Abstract: This disclosure describes systems, methods, and devices related to predictive modeling for evaluating vehicles. A device may receive a customer identifier (e.g., a user identification number, a social security number, driver license number, etc.). The device may retrieve credit data associated with the user identifier and vehicle data associated with a vehicle. The device may determine a first weight for the credit data and a second weight for the vehicle data. The device may determine, based on the first weight and the second weight, a value. The device may determine whether or not the value exceeds a profitability threshold. The device may determine a loan information associated with the customer identifier. The device may send a first indication of the product or service to a user device for presentation. The device may send a second indication of the loan information to the second device for presentation.

Abstract: This disclosure describes systems and methods for improved transaction platforms. An example method may include receiving, by a processor and from a user, a selection of a first vehicle from a user interface. The example method may also include determining, by the processor and based on the first vehicle, a second vehicle. The example method may also include sending, by the processor, data associated with the first vehicle and data associated with the second vehicle to one or more entities. The example method may also include receiving, by the processor, first payment information for the first vehicle and second payment information for the second vehicle. The example method may also include determining, by the processor and based on the first payment information and the second payment information, third payment information for a third vehicle.

Abstract: This disclosure describes systems, methods, and devices related to predictive modeling for evaluating vehicles. A device may receive a customer identifier. The system may determine financial data associated with the customer identifier and vehicle data associated with a vehicle. The system may determine loan information associated with the customer identifier and the vehicle. The system may determine a product or service associated with the vehicle. The system may determine a first value indicative of a probability that the customer will purchase the vehicle and the product or service based on the loan information. The system may determine a second value indicative of a profitability of a purchase of the vehicle and the product or service based on the loan information. The system may determine respective indications of the vehicle, the product or service, and the loan information to a user device for presentation.

Abstract: This disclosure describes systems, methods, and devices related to predictive modeling for evaluating vehicles. A device may receive a customer identifier (e.g., a user identification number, a social security number, driver license number, etc.). The device may retrieve credit data associated with the user identifier and vehicle data associated with a vehicle. The device may determine a first weight for the credit data and a second weight for the vehicle data. The device may determine, based on the first weight and the second weight, a value. The device may determine whether or not the value exceeds a profitability threshold. The device may determine a loan information associated with the customer identifier. The device may send a first indication of the product or service to a user device for presentation. The device may send a second indication of the loan information to the second device for presentation.

Abstract: This disclosure describes systems, methods, and devices related to predictive modeling for evaluating vehicles. A device may receive a customer identifier (e.g., a user identification number, a social security number, driver license number, etc.). The device may retrieve credit data associated with the user identifier and vehicle data associated with a vehicle. The device may determine a first weight for the credit data and a second weight for the vehicle data. The device may determine, based on the first weight and the second weight, a value. The device may determine whether or not the value exceeds a profitability threshold. The device may determine a loan information associated with the customer identifier. The device may send a first indication of the product or service to a user device for presentation. The device may send a second indication of the loan information to the second device for presentation.

Abstract: This disclosure describes systems, methods, and devices related to predictive modeling for evaluating vehicles. A device may receive a customer identifier. The system may determine financial data associated with the customer identifier and vehicle data associated with a vehicle. The system may determine loan information associated with the customer identifier and the vehicle. The system may determine a product or service associated with the vehicle. The system may determine a first value indicative of a probability that the customer will purchase the vehicle and the product or service based on the loan information. The system may determine a second value indicative of a profitability of a purchase of the vehicle and the product or service based on the loan information. The system may determine respective indications of the vehicle, the product or service, and the loan information to a user device for presentation.

Abstract: This disclosure describes systems, methods, and devices related to predictive modeling for evaluating vehicles. A device may receive a customer identifier (e.g., a user identification number, a social security number, driver license number, etc.). The device may retrieve credit data associated with the user identifier and vehicle data associated with a vehicle. The device may determine a first weight for the credit data and a second weight for the vehicle data. The device may determine, based on the first weight and the second weight, the value. The device may determine whether or not the value and a profitability threshold. The device may determine a loan information associated with the customer identifier. The device may send a first indication of the product or service to a user device for presentation. The device may send a second indication of the loan information to the second device for presentation.

Abstract: Methods and apparatuses are described for automated generation and execution of computer software test cases. A digitized voice segment is captured that corresponds to speech submitted by a user of a remote device. A software automation test case is generated using one or more phrases extracted from the digitized voice segment. The software automation test case is executed against a plurality of browser-based software applications using a plurality of automation testing tools, including converting the software automation test case into a plurality of tool-and-browser specific test cases, each based upon test case requirements of a selected automation testing tool and test case requirements of a selected browser-based application. An automation execution report is generated based upon the execution of each of the plurality of tool-and-browser specific test cases.