Patent Issued for Apparatus and method for resource allocation prediction and modeling, and resource acquisition offer generation, adjustment and approval (USPTO 11915174): Assurant Inc.

2024 MAR 14 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Caltabiano, Brett (Atlanta, GA, US), Dhirasaria, Deepak Kumar (New York, NY, US), Jeffries, III, Ronnie (York, PA, US), Jha, Vivek Kumar (New York, NY, US), Moorthy, Satish (Wayne, PA, US), Stauffer, Jr., Jay (Wayne, PA, US), filed on February 13, 2020, was published online on February 27, 2024.

The patent’s assignee for patent number 11915174 is Assurant Inc. (New York, New York, United States).

News editors obtained the following quote from the background information supplied by the inventors: “Many of today’s network environments are dynamically resource-constrained, at least in the sense that the need for resources, and the nature of the needed resources, can change rapidly and significantly over time and geography. Some of the technical challenges that hinder the effective and efficient allocation of resources in such environments are compounded in situations where the supply, utility, and/or value of the needed resources changes over time. Additionally, in this regard, acquisition of resources for a particular time and/or geography can change significantly. Technical challenges in data compilation, analysis, visualization, and manipulation associated with conventional systems hinder efficient resource acquisition planning. The inventors of the invention disclosed herein have identified these and other technical challenges, and developed the solutions described and otherwise referenced herein.”

As a supplement to the background information on this patent, NewsRx correspondents also obtained the inventors’ summary information for this patent: “An apparatus, computer program product, and method are therefore provided in accordance with an example embodiment in order permit the efficient determining of one or more channels and/or related conditions through which a particular resource set may be effectively distributed. In this regard, the method, apparatus and computer program product of an example embodiment provide for the creation of predicted channel and condition data set that can be stored within a renderable object and otherwise presented to a user via an interface of a client device.

“Moreover, the method, apparatus, and computer program product of an example embodiment provide for use of the machine learning model in connection with the determination and retrieval of a predicted channel and condition data set determined based at least in part on context data associated with a particular resource set to be distributed at a time in the future.

“In an example embodiment, an apparatus is provided, the apparatus comprising a processor and a memory, the memory comprising instructions that configure the apparatus to: receive a request data object from a client device associated with a user; extract, from the message request data object, a request data set, wherein the request data set is associated with a first set of resources; receive a first context data object, wherein the first context data object is associated with one or more resource distribution channels; retrieve a predicted channel and condition data set, wherein retrieving the predicted channel and condition data set comprises applying the request data set and the first context data object to a first model; and generate a control signal causing a renderable object comprising the predicted channel and condition data set to be displayed on a user interface of the client device associated with the user.

“In another example embodiment, a computer program product is provided, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising program code instructions configured to: receive a request data object from a client device associated with a user; extract, from the message request data object, a request data set, wherein the request data set is associated with a first set of resources; receive a first context data object, wherein the first context data object is associated with one or more resource distribution channels; retrieve a predicted channel and condition data set, wherein retrieving the predicted channel and condition data set comprises applying the request data set and the first context data object to a first model; and generate a control signal causing a renderable object comprising the predicted channel and condition data set to be displayed on a user interface of the client device associated with the user.

“In another example embodiment, a method for determining a predicted future demand for resources in a dynamic environment is provided, the method comprising: receiving a request data object from a client device associated with a user; extracting, from the message request data object, a request data set, wherein the request data set is associated with a first set of resources; receiving a first context data object, wherein the first context data object is associated with one or more resource distribution channels; retrieving a predicted channel and condition data set, wherein retrieving the predicted channel and condition data set comprises applying the request data set and the first context data object to a first model; and generating a control signal causing a renderable object comprising the predicted channel and condition data set to be displayed on a user interface of the client device associated with the user.”

The claims supplied by the inventors are:

“1. A computer-implemented method for generating a resource offer set, the method comprising: retrieving at least one resource offer generation input data set comprising a plurality of data sets associated with a plurality of resource identifiers; receiving a benchmark and portfolio target data set in response to an input by an offer control user via one or more client devices; generating a resource offer set by applying, to a resource offer generation model, (1) at least one of the plurality of data sets in the at least one resource offer generation input data set transformed to be processable by the resource offer generation model and (2) the benchmark and portfolio target data set, wherein the resource offer generation model generates the generated resource offer set satisfies the benchmark and portfolio target data set, and wherein the resource offer set comprises at least one resource offer data object, at least a portion of the at least one resource offer data object associated with at least one resource identifier of the plurality of resource identifiers; generating a control signal causing real-time rendering of a renderable object comprising an offer adjustment interface comprising an indication of each resource offer data object of the resource offer set associated with the at least one resource identifier; dynamically updating, in real-time, the offer adjustment interface in response to user interaction with the one or more client devices causing update of a value of at least one resource offer data object of the resource offer set to create an adjusted resource offer set; dynamically displaying, at a first portion of display of a first client device of one or more client devices, a first instance of a dashboard comprising offer analytics data, wherein the dashboard is updated in real-time in response to each update to the value of at least one resource offer data object received via the offer adjustment interface, wherein each update further updates the offer analytics data, wherein the dashboard is rendered at a second portion of the display that is non-overlapping with the first portion associated with the offer adjustment interface and is simultaneously accessible while interacting with any resource offer data object of the resource offer via the offer adjustment interface, wherein one or more portions of the dashboard are selectable to dynamically change between presenting, at the display of the one or more client devices, the offer adjustment interface and presenting at least one additional interface including details associated with at least a portion of the offer analytics data, and wherein in an instance in which at least one additional interface is displayed, the dashboard in configured to be rendered non-overlapping with each of the at least one additional interface and is simultaneously accessible while interacting with each of the at least one additional interface: receiving a completion control signal from the first of the one or more client devices; in response to the completion control signal, generating an approval request control signal causing rendering, at a first portion of a second display associated with a second client device of the one or more client devices, of an approval interface an indication of the adjusted resource offer set, wherein the indication of the adjusted resource offer set is not modifiable by an offer approval user of the second client device; causing rendering at a second portion of the second display associated with the second client device, of a second instance of the dashboard that comprises shared data values depicted in the first instance of the dashboard in an instance in which the completing control signal is received, wherein the second instance of the dashboard is selectable to dynamically change between presenting the indication of the adjusted resource offer set and the at least one additional interface via the second display; receiving, from the second client device of the one or more client devices, an offer approval control signal comprising an offer status indicator; and storing the resource offer set associated with the offer status indicator.

“2. The computer-implemented method of claim 1, wherein retrieving the at least one resource offer generation input data set comprises: determining the at least one resource offer generation input data set satisfies an untrustworthiness threshold; and retrieving an updated resource offer generation input data set for the at least one resource offer generation input data set for including in the resource offer generation input data set.

“3. The computer-implemented method of claim 1, wherein the computer-implemented method further comprises generating at least a portion of the offer analytics data set based on the resource offer set and at least one of the at least one resource offer generation input data set.

“4. The computer-implemented method of claim 1, wherein the plurality of resource identifiers comprises a plurality of third-party resource identifiers, wherein at least a portion of the plurality of third-party resources identifiers is unstandardized and wherein the plurality of data sets associated with the plurality of third-party resource identifiers is not processable by a resource offer generation model, the computer-implemented method further comprising: transforming the plurality of unstandardized third-party resource identifiers to a set of standardized resource identifiers by applying the plurality of unstandardized third-party resource identifiers to a resource mapping data set, wherein applying the plurality of unstandardized third-party resource identifiers to the resource mapping data set comprises determining a standardized resource identifier for each unstandardized third-party resource identifier, wherein the standardized resource identifiers are compatible with and processable by the resource offer generation model; transforming the plurality of data sets in the at least one resource offer generation input data set to be processable by the resource offer generation model by at least linking the plurality of data sets to at least one standardized resource identifier of the set of standardized resource identifiers determined corresponding to a particular unstandardized third-party resource identifier associated with the portion of the at least one resource offer generation input data set; for each particular unstandardized third-party resource identifier: parsing a plurality of resource attribute values from third-party resource identifier information corresponding to the particular unstandardized third-party resource identifier; programmatically calculating a mapping score data value by at least comparing the plurality of resource attribute values from the particular unstandardized third-party resource identifier information with second resource attribute values associated with a first standardized resource identifier; programmatically determining the mapping score satisfies a mapping confirmation threshold; and in response to programmatically determining the mapping score satisfies the mapping confirmation threshold, generating data mapping the particular unstandardized third-party resource identifier to the first standardized third-party in the mapping set, wherein each resource offer generation input data set associated with the particular unstandardized third-party resource identifier is linked with the first standardized resource identifier, wherein the offer adjustment interface comprises the identification of each resource offer data object of the resource offer set associated with a standardized third-party resource identifier corresponding to the third-party resource identifier for the resource offer data object.

“5. The computer-implemented method of claim 4, the computer-implemented method further comprising: receiving data transmissions comprising the at least one resource offer generation input data set from a plurality of external systems; and extracting the plurality of unstandardized third-party resource identifiers from the data transmissions.

“6. The computer-implemented method of claim 4, the computer-implemented method further comprising: receiving data transmissions comprising the at least one resource offer generation input data set from a plurality of external systems; and identifying the plurality of unstandardized third-party resource identifiers by identifying the particular unstandardized third-party resource identifier associated with each external system of the plurality of external systems.

“7. The computer-implemented method of claim 4, the computer-implemented method further comprising: for each particular unstandardized third-party resource identifier: programmatically calculating a second mapping score by at least comparing the plurality of resource attribute values from the particular unstandardized third-party resource identifier information with third resource attribute values associated with a second standardized resource identifier; and determining the second mapping score does not satisfy the mapping confirmation threshold.

“8. The computer-implemented method of claim 4, wherein the offer adjustment interface separately renders each indication of each resource offer data object associated with a different standardized resource identifier.

“9. The computer-implemented method of claim 8, wherein the offer adjustment interface comprises a table comprising a row associated with each resource offer data object associated with a particular standardized resource identifier, and wherein each row comprises at least a portion of the at least one resource offer generation input data set corresponding to the particular standardized resource identifier.”

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For additional information on this patent, see: Caltabiano, Brett. Apparatus and method for resource allocation prediction and modeling, and resource acquisition offer generation, adjustment and approval. U.S. Patent Number 11915174, filed February 13, 2020, and published online on February 27, 2024. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11915174)&db=USPAT&type=ids

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