The Settlement Conundrum
1611 .. the first modern stock exchange was created ..
Its 2023 and trades are still failing, and settlement rates are getting worse .. why? Where did we go wrong? What can be done?
c93% of trades settle on time, and we operate in a society where money can move in a millisecond. Why are we still struggling with settlement data?
To scale this, on Nasdaq alone there was in excess of 4 billion shares traded, at a value of in excess of $173 trillion, on May 8th.
Of the 7pc of trade settlement fails, the vast majority are through inventory issues, and Standard Settlement Instruction problems (SSI) - and you can bet your bottom dollar, many of the inventory issues are also related to poor settlement instructions too.
With CSDR, the US and Canada moving to T1 soon there is also impending regulatory pressure, and AFME estimate that the available post-trade processing time will be reduced by nearly 85pc - meaning settlement teams will have only 2 core business hours between the end of trading and the start of the settlement window, compared to >12 hours available today in a largely T2 environment.
Its going to be a nightmare if we carry 400 years + of challenges into 2024 ..
So - what do you do?
Increase headcount exponentially in on and offshore operations teams, at a time of recession, and cost focus? Good luck with that conversation ..
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No - you have to look to other methods and tools, and the time is now.
A trade doesn't and shouldn't need to fail before an SSI discrepancy is found - this calls for clean, accurate and up to date data, good SLA's and a strong process.
The data element should be supported by a cost effective data strategy - something like SSImple have a new model for solving static data issues at source - give them a look, ask for a demo!
The process element should be automated, once you have the datasets required, you should use digital workers to handle the exceptions, supported by the best available AI processes and models - we SS&C Blue Prism can help with that angle, to give you 5 times the processing agility vs humans, ask us to show you!
As you traverse the challenges above, ask yourself ..
How fast and accurate can I be?
What limitations do I have?
And make a change ..!