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Stealing Some Magic From Retailers

My last post talked about a recent project to set customer-level limits for a major European bank. By understanding activity from across a range of products, the bank can better assess the degree to which it's willing to lend and how to allocate available credit between different products.

This is an important step in understanding overall credit capacity. In so doing, part of the modeling exercise is to understand the likelihood of uptake for a given product. There is no doubt that a bank armed with this type of information could make better offers. But it still leaves open the challenge of making those offers at the right time and through the right channel.

The need to understand when to make a particular offer isn’t new to those in retailing. Retailers, especially those with access to transaction data, are familiar with the challenge of anticipating both if and when a customer will make a purchase, and what sort of incentive, if any, might be needed.

Banks, of course, have access to data on customer spending too. Credit card accounts and deposit accounts (especially in markets where consumers use them to automatically pay a variety of bills) could provide substantial visibility. While it isn’t the product-level detail that the retailer has, there's the advantage of breath across many different retailers, and insight into inflows as well as outflows.

The analysis of this data can provide deep insight into the financial condition of the customer, which in turn can help drive smarter product offers and product design.

Overall, credit assessment is a good staring place to understand what is good for the bank. But the smartest banks also need to understand what is best for the customer. 

Creditors, for instance, need to make more compelling offers than "Do you want another credit card?" Many of the most desirable customers don't want another card. They want the right card or set of services for their financial situation, lifestyle and goals.

Banks must also become more innovative if they're going to make inroads into the so-called "underbanked" population. Here traditional financial services face growing competition from services like PayPal and Google as well as startups such as PayNearMe, Green Dot and Netspend Holdings, all of which, through acquisitions or close partnerships, have one foot in retail.

The danger isn't only that these competitors are coming up with a slew of fresh ideas for meeting the needs of today's consumers. It's also that, through these services, they're collecting vast, rich data on how customers are spending their money.

To fully leverage their own data, banks should be implementing transactional analytics if they haven't already. They should be using them not only, as in the past, for fresher, deeper insights into developing risk, but for timely insights and event triggers that create opportunities to be of greater service to their customers.

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