Abstract: A method for predicting, assessing, and auditing prices of products or services is provided. In some embodiments, the method includes receiving a product description with one or more terms and obtaining a product list with product descriptions having respective prices, where each product description in the product list includes the one or more terms or combinations thereof from the received product description. The method further includes, training a model to determine how the one or more terms or combinations thereof influence the prices in the product list, using the trained model to make a price prediction for the received product description, and enabling assessment of product prices based on the price prediction made by the trained model.

Abstract: A method and system for detecting deviation between invoices and receipts are disclosed. In some embodiments, the method includes receiving invoice data and receipt data. The method includes filtering the received data to generate filtered data. The method includes performing line-level matching on the filtered data based on one or more line-level attributes and one or more distance based algorithms. The method then includes determining, from the line-level matching, matched line items and unmatched line items between each pair of the invoice and receipts. The method also includes calculating one or more types of claims for both the matched line items and the unmatched line items to measure a total deviation between the invoices and receipts. The method further includes determining a level of match between the invoices and receipts and generating a recommended matching pair of invoice and receipt based on the level of match.

Abstract: A method for detecting price errors and/or discrepancies includes receiving an item file containing at least retail store identifiers, product identifiers corresponding to products sold in stores associated with the store identifiers, and product prices corresponding to the product identifiers. The method further includes creating a dataset having a first grouping with the store identifiers, a second grouping with the product identifiers, and a third grouping with the product prices; selecting a group of the stores based on one or more criteria; and applying regression analysis on the dataset to predict a price for each product across the group of the stores. Additionally, the method includes ranking residuals from the regression analysis to identify, within the group of the stores, products whose prices do not match their predicted prices.

Abstract: A method for mitigating routing risks during transport of goods is provided. In some embodiments, the method includes obtaining historical records for transported goods, where the records include routes with associated road segments. The method also includes establishing risk metrics for each road segment on each route based on the historical records and calculating, from the risk metrics, road risk and road probability metrics for each road segment on each route. The method further includes applying a weight to each of the road risk and road probability metrics, combining, for each road segment, the weighted road risk and road probability metrics for such road segment into a composite risk score (CRS) that defines whether such road segment is low-risk or high-risk for transporting goods, and selectively adjusting a length of each road segment defined as low-risk and/or each road segment defined as high-risk based on their corresponding CRS.

Abstract: A method for predicting, assessing, and auditing prices of products or services is provided. In some embodiments, the method includes receiving a product description with one or more terms and obtaining a product list with product descriptions having respective prices, where each product description in the product list includes the one or more terms or combinations thereof from the received product description. The method further includes, training a model to determine how the one or more terms or combinations thereof influence the prices in the product list, using the trained model to make a price prediction for the received product description, and enabling assessment of product prices based on the price prediction made by the trained model.

Abstract: A method for identifying shipment shortages on pallets is provided. In some embodiments, the method includes taking one or more digital images of a pallet with a shipment thereon to estimate the shipment's volume. The method further includes estimating an anticipated shipment volume based on the shipment's invoice information, and comparing the estimated shipment volume to the anticipated shipment volume to calculate volume mismatches. The volume mismatches can be used as an indicator of any shipment errors.