Abstract: A system is disclosed. The system has a remediation module, comprising computer-executable code stored in non-volatile memory, a processor, a buyer device of a buyer, and a seller device of a seller. The remediation module, the processor, the buyer device, and the seller device are configured to receive asset data of the seller, receive exception rules of the buyer, determine exceptions of the asset data based on the exception rules, display the exceptions via at least one of the buyer device or the seller device, and update the asset data based on the displayed exceptions.

Abstract: A system is disclosed. The system has a mortgage servicing and loan valuation module, comprising computer-executable code stored in non-volatile memory, a processor, and a user interface configured to communicate with the mortgage servicing and loan valuation module and the processor. The mortgage servicing and loan valuation module, the processor, and the user interface are configured to receive a full loan valuation data of a buyer, select a plurality of loan samples based on the full loan valuation data, determine a function data file based on the full loan valuation data and the plurality of loan samples using machine learning operations, transform a seller asset data of a seller, which includes a plurality of assets, to a normalized data structure, and determine a subset of the plurality of assets by applying the function data file to the normalized data structure.

Abstract: A system is disclosed. The system has a mortgage servicing and loan valuation module, comprising computer-executable code stored in non-volatile memory, a processor, and a network component configured to communicate with the mortgage servicing and loan valuation module and the processor. The mortgage servicing and loan valuation module, the processor, and the network component are configured to receive a pricing file via the network component, provide a plurality of machine learning regression models, determine one or more of the plurality of machine learning regression models to apply to the pricing file, apply the determined one or more of the plurality of machine learning regression models to the pricing file, and transfer a priced portfolio to the network component.