Trade settlement failures are already a prevalent issue in the post-trade industry, and new European rules will soon come into effect that impose tougher standards on trades that fail to settle on time. Such failures occur when a seller doesn’t deliver securities or when a buyer fails to pay owed funds by the settlement date. According to the European Securities and Markets Authority, failed trades account for about 3% of the trades value in corporate bonds and sovereign debt markets, and about 6% in equity markets.
This translates into millions of trades failing annually. According to the Depository Trust & Clearing Corporation (DTCC), a trade settlement failure rate of just 2% may result in costs and losses of around $3 billion. The European Central Bank (ECB) cites the value of delivery instructions processed annually by European CSDs (central securities depositories) and international CSDs as €1,295 trillion in 2018, and the number of deliveries approached 390 million. Such large volumes and transaction values weigh heavily, as even a 1% average failure rate equates to about four million transactions failing annually in Europe.
The Central Securities Depositories Regulation (CSDR) introduces punitive measures under the settlement discipline regime for failing to deliver securities and initiating buy-in of aging fails. This has strengthened the business case for urgent action to ward off the financial threat. In addition to investing in regulatory technology for CSDR compliance, firms should explore opportunities to reduce costs associated with trade settlement failures, especially in the post-COVID-19 era where cost optimization would be a critical business imperative. Predicting trade settlement failures will not only lessen risks arising out of these transactions but also reduce the financial impact of cash penalties.
Effects of trade settlement failures
Typically, a trade settlement failure results in trades or a group of related/linked trades falling off the straight-through processing (STP) engine of market participants. A failed trade then goes through a manual investigation in an exception queue, and mid/back office personnel take corrective action through interventions. Corrective actions include addressing referential data, trade booking and inventory management issues that caused the process to abort. Such failed trades are responsible for about 80% of the total operational costs involved in trade processing. The administration and resolution of settlement failures can adversely affect trade processing across market entities and, if left unaddressed, may potentially disrupt market operations.
According to the DTCC, firms engaged in post-trade activities and settlement processes in general, are slow to adopt digital solutions. However, there are glimmers of progress. One of Europe’s largest CSDs is investing in digital and data services that support post-trade efficiency. And a large European bank is exploring ways to reduce issues in trade processing with a predictive analytics tool for decision support.
Prediction and mitigation
A digital solution using predictive analytics will assist in facilitating early corrective action when fails occur, such as alerting investment managers prior to the settlement date about insufficient securities. We recommend the approach to an analytics solution for predicting trade settlement failures depicted by the illustrated equation, where the probability of a trade settlement failure (the dependent variable) is determined as a function of the factors (sets of independent variables) presented below.
The formula is asset-class agnostic and can be applied to cash markets. The model’s output is the probability of a trade failure of a security (ISIN) for a settlement date. Based on the probability, business operation leaders can identify a group of trades that can potentially fail and involve counterparties to take action, such as addressing a liquidity shortfall. This early alert to counterparties will smoothen trade settlement processing on the settlement date.
