How we helped a client hunt down errors in their pricing system, and fix security price issues once and for all.
What is a security price?
It sounds like a simple question. But if you’re in finance, you already know that the answer can be very complex indeed.
You’ve got bid, ask, mid, intraday and closing prices – from multiple exchanges around the world. But whichever data source you choose, you need to be sure you have a consistent, accurate price you can rely on.
In this post, we’ll tell the story of what happened when a client’s pricing system went wrong – and how we identified and fixed the problem.
How securities pricing works
Most firms use a similar approach to getting accurate price information. If you work in a trading team, you may be familiar with it already.
First, the valuation system generates a driver file based on all securities with a holding, identifying each one with a market ID, ISIN or SEDOL, exchange code and security type code.
Then, the pricing engine takes on the information from the driver file. However, in the case of this client, it only adds new items – if a security is already included in the engine, that data is left untouched.
If all goes well, the pricing team receives the information they need: a complete and accurate list of every security in the portfolio, with an accurate security price alongside it.
The problem: rogue prices in the system
So far, so good. But our client had noticed that multiple security prices were wrong.
It was only a few. But in a portfolio of 5000 securities, even a 1% failure rate was a real problem.
Pricing staff had got into the habit of correcting these prices by hand. But that raised the risk of them entering a wrong price,or neglecting to do it at all. The extra manual work was imposing an unnecessary operational overhead on the business, adding around 20% to costs.
What’s more, the errors were enough to undermine confidence in the whole system – which was jeopardising the firm’s reputation.
The firm couldn’t go on like that. So we set out to find and fix the problem once and for all.
Hunting down the errors
Where was the system getting these incorrect security prices from? Nobody knew.
The errors seemed to be completely random. But when you’re dealing with data, anomalies are rarely random. There’s always a cause.
To hunt down the errors, we carried out a comparative analysis, checking the securities with correct prices against those that were wrong.
We found that it all came down to the primary exchange, denoted on the valuation system, that prices were taken from. All correctly priced securities had the correct primary exchange. Some of the wrongly priced ones had the incorrect exchange – and some of them had the right exchange, but the audit trail showed it had originally been wrong.
Finding the fix
Once we’d discovered what was going wrong, the solution was relatively simple: fix the exchange in the valuation system, delete the incorrect line from the pricing engine and monitor the results. All prices were now correct. Success!
To follow up, we measured the reduced reprocessing rates, shorter timelines and improved accuracy, to quantify the savings achieved for the client.
We also updated operations procedures and training documents to ensure that the knowledge of this problem – and how to fix it – was safely institutionalised for the future.
Teams need to talk
On one level, this was a technical problem with a technical solution. Yet it also highlighted the importance of organisational memory and communication between teams.
The original mistake had been made over a decade earlier. The person who made it was long gone, and all knowledge of the development and go-live for the pricing system had been lost.
That left the company’s team with a flaky system that really wasn’t fit for purpose – yet they soldiered on with their manual workaround, simply because ‘that’s the way we’ve always done it’.
On top of that, functional teams were too focused on their own tasks, never looking outside their ‘siloes’.
To prevent this sort of situation, it’s vital that different teams within the business talk to each other.
Operations teams have to understand the technology they work with, and technology teams have to understand the people who use their tools. Only then can they work together to overcome obstacles to efficient operations.
After all, if you can’t even see a problem, how can you ever fix it?
If you need help with a gremlin in your system, talk to us. We have decades of experience in finding and fixing technical issues for financial firms.
Photo by iSAW Company on Unsplash