12-month placement, extended to 15 months. Performance, fund and client data; client reporting; AI-enabled process improvement.
One team, several areas of work. An all-round contributor across all of them, with a particular interest in the quantitative side.
Areas of work · Client Reporting
- Generated many types of client reports from internal performance, fund and client data, and contributed to PowerPoint decks.
- Answered client and internal queries, handling ad hoc and recurring requests and due diligence questionnaires (DDQs).
- Prepared holdings analyses, performance comparisons and bespoke data extracts for institutional clients and consultants.
- Delivered accurate, consistent and timely client reporting through month-end cycles by verifying large internal datasets.
- Applied regulatory and labelling guidance to reporting materials with Compliance and investment specialists.
- Coordinated daily reporting handovers with the Vancouver team; hosted team meetings and mentored new joiners.
- Analysed the funds, what makes each different, and the share classes within them.
- Verified fund and share class data on Bloomberg and Morningstar, including setting up client-specific share classes and new Orbis funds.
- Resolved client missing-price queries directly with Bloomberg.
- Rolled out a best-practice distributions process across London and Vancouver: researched it, created standardised documentation and a deck, and presented to the global team.
- Freed time for higher-value work and made processes more consistent by using AI to automate everyday internal tasks; presented the improvements to the team.
- Reduced manual rework and error risk by simplifying complex formulas and embedding automated validation checks in core reporting workbooks.
- Removed legacy tasks by challenging existing processes and analysing workflow dependencies and knock-on effects.
- Wrote documents comparing internal data on how different processes are treated.
Case notes
01
Challenging the default
Questioned decisions and assumptions, tracing their knock-on effects so the team took the right approach.
02
Automating the routine
Used AI to automate everyday internal processes, saving time and making the output more consistent.
03
Knowing the product
Analysed what makes funds, and the share classes within them, different.