Success in today’s data-oriented business environment requires being able to think about how API, Data & Analytic concepts apply to particular business problems.
Data and data science can provide value in the context of Bank’s business & competitor strategy and to meet demands of customer experience.
He won’t need to print a coupon to redeem an offer, he’d just swipe his existing credit or debit card , and receive the discounts as a statement credit after he makes a purchase.
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However, matching this to previous card usage data or to purchases such as an airline ticket for future travel makes the pool of data available from within a bank highly sought after. Cardlytics essentially provides an offer-matching capability and mines card data on an aggregated basis to match merchant codes with offers that might be of interest to the bank customer. Here are some examples of the context of core retail banking products: 1.
This, of course, requires that the bank have a relationship with multiple merchants so that offers can be successfully served to a customer. Mortgage (at a potential home or with a realtor) 2.
Whatever bank or company operates the mobile-money system will be able to leverage the data for its own purposes (with the right partner, a bank, for example, could offer consumers discounts on a vacation to a favorite destination in addition to offering a savings account to let consumers hoard money for the trip).