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Credit Cards is a profitable segment due to the high interest rates, which is drawing Fintech companies that have already disrupted the high-fee cross-border payments market with low-cost alternatives. With the rise of wearables, IoT, Biometrics, Point-of-sale-finance, etc. the consumer now more payment choice than ever before.
It is vital that card issuers get every customer interaction and decision right to ensure they acquire & retain the best & most profitable customers. From acquisition marketing, underwriting, price/limit setting to customer management, rewards & collections strategy every moment matters.
Decision Science moves the focus of your business decisions to what matters most: Profit. This allows organizations to take a top-down decisioning approach and then working back to understand the tradeoffs between customer lifetime revenues and costs.
Direct Mail (pre-approve & pre-selected)
Online
In-branch
Approve vs Decline
Setting the Credit Limit
Balance Transfers
Contact Strategy
The increased profit & growth will come from 3 sources:
By making decisioning one applicant at a time, the business benefits from the extra revenue or lower losses
There are many possible decisions that a credit card issuer must address during a customer’s lifetime. These begin with acquisition targeting and may end with either retention activities or post-default recovery.
We will discuss how credit policy managers make many of these decisions. Our objective here is to showcase how a migration from traditional methods to a long term profit focus based on decision science optimization methods will deliver significant financial benefits.
All of these should account for an issuer’s risk appetite, access to capital, requirements to manage regulatory capital, and other locally imposed regulatory requirements such as stress testing and IFRS9. In addition, full-service banks may want to consider the value of credit card in the context of the entire banking relationship.
Freedom Analytics can offer solutions across this spectrum for credit card issuers. A deeper dive is provided here for the underwriting decisions and separately for limit management
In the case of underwriting, the amount of profit (or loss) is generated by the decision to approve and by the amount of limit to assign.
In the case of existing account management, the amount of expected lifetime profit can be increased by a periodic decision to increase or decrease a customer’s limit.
We will assume that issuers are capable of building or buying credit risk models that are fit for purpose. We will take profitable decision making to the next level with policy optimization.
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