Trade Receivables as a Short Term Fixed Income Product – Part III

This is a four part series on the emerging interest of Trade Receivables as a short term, fixed income product.   Part III talks about the challenges in investing.

 

 The challenges investing in Trade Receivable are several and significant:

  1. First, as an asset class, it is poorly understood by end investors.  Trade Assets are varied and get lumped into one Asset Class.  Many investors I have spoke to consider trade and factoring the same thing.  So there is a serious amount of education in order to develop products.
  2. Second, Trade finance data is not standardized, transparent, or granular, making it more difficult to package.  A letter of credit (“L/C”) for coal can be quite different than an L/C for merchandise or corn.
  3. Third, Trade is not a visible asset class.  From an investor’s perspective, there is very limited information on Bloomberg, there is no bourse or exchange, and the one data provider that provides pricing data (Markit’s LTP Trade Index), has only two banks contributing data.
  4. Fourth, Funds that have invested in Trade Finance typically are not scalable, and mention the high barriers of entry to develop product.  This is due to the need for expertise around custody, settlement and documentation.

 

Given the potential for large information asymmetries, assessing and maintaining underwriting standards may become problematic, which may reduce investors’ willingness to provide funds.

Supplier Networks potentially offer a game changer because of the technology behind them.  Algorithms can be used to predict invoice overpayment risk and collection risk.  The data contained in networks can provide input on supplier/buyer relationships, purchase order history, invoices, payments, etc.    As an example, Tungsten has signed a 5 year rolling agreement with @UK PLC to deliver TungstenAnalytics, a comprehensive and innovative line level spend analytics solution, to be applied to the invoice data transacted over Tungsten′s network

The challenges for non banks around networks comes about by creating the right underwriting model that can deal with the potential dilution loss.  This may sound like its easier said than done, but with the right data, smart underwriters can build this into their loss models and price accordingly.

Part IV will discuss different type of investors and provide a brief on their likelihood to invest in this asset class.

 

 

 

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