex picture of their habits. With the right algorithms, unusual activity can be flagged and analyzed much faster than in the past.
This allows banks to assess the transaction and have their systems accurately determine in real-time whether to allow it, or request further information to validate it is the genuine customer. It could also decide to decline if it likely to be definitely fraudulent or if the further authentication fails.
As well as minimizing the risk a fraudulent transaction will be allowed, it can also greatly cut down on the risk of a false positive, where a legitimate, if unusual, transaction is declined. This is something that can be immensely frustrating to consumers, so big data has the added benefit of providing a smoother experience, even if it is invisible to the end-user.
Enhancing the customer experience
More accurate fraud detection is only the tip of the iceberg, however, when it comes to improving the banking customer experience. With so much personal data now available to companies – ranging from demographic and location data to in-depth purchasing histories and social media data that reveals what people are really thinking – the possibilities are almost endless.
Using this to craft more personalized offers and messaging is often one of the first use cases for insight gleaned from this data. Delivering information about services they have been proven to have an interest in not only makes customers feel that their needs are being met, it can also have a direct impact on a bank’s sales performance. Personalized offers can be less intrusive than non-targeted advertizing, yet have a much bigger impact.
But it’s not all about selling. Using big data to build a complete, 360-degree of customers helps banks gain a much better insight into what drives and motivates them, enabling them to change their services accordingly. Understanding what motivates people to adopt a particular service, or get in touch via a certain channel, gives businesses vital insight into where they should be focusing their resources.
Predictive analytics can also be used on a wider level to spot customer trends and alert banks to changes in the market before they occur. This allows them to be proactive rather than reactive when making decisions and can give them a clear advantage over slower-responding competitors.
Putting customers first
However, with so much more personal data being collected, stored and analyzed by FIs, this will inevitably raise questions about how this data is kept secure, and how banks ensure that their customers’ privacy is being respected.
One of the first things that all banks must do is ensure they are communicating clearly about what data they are collecting, and exactly how this will be used. Javier Ruiz, policy director at UK-based privacy advocate body Open Rights Group, told Banking.com that there needs to be a public discussion about the ethics of increased use of personal data – particularly if banks are looking to incorporate non-financial data into their decision-making.
For example, many companies view social media data as a potential gold mine when it comes to learning more about their customers’ preferences and being able to offer more personalized services. But careful considerations will need to be made about the ethics of this.
“Banks should be clear about exactly how customers will benefit from sharing their data rather than vague claims about improving services,” Mr Ruiz said. “There is also an issue about whether customers will feel compelled to hand over their personal data in order to access better offers from banks.”
He noted that the idea of ‘enhanced’ services being used as an incentive to persuade people to share more data is ethically questionable. “If a service requires more data to be delivered – say fraud prevention based on sharing mobile location data – that’s fair; but using data as a bargaining tool, when the service itself does not require it, is not OK.”
The changing regulations
As well as these ethical considerations, changing regulations related to privacy and the use of personal data will also have to be taken into account. This is particularly true for banks operating in the European Union, where the updated General Data Protection regulation (GDPR) will come into effect next year, bringing with it much stricter guidelines on how customer data should be handled, as well as larger penalties for companies that fail in their responsibilities.
GDPR will change some of the rules on profiling and automated decision making that are central to many aspects of big data analytics, but it will also alter the rights of citizens to access information held about them and be informed of what organizations do with their data, which is something the financial sector needs to be particularly aware of.
Mr Ruiz said: “The banking sector has very complex regulatory needs, including anti-fraud and money laundering obligations, and banks should prepare to provide more information to their customers.”
It’s clear, then, that the adoption of big data by the banking sector will not be without its challenges. For some, managing the competing needs of improving decision-making, maintaining customer privacy and meeting regulatory demands will be a fine balance.
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