Identification of loss risk candidates for financial institutions
AssigneeWells Fargo Bank, N.A.
InventorMark Beere
Life of this patent
Estimating the term…
Abstract
Systems and methods of analyzing client activity and identifying loss risk candidates based on the client activities is provided. A client database can be analyzed for determination of clients having a high risk of losses for a financial institution. The determination is based on known activities of filtered clients where the activities are historically indicative of resulting in a loss for the financial institution. A target client profile representative of a high risk client may be selected. The client database can be mapped to find similar clients to be identified as a high risk of loss.
Claims17
A method for determining loss risks, comprising:
- employing a processor to execute executable instructions stored within a memory to perform the following:
- receiving client data including client activity data associated with a set of client accounts;
- filtering the client activity data into a subset of the client activity data associated with a subset of client accounts, wherein the filtering includes coarse filtering of client data and refined filtering of client activity data to generate the subset of client accounts;
- calculating composite activity scores of the subset of client accounts according to the filtered subset of the client activity data;
- generating a composite activity ranking from calculated composite activity scores of the subset of client accounts, wherein the composite activity ranking indicates a level of risk of loss;
- identifying an activity rank target profile, wherein the activity rank target profile is based at least in part upon a composite of client accounts in the subset of client accounts that have similar composite activity rankings;
- and
- identifying client accounts in the set of client accounts that are similar to the activity rank target profile.
A system for determining loss risks, comprising:
- a processor that executes computer executable components stored in a memory;
- a client database comprising account information for a set of clients;
- a client activity database comprising a set of client activity data for entries in the client database;
- a filtering component that filters the client activity data into a subset of client activity data associated with a subset of client accounts, wherein the filtering includes coarse filtering of client data and refined filtering of client activity data to generate the subset of client accounts;
- a ranking component that generates a composite activity ranking of the subset of client accounts according to the filtered subset of the client activity data wherein the composite activity ranking of the subset of client accounts identifies at least one loss risk;
- a target component that identifies an activity rank target profile, the activity rank target profile is based on a composite of client accounts in the subset of client accounts that have similar composite activity rankings;
- and
- a mapping component that identifies client accounts from the set of client accounts that are similar to the activity rank target profile.
A non-transitory computer readable medium having instructions to control one or more processors configured to:
- receive client data including client activity data associated with a set of client accounts;
- filter the client activity data into a subset of the client activity data associated with a subset of client accounts, wherein the filtering includes coarse filtering of client data and refined filtering of client activity data to generate the subset of client accounts;
- receive weights for at least one data field;
- and
- apply the weights to the subset of client activity data;
- generate a composite activity ranking from calculated composite activity scores of clients according to the filtered subset of the client activity data, wherein the composite activity ranking of clients identifies at least one loss risk;
- identify an activity rank target profile, the activity rank target profile is based on a composite of client accounts identified as a loss risk in the subset of client accounts that have similar composite activity rankings;
- and
- identify client accounts from the set of client accounts that are similar to the activity rank target profile.
Dependencies are inferred from the claim text.