One goal banks often have is streamlining their decisioning processes. Another goal is gaining new customers that were previously unattainable. These unreachable customers are called the underbanked and have limited experience with traditional bank products, and therefore lack full credit files, leaving banks wanting more information to determine that individual's creditworthiness. Streamlining processes while gaining these customers seems like a contradiction--the bank wants to approve customers that have little to no financial history. The processes to decision these consumers, therefore, seem like they would be anything but quick--the bank has to accept the application, check credit history, and then often, decline the consumer based on lack of information. However, by leveraging alternative data and automated decisioning, banks can assess the creditworthiness of underbanked consumers in realtime.
Alternative data can be incorporated into the automated decisioning process to evaluate underbanked consumers. The process is very similar to that for banked consumers where banks retrieve credit information automatically from traditional credit data providers. For underbanked consumers, information is retrieved from alternative data providers during the automated decisioning process. This allows banks to access information that will accurately portray the customer when traditional data is not available. This consumer segment will receive terms and interest rates directly tied to how responsible they have been with non-traditional financial accounts.
Alternative data is valuable because it provides information that credit bureaus do not receive. For example, credit bureaus record lines of credit, open accounts, and any credit history for the past seven years. Alternative data providers capture information on rental history, utility payments, insurance records, etc. As underbanked consumers show financial responsibility in areas other than traditional credit products, banks are able to make an assessment of an underbanked consumer's creditworthiness. This kind of data can be easily accessed, as stated before, with a connection to a variety of data providers. These processes are no more time-consuming than processes that use traditional data. In fact, the processes may be identical except for the source of consumer data.
When banks incorporate alternative data into automated decisioning, they and their customers gain value. Banks are able to access a new segment of consumers without increasing risk tolerance and underbanked customers receive product offers with rates that accurately reflect their past payment diligence and ability to repay new loans.
Alternative data can be used in automated decisioning to open up a wider customer base. Banks are able to accurately assess customers that have limited or missing credit files. Leveraging both automated decisioning and alternative data provides banks and underbanked consumers benefits by making the decisioning process more effective.
Kelty Wallace is a SEO specialist and copywriter at Zoot Enterprises in Bozeman, Montana.