Distressed Loan Settlement: The PSA solution

In an earlier article I suggested that we can finally address the challenge of extremely long trade settlement times in the distressed loan market (T+66 is the current average) by applying three rules for driving technology and process change.

• Rule #1: What can be standardized must be standardized.
• Rule #2: What has been standardized must be automated.
• Rule #3: Go back to Rule #1, and then to Rule #2.

Creation and negotiation of the LSTA Purchase and Sale Agreement for Distressed Trades (PSA) is a natural place to apply Rule #2 and introduce automation.

Let's start by demystifying the PSA. Yes, it contains 52 data fields, all of which must be populated correctly to ensure buyer receives marketable paper from seller. Done manually, that's complicated and time-consuming. But from a technology standpoint the PSA is not a complex document. It's not even really a document. Rather, it's an output, an automatic consequence of inputs, substantially all of which trade settlement systems like ClearPar have at the time of trade.

Some of these data are hardcoded into the PSA itself, such as the applicable LSTA Terms and Conditions for Distressed Trades governing the transaction. Other data can be mapped to the PSA from known sources such as the trade ticket (e.g., trade date, purchase amount) or a trusted bankruptcy data feed. Still other data can be derived from other information in the system (e.g., if the seller allocates upstreams to the buyer, "Type of Assignment" in the PSA's Transaction Summary is, by definition, "Secondary").

A very limited number of fields in the PSA - as few as seven - need to be completed manually. However, even for these fields, system logic can allow the user to simply confirm the likely answer. For example, because "None" is almost always the response to Section 4.1(w) Notice of Impairment on the PSA's Annex, we can make "None" the default answer, subject to user confirmation. So, even when full automation is not possible, technology can speed the process.

Mapping data to the PSA, deriving data to populate the PSA and providing intelligent assistance to complete the PSA are all possible today. That's a substantial improvement to the status quo in distressed loan settlement.

Applying, Rule #2 lets data do what data are meant to do: be distributed far and wide within the context of the trade. Technology facilitates this. It ensures that when something is known once by ClearPar in the context of a distressed trade, it never needs to be keystroked again. It simply is distributed everywhere it needs to go. This is what full standardization enables, and, recalling Rule # 1, why it's so desireable.

It's no longer seller or buyer drafting a PSA. It's seller and buyer answering a few questions and then letting the platform create an instant output, drawing on those and all other inputs. We're also letting technology do what it's best at, namely, take standardized processes and workflows and automate them. Users can then decide for themselves how they want to handle what little remains. How nice will it be when a completed PSA is the output of confirming a mere seven data fields? How much more so, when you consider the reality of multiple trade allocations! That reality is closer than you think.

At this point you're probably beginning to see how distressed loans could settle much more like par. But you may be wondering how we deal with inventory management and upstream review, each of which are required to finalize the PSA and close the trade. We'll be back soon to discuss those important missing pieces of the distressed loan settlement puzzle.

Posted 17 April 2019 by Patricia Tessier, Managing Director and Head of Loan Platforms, S&P Global Market Intelligence

S&P Global provides industry-leading data, software and technology platforms and managed services to tackle some of the most difficult challenges in financial markets. We help our customers better understand complicated markets, reduce risk, operate more efficiently and comply with financial regulation.

This article was published by S&P Global Market Intelligence and not by S&P Global Ratings, which is a separately managed division of S&P Global.