The Capital Markets industry was one of the first data driven industries. However, with the relentless move to algorithmic trading, and an increasingly onerous regulatory regime, banks and other players need to be increasingly intelligent and responsive in how they respond to situations.
Analytics can of course be used in the markets for proprietary trading or client order flow in order to maximize order value or execute the order using an algorithm.
As analytics have been used in the front office for some time, more fertile ground is in using analytics and automation in the back office process to help with settlements, clearing and administering accounts intelligently. There can be a huge business case in adding this form of intelligent automation here.
Example Use Cases
Timeflow integrates with a range of websites, applications, APIs and other data sources across your business to identify and respond to key situations of interest. Examples specific to this industry include:
Example 1 – Trade Execution
A trader would like to place an order for a stock when a 12 month moving average is crossed and the price falls beneath a certain level. Timeflow listens to a price feed and either automatically executes the trade or informs the trader when the condition is met.
Example 2 – Limit Checks
A customer is placing a high number of orders in a volatile market. It is important that they do not breach trading limits to limit credit exposure and for regulatory reasons. Timeflow monitors for this situation and informs relevant people should it occur.
Example 3 – Customer Analytics
A main contractor works with a number of sub contractors to deliver building projects around the globe. One subcontractor is regularly late in delivering their components. This data is captured and flagged on KPI dashboards for relevant team leaders.
Example 4 – Regulatory Reporting
New regulations are published which capital markets need to respond to. We need to quickly respond to these without re-engineering existing systems. Timeflow is deployed to listen to a large volume of low latency data feeds and report on any violations.