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Supply@ME Capital
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==== A suitably large inventory-related database and machine learning ==== A key ingredient to lowering the finance cost is inventory-related data. That is to say, the more inventory-related data to which an inventory-finance provider has access, the lower the finance cost (and, ultimately, the higher the finance demand). Accordingly, we believe that building a suitably large database of inventory-related data is key for the success of a company in the inventory-finance space, and, therefore, thatβs where Supply@Me Capital needs to focus its energy. Indeed, a study by the International Monetary Fund (IMF) detailed that "the absence of comprehensive trade finance data posed a significant hurdle ... to make informed, timely decisions".<ref name=":2">https://www.imf.org/-/media/Files/Publications/WP/2019/wpiea2019165-print-pdf.ashx</ref> For us, therefore, a key milestone is the hiring of a chief technology officer (CFO) and senior data scientist (i.e. someone who has around five years experience with Python or another similar programming language), which we estimate will cost the company around >Β£100,000 per year each.
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