The Role of Big Data in the Lending Industry
In order to reach fast and accurate decisions that will satisfy both lender and customer, a large amount of data has to analysed as part of the process. The introduction of big data analytics makes it easier for lenders to handle large, complex pieces of information to manage small loan applications that will lead to quick and insightful answers.
The role of big data in the lending industry will continue to increase as the technology advances and becomes even more affordable to businesses of all sizes. We explain how it is currently being used and some of the ways it is helping lenders to create a more efficient method of working.
Analysing customer credit history
The use of both big data and AI allows lenders to analyse and efficiently process large amounts of credit-related information to support their decision making. Every action related to repayments – such as paying on time, defaults etc. – can be recorded and assessed to make it easier and faster to decide whether or not to provide credit to an individual customer. AI plays a key role helping to evaluate future risk based on previous behaviour, which helps to protect the lender’s assets. All of these processes can be done instantly to dramatically cut down the decision time for both parties.
The rise of online fraud makes it more important than ever for lenders to tighten up their security. The use of big data and analytics allows the lender to have a clear view of a customer’s repayment history and overall behavioural payments when it comes to credit. If there is any sudden change it will raise an alert within the system which will enable the lender to quickly respond to any potential fraud taking place. The technology is already being used right across the industry and it will become even more commonplace as it evolves.
Matching products to customers
Big data provides access to a pool of information related to customer behaviour, which allows lenders to fine tune their products and services to meet the needs of their consumers. Combined with the use of AI, which will map out predicted behaviour, it presents an overall picture of each individual in a way that was never before possible. The technology can even be used to pull in data from social media platforms to understand spending interests, along with other products and services that may be useful to their lifestyles.
Risk management plays a crucial role in the success of any financial institution. The implementation of big data provides a way for lenders to predict market behaviour and to introduce robust risk-management tactics. The finance sector must comply with strict regulatory guidelines and this requires the ongoing task of analysing data and providing in-depth reports. The use of big data technology makes this high-level monitoring of information more manageable, while still remaining within the required legal boundaries.