FEE REFUND MANAGEMENT
The innovation relates to a system and/or methodology for the convenient and consistent determination of fee refunds for financial products. The system provides for a fee refund component that determines a proposed fee refund based on a customer's score, and information regarding the financial institution's fee refund policies. The customer scores and fee refund policies are determined by a data analytics component, which can update the data at regular intervals or when modifications to the data occur.
1 . A fee refund management system, comprising:
a data analytics component that determines at least one of a customer score, or a set of refund policies; and
a fee refund determination component that determines a proposed fee refund for at least one of a deposit account, an investment account, or a credit account based at least in part on at least one of the customer score or the refund policy.
2 . The system of claim 1 , the data analytics component determines the customer score based at least in part on a relationship between a customer and a financial institution, the relationship including at least one of the customer's account type, account balance, prior fees assessed, prior fee refund requests, or length of patronage.
3 . The system of claim 1 , further comprising a user interface component that exposes at least one interface that facilitates user interaction with the system.
4 . The system of claim 3 , the user interface component obtains at least one data field from at least one of a user or a data store, the data fields that include at least one of a customer identification field, an account number field, or a reason field.
5 . The system of claim 4 , the fee refund determination component verifies the data field by comparing a subset of the data fields against data maintained in a data store, and acquires at least one of the customer score or refund policies from the data store.
6 . The system of claim 1 , the data analytics component stores at least one of the customer score or the refund policies in a data store.
7 . The system of claim 6 , the data analytics component updates at least one of the customer score or refund policy maintained in the data store at a predetermined interval.
8 . The system of claim 1 , the fee refund component updates at least one of a customer's account data, the customer score, or the tracking data, based at least in part on a disposition of the proposed fee refund, the disposition includes at least one of an acceptance or a rejection.
9 . The system of claim 1 , further comprising an artificial intelligence component that facilitates automating at least one of: adjusting at least one of a set of account data, a customer score, a refund policy, or a set of tracking data, determining a customer disposition regarding a proposed fee refund, or determining an optimum fee refund to propose to the customer, wherein the optimum fee refund to propose can be a fee refund amount below the permissible refund amount that the customer is likely to accept.
10 . A computer-implemented method of fee refund management, comprising:
analyzing at least one of a customer score or a set of refund policies; and
generating a proposed fee refund for at least one of a deposit account, an investment account, or a credit account based at least in part on at least one of the customer score or the refund policies.
11 . The computer-implemented method of claim 10 , further comprising analyzing a relationship between a customer and a financial institution to determine the customer score, wherein the relationship based at least in part on at least one of account types, account balance, prior fees assessed, prior fee refund request, or length of patronage.
12 . The computer-implemented method of claim 10 , further comprising obtaining a set of refund policies, wherein the set of refund policies include a financial institution's policies regarding issuing fee refunds.
13 . The computer-implemented method of claim 10 , further comprising capturing a user input that includes at least one data field, wherein the data field includes at least one of a customer identification field, an account number filed, or a new customer field.
14 . The computer-implemented method of claim 13 , further comprising verifying the data field by comparing the data field and a set of data maintained in a data store, and collecting at least one of the customer score or refund policies from the data store if the data fields are verified.
15 . The computer-implemented method of claim 10 , further comprising storing at least one of the customer score or the set of refund policies in a data store.
16 . The computer-implemented method of claim 15 , further comprising modifying at least one of the customer score or the set of refund policies maintained in the data store based at least in part on at least one of: changes to the customer score or refund policies, or a passage of time.
17 . The computer-implemented method of claim 16 , further comprising modifying the set of refund policies based at least in part on at least one of the tracking data, or data obtained from an external source.
18 . The computer-implemented method of claim 10 , further comprising updating at least one of a customer's account data, the customer score, or the tracking data based at least in part on a disposition of the proposed fee refund, wherein the disposition includes at least one of an acceptance or a rejection.
19 . A fee refund management system, comprising:
means for determining at least one of a customer score, or a set of refund policies, wherein the customer score is based at least in part on a relationship between a customer and a financial institution, the relationship includes including at least one of a customer's account types, account balances, prior refunds, or length of patronage; and
means for determining a proposed fee refund for a customer account based at least in part on at least one of the customer score or the set of refund policies.
20 . The system of claim 19 , wherein the fee refund is for at least one of a non-sufficient funds fee, a late payment fee, or an automated teller machine fee.