Video: The data-centric approach to mastering T+1 settlement

Video transcript

Let’s think about a customer journey for a trade.

We’ve talked about T+1, which is clearly a hot topic in the industry right now.

But really, when you start to break down, actually that trade flow, there are common data sets needed to make that process work.

I need instrument data. I need counterparty data.

I need settlement instruction data, to really kind of make that process flow neatly front to back.

By being able to look at where that data comes from, being able to understand the causes of bad data and the impact to your process, you can actually discover a lot of opportunity for removing process friction that typically kind of persists in a lot of these traditional operating models.

So just by being able to think around where your data comes from, the controls that it needs to go through, the checks and balances that are needed to make it accurate… By being able to hone in and focus on those points, you can extract a lot of efficiency value, actually around kind of where a lot of those common pinch points are.

And to come back to some of our own thoughts on this.

Our language around Human API, which is a fairly common term in the industry now.

The role of the operations or process owner in the processing chain, taking data from one system and moving it to another, perhaps reconciling or cleaning data because it’s not perfect, it’s incomplete.

By being able to recognise the cost of that and being able to overlay that around data and understanding the journey that data goes on through your infrastructure, there’s material opportunities for efficiency in terms of the amount of people needed to keep the engine running, but also in terms of speed, timeliness and quality, which clearly has been a big driver from the regulators over the last 10 years.