Big data & analytics in the banking industry means lenders need to think like retailers
Shopping for small business loans has become an on-line activity. Big data and analytics in the banking industry have transformed it like many other on-line activities. Customers expect convenience, security and service. In addition customers expect the same quality experience whether applying for a loan in-store, on-line, or mobile.
For small business lending, consistency across channels is particularly challenging. Small business owners are a unique borrowing customer. Neither credit scores nor cash-flow analysis are clear indicators of risk:
Credit-scores: Often small businesses mix personal and business credit together, making it appear the business owner is carrying higher than normal debt.
Cash-flow: While small businesses have cash-flow, their ability to show cash-flow is related to how much the business owners pay themselves.
Therefore many small business lenders focus their in-store lending processes on learning about their client, understanding cash flows, and ensuring that the requested loan makes sense.
These activities require due-diligence and time. This drives up the unit cost of the loan. Given limited staffing, this also takes away from other business development services and activities.
Small-business lenders need to think more like retailers. They need to embrace the changes in their customers’ behavior. They need to use technology to combine the flexibility of being small with the scale of being big.
Operations. It should be no surprise that over the past decade FinTech players have created technology to streamline business loans for on-line customers. Big banks are now creating or adopting this technology for in-store and on-line customers. Small and mid-size lenders are also exploring ways to use similar customer relationship and credit decisioning technologies to streamline their operations.
Customer Journey. The next step is to recognize that the customer journey is neither linear nor limited to a single channel. Customers expect that their lender is where they are. If a small business owner starts an application on-line, she will expect that if she comes into a branch or contacts a call-center, she will be able to pick up where she left off.
Personalization. In addition small business owners expect their lender to personalize recommendations. An in-store experience with a lending officer will identify the right loan products for the small business. Small business owners expect that on-line and mobile experiences will also dynamically recommend loan products and identify prices that appeal and work for the individual business. Thanks to AI and analytics in banking, this is possible for any lender.
Technology. Vendors have created technology products right-sized for lenders of all sizes. Big data and predictive analytics in the banking industry can integrate the customer information file with data-science to gain customers and improve customer lifetime value. This allows lenders of all sizes to focus on the right customers, at the right time, with the right message and loan product.
Small business lenders can learn from retailers’ playbook – but there is a historical difference. Retailers initially transformed their strategy in response to competitor’s activities. Small business lenders must transform themselves in response to their customers’ activities.
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