Invention Application
- Patent Title: COST ALLOCATION ESTIMATION USING DIRECT COST VECTORS AND MACHINE LEARNING
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Application No.: US16358850Application Date: 2019-03-20
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Publication No.: US20200302550A1Publication Date: 2020-09-24
- Inventor: Steffen Vollmert , Luisa Karl , Konrad Schenk , Olga Cherepanova , Janet Dorothy Salmon , Ralf Ille , Thomas Zuerker
- Applicant: SAP SE
- Main IPC: G06Q40/00
- IPC: G06Q40/00 ; G06N20/00

Abstract:
The disclosure generally describes methods, software, and systems for estimating cost allocations, including a method for the following steps. Using a machine learning system, transactions are consolidated into estimated sender-receiver totals for costs transmitted by senders to receivers in an organization. A sender-receiver percentage matrix is determined from the estimated sender-receiver totals of a given sender and for each receiver of the transactions from the given sender. The sender-receiver percentage matrix includes, for each sender, estimated sender-receiver percentages. Current actual costs are determined for each sender to receivers for a given time period. Estimated cost allocations are determined for given time period using the sender-receiver percentage matrix. The estimated cost allocations are determined for each receiver in the organization based on a function of the current actual costs for each sender. A report that includes the estimated cost allocations is provided for presentation to a user.
Public/Granted literature
- US11521274B2 Cost allocation estimation using direct cost vectors and machine learning Public/Granted day:2022-12-06
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