More than $20 billion is spent on trade processing every year by financial institutions, according to a report published by the Bank of England in June 2020.

Yet, about 12% of all securities settlements fail for several reasons, including a lack of pre-matched instructions, liquidity and funding issues, inventory, data inaccuracies, and manual errors, according to the European Securities and Markets Authority (ESMA).

These fails adversely impact firms, causing unsatisfactory client experiences, reputational risks, adverse balance sheet impacts through RWA provisioning, and regulatory non-compliance. In addition, there are significant hidden costs associated with investigating a failed trade, communicating with a client, following a compensation process, and reconciliation.

An intelligent automation solution for pre-matching can help address some of the concerns around failed transactions.

‍

State of post-trade settlements operations

Recent guidelines from the Central Securities Depositories Regulation (CSDR) impose stiff penalties and a minimum RWA provisioning of 8% for participants failing to deliver on their settlement obligations, leading to a significant balance sheet/cost of carry impact.

On a typical day, a mid-to large-sized securities market participant handles about 500 or more trades, executed with over 20 counterparties, across several markets, depots, and currencies.

The Settlements Operations teams perform a series of critical, time-consuming tasks that require exercising judgement to enable the settlement of these trades. This includes:

• extracting reports from settlement systems
• Identifying failed trades based on trade status
• pulling out the SSI information on each trade
• determining counterparties and their contact information from reference data systems
• preparing emails for each counterparty
• attaching the SSI information on each trade, and
• sending mail out and tracking responses from counterparties

All this is done to ensure the place of settlement is correctly identified and affirmed to ensure that the trade does not fail due to a lack of adequate liquidity or available positions required to fulfil the settlement obligations.

‍

Pre-matching for smarter settlements

To enable successful post-trade processing, an intelligent and automated pre-matching system is a critical step.

LatentBridge’s solution reduces the fails management costs by 75% and improves efficiency by 80%. It ensures an enhanced client experience and effective controls and monitoring.

The automated pre-matching solution enables a faster, more accurate, and scalable deployment by:

1. Identifying failed trades for a given expected date of settlement for one or more settlement depots
2. Investigating fails and identifying SSIs for each trade
3. Preparing failed trade reports and sending them to relevant counterparties.
4. Identifying appropriate counterparties to the trade in different capacities, like trading or parent trading company, settlement agent, or custodian, and applying intelligent mailing rules
5. Scanning counterparty email responses and updating fails status
6. Scheduling an automated pre-matching process across several markets and settlement depots and enabling operations to become more resilient and scalable

‍

To discuss how intelligent automation can help you overcome challenges with your trade settlement process, reach out to us at contact@latentbridge.com.