Financial Services
Automation & Cloud Analytics
A City Financial Services firm wanted us to establish cloud reporting; we needed just a week to launch the delivery.
Days #1 and #2 were focused on 'speed business analysis' - meeting individually with stakeholders to identify the top business priorities and limiting each conversation to the length of a coffee! In parallel, a second member of our team worked with IT to confirm which of the technologies already in their stack we would use to get going with the delivery. By the end of day #3 we'd built out a product backlog in Microsoft DevOps and designed a starting technical architecture; by the end of day #5 we'd agreed Return on Investment metrics and refined key deliverables, ready for implementation to commence the following week.
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Process Automation
During the engagement we worked across the front, middle and back office, supporting prop and agency trading desks and also research analysts. We delivered process, reconciliation and reporting automation, opening up trade opportunities and identifying compliance issues.
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The flowchart above shows an example of an Ops daily process that we overhauled in two weeks. The original procedure was fully manual, time-consuming and error-prone. To improve it - with minimal disruption to the already busy team - we retained the existing MS Excel front-end but blended critical investigation activities with automated steps.
Power BI Reporting
During the engagement we worked to improve revenue reporting, and linked to this we created a new MS Power BI Management Information dashboard. As demonstrated by the flowchart, we transformed the reporting from a fully manual, monthly process - which simply provided data as a snapshot - to an automated dashboard that refreshed daily, could be consumed on-demand and offered users the ability to more easily interrogate and visualise the data.
Cloud Analytics
The firm had no centralised nor systematic way of interrogating data and producing analytics, making it hard to meet business needs.
To mature their analytics capabilities we set up an MS Azure Data Lake, creating a 'single source of truth' and enabling the customer to rapidly analyse multiple years' worth of trading data.
We established this architecture in parallel with working on more urgent deliverables to ensure that business staff continued to gain new value from our output at least every two weeks.