PATENT CLAIM ANALYSIS

Application Number: 15925664
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-08
Patent Classification: ["705", "014350"]

Abstract:
A visual discovery tool for automotive manufacturing with network encryption, data conditioning, and prediction can include an extraction device configured to receive data records from application-specific file source databases. The tool can further include a vehicle alert database that receives the vehicle records from the plurality of extraction databases. The visual discovery tool can include at least one hardware processor in communication with the extraction device and the vehicle alert database. The tool can be configured to selectively restrict access to an interactive display based on whether a client device receives authorization credentials.

Claim (Index 1):
A visual assessment tool for use by an automotive manufacturer with network encryption, data conditioning, and prediction, the tool comprising:\n a vehicle records extraction interface configured to obtain vehicle records from application-specific file source databases and at least temporarily store the vehicle records in at least one vehicle records extraction database; an external parameter extraction interface configured to obtain external parameters comprising current loan rates and/or incentives available from one or more external sources; a vehicle alert database configured to receive at least some of the vehicle records from the vehicle records extraction database; a vehicle manufacturer data interface configured to pass data from the vehicle alert database to a vehicle manufacturer database; and at least one computer processor configured to communicate with the extraction interface and the vehicle alert database and to perform computer-executable instructions to at least:\n use the extraction interface to receive, over a network, vehicle records from the application-specific file source databases; \n load the vehicle records into one or more of the at least one extraction database based in part on the file source database from which each vehicle record was sent; \n selectively remove, based on disqualifying criteria, one or more vehicle records from one or more of the plurality of extraction databases; \n selectively modify, based on modification criteria, one or more vehicle records in one or more of the plurality of extraction databases, the selective removal and selective modification resulting in trusted and standardized vehicle records; \n transfer the trusted and standardized vehicle records to the vehicle alert database, wherein the trusted and standardized vehicle data records comprise:\n a customer name for a previously sold vehicle and that customer's contact information, the customer name comprising a name of a past customer not known to be currently shopping or looking for a new vehicle; \n a vehicle identification number of the previously sold vehicle; \n data from a deal that resulted in a previous sale to the customer, the data sufficient to show or obtain:\n the customer's current monthly payment for the previously sold vehicle; \n an estimated current trade value of the previously sold vehicle; and \n an estimated current payoff amount of the previously sold vehicle; \n \n \n use the trusted and standardized vehicle records in the vehicle alert database to automatically evaluate a specific new deal proposal for each member of a large set of past customers to determine which past customers are good prospects for offering such deal proposals on favorable terms, wherein favorable terms comprise at least the same or lower monthly payments for a given customer, thereby determining that certain past customers should be included in a display of \u201calerts,\u201d the analysis comprising:\n automatically determining for each of the past customers a new suggested replacement vehicle for the previously sold vehicle using a one-to-one algorithmic association protocol, thereby limiting use of computer resources by confining analysis to one new suggested vehicle per customer for the determination of whether that customer is an \u201calert\u201d; \n periodically receiving updates to current trade value and current payoff amount for the large set of past customers; \n dynamically receiving updates to one or more external parameters through the external parameter extraction interface; \n determining customer-specific proposed payments for each new suggested replacement vehicle by:\n obtaining a price of the new suggested replacement vehicle for each customer; \n obtaining a net trade-in equity by combining the estimated trade value for each customer with the estimated payoff amount of the previously sold vehicle to that customer, wherein the trade-in equity may be either negative equity or positive equity; \n determining an amount to be financed by combining the price of the new suggested vehicle with any obtained net trade-in equity, whether positive or negative; \n using the amount to be financed and updated one or more external parameters to determine the new proposed payment; \n comparing each customer's current payment and the customer-specific new proposed payment to determine one or more differences; \n analyzing the differences to determine those meeting a criterion to identify the customer as an \u201calert\u201d for outreach because the difference meets a favorability condition; \n calculating aggregate data for the favorable deals resulting from analyzing the differences; \n via the vehicle manufacturer data interface, transmitting the aggregate data for display using a graphic user interface; \n accepting user input through a graphical user interface configured to adjust at least one incentive parameter; \n dynamically determining the effect of the at least one incentive parameter adjustment on the number of customers for whom the favorability condition is satisfied; and \n configuring refreshed alert information for display to a user through the graphical user interface, the refreshed alert information corresponding to a subset of the large set of past customers for whom the favorability condition is satisfied after the updates to the external parameters have been applied.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 90.0
- Lexical Diversity: 1.65
- Patent Class: 705.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14506550', '10996122', '13355412', '13076203', '13299293']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.0928404788751204
- 35 USC 102 Novelty (BERT): 0.4945898131465331
- Combined Prediction Score: 0.1330154123022616
- Mean Citation Score: 187.407612
- Max Citation Score: 214.72324
- Similarity Product: 141.369941480968

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test