apisq

Our Track Record

Case Studies

A selection of recent engagements across asset management and banking. These represent the collective delivery experience of our founders in solving some of the industry's most persistent operational and technical challenges.

Asset Management C$300bn gross assets

XX Investment Management

Portfolio Management & Benchmarking

XX Investment Management — Portfolio Management & Benchmarking

The Challenge

A portfolio rebalancing and benchmarking system built on Excel, VBA, and C# had been left unmaintained for five years. The models were broken, the original authors had left, and the business team had no capacity to drive transformation themselves. The process consumed hours of manual effort with multiple human touchpoints — yet it sat at the top of the investment function, directly influencing asset allocation decisions for a C$300bn fund.

What We Did

apisq was brought in to own and deliver the full transformation. We rebuilt the process from first principles: a fully automated pipeline with parallel processing, optimised data handling, and outputs streamlined to what the business strictly needed. The system was deployed to a production server running on a schedule, with a self-service mechanism for the business to apply manual adjustments and trigger reruns without technical support.

Outcomes

15 min
End-to-end runtime (down from hours)
6:00 AM
Automated start — results ready on arrival
0
Manual touchpoints in the main process
Asset Management £800bn AUM

XX International

Fund Performance Monitoring

XX International — Fund Performance Monitoring

The Challenge

Fund performance comparisons across multiple geographies relied on someone manually exporting approximately 400 separate Excel files from the Morningstar front-end — a process that constituted a licensing breach and was built on logic nobody fully understood. Two successive owners of the system had left the organisation. Investment managers' compensation was tied directly to these figures, meaning inaccurate or indefensible outputs created regular organisational friction.

What We Did

We replaced the entire manual approach with an automated Python platform that ingests approximately one million rows of Morningstar data per run via API, applies geography-specific peer group logic externalised into config tables, and visualises results in Power BI. Business users can extend the system to new fund types or geographies by editing a table — no code changes required. We also built an AI-assisted release process that auto-generates technical, business, and executive summaries at each release.

Outcomes

400 → 0
Manual Excel file exports eliminated
~1M rows
Morningstar data processed per run
1 hr
Full automated run time
Asset Management £800bn AUM

XX International

Counterparty Risk Management

XX International — Counterparty Risk Management

The Challenge

No consolidated counterparty risk view had ever existed for this organisation's £800bn portfolio. Exposure data was scattered across 75 different source systems — FTP file drops, APIs, databases, and emails — many of which were human-oriented and not designed for machine consumption. The prior approach was rough Excel spreadsheets that could not scale. Without a consolidated view, the firm could not monitor its total counterparty exposure at any meaningful level of completeness.

What We Did

We architected and built a first-of-its-kind global counterparty risk platform from scratch: a robust ingestion pipeline handling all 75 source types, source-specific parsing and standardisation logic, and criticality-tiered processing (warnings for non-critical gaps, automated stop-and-escalate for critical ones, prior-period fallback where appropriate). The result was a consolidated global counterparty risk view with full drill-down capability by source and risk category.

Outcomes

75
Source systems integrated
1st
Consolidated global counterparty risk view ever produced
Growth in the client's department following project success
Banking €413bn total assets

XX Bank

Customer Service Compliance Monitoring

XX Bank — Customer Service Compliance Monitoring

The Challenge

Supervisors could only review approximately 7 calls per week per agent, while each agent handled hundreds of calls. The vast majority of all customer interactions went entirely unmonitored — creating significant conduct risk and regulatory exposure. Netherlands privacy regulations added a further constraint: all personal identifying information had to be masked before any data processing could take place.

What We Did

We designed and delivered a twice-daily batch pipeline: speech-to-text transcription of all calls, automated PII masking to meet Dutch privacy requirements, then text analytics including sentiment analysis and automated compliance scoring. A second workstream — a near-real-time AI assist panel surfacing contextual information on-screen as the customer speaks — was road-mapped and vendor-selected at project handoff.

Outcomes

~7/wk
Calls reviewed per agent before (manual)
~100%
Call coverage achieved with automated monitoring
2×/day
Automated pipeline runs across all calls
Banking $26.6bn balance sheet

XX Bank

Treasury Operations Transformation

XX Bank — Treasury Operations Transformation

The Challenge

The weekly treasury operations process consumed three full working days and was performed entirely by hand — every step manual, no automation tooling of any kind. The client operated under strict tooling constraints: Python and any modern automation framework were not permitted. All work had to be delivered within Excel and VBA alone.

What We Did

We built a custom robotic process automation framework entirely within Excel and VBA, designed around a table-driven instruction model: each row represents one automation step, with columns defining the action, source, target, and parameters. A two-phase execution model first previews required parameters for human review, then executes the full sequence with step-by-step logging. The framework was subsequently rolled out across the broader finance department, enabling non-technical teams to build their own automation.

Outcomes

3 days
Previous weekly process duration
15 min
Process duration after automation
5+
Finance teams using the framework post-rollout
Banking Global Systemically Important Bank

XX GSIB Bank

Product Control & Daily P&L Automation

XX GSIB Bank — Product Control & Daily P&L Automation

The Challenge

The product control function — responsible for the daily P&L and balance sheet for 100+ traders across 20+ trading desks — ran on a highly manual, fragile process that took up to 8 hours to complete each day. Batch processes ran overnight from an offshore team; when they broke, the entire function reverted to full manual execution. System changes took up to 3 months to implement. The original platform had taken 9 months to onboard. With trader compensation tied directly to the P&L figures, any perceived inaccuracy generated significant organisational friction and sign-off overhead.

What We Did

We delivered a cloud-based data ingestion and reconciliation platform that restructured the entire process from the ground up. Twenty-eight source systems were onboarded and reconciled against each other in 4 weeks — a task that had previously taken 9 months. The daily P&L and balance sheet run was compressed from 8 hours to 25 minutes. Management sign-off, previously a manual process of collecting individual controller signatures, was replaced with automated 4-eye digital review — with a real-time CFO-level oversight dashboard available on demand.

Outcomes

25 min
Daily P&L run time (down from 8 hours)
4 weeks
Full platform onboarding across 28 sources (down from 9 months)
Instant
Automated 4-eye sign-off with CFO real-time dashboard

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