In the years preceding the financial crisis, banks, on the whole, had everything their own way. Regulation was loose, they could lend to pretty much whoever they wanted to, and there was next to no competition. Any customer who decided that they were getting a rough time of it was left with one of two options - like it, or lump it.
In the years since, this has changed. Maybe not as much as some would like, maybe more than some would like, but they have changed. A raft of regulation has been introduced, and in the UK, the government’s attempts to increase competition in the market have led to regulations which making it easier for customers to switch their accounts. This means banks must be more on their game than ever when it comes to customer service. There have also been a raft of newcomers looking to exploit the rise in online banking, such as Atom Bank.
The problems facing banking - customer dissatisfaction, fraud, increased competition, and regulations - are all issues that Big Data analytics can contribute to solving. Nearly every major decision to drive revenue, to control costs, or to mitigate risks can be infused with data and analytics.
In terms of customer service, analytics is enabling a hyper-personalized experience. It does this by allowing for more targeting - looking beyond traditional structured datasets and segmenting by transactional, behavioural and social data. The other advantage of this is that customers are more willing to hand over more information, as they feel they are getting something in return.
Risk management is one of the main ways in which analytics can be of help to banks. Keeping on top of the raft of incoming regulations is an exceptionally difficult task for a big bank in particular, and compliance requires a standardized model that can adapt to different territories and adapt to any sudden changes. Moreover, cyber crime is growing, and banks and their customers are some of the main victims. Big Data analytics can help spot vulnerabilities in the system, and predict where an attack may come from. It can spot any deviations in customer behavior that could indicate fraud. Big data technologies can also integrate external watch list screening systems and unstructured emerging data sources, such as geolocation. This should hopefully reduce the incidence of false positives.
For newcomers to the Fintech sector, there is an opportunity to exploit Big Data in a way that big banks can’t. The larger banks have to integrate new analytics technology with legacy systems that are often difficult to combine. Newcomers are far more agile and have been built with analytics in mind. Big banks do, however, still hold the advantage through the sheer wealth of data that they hold, but they will need to act fast if they are to leverage it to maintain their competitive edge.