Customers want a personalised services. To accomplish this, data is key for banks. The big question that remains is how to optimise the flow of big data. How to structure data that enables insights, That generate revenue and lower operational costs.
The banking industry deals with large amounts of data. This info is spread out between systems, or silo’s, and different tools. Because of this info is not centralised, there’s no single customer view that can be used to gain a full understanding of customers' expectations and needs.
Unorganised client data leads to failing customer service and incomplete info leads to missed sales opportunities and loss of revenue. This inefficient customer service also generates higher operational costs.
Big data helps mitigate risks and detect fraud. Calculating risk by collecting info on the customers capital, interest payments, lifestyle, and more. This way it helps you to offer the best formulas with the lowest risk.