The Challenge
The firm (one of the UK's leading independent chartered accountancy and business advisory practices) had reached a tipping point with its client data.
Years of growth across multiple service lines had left client information fragmented across legacy systems, with duplicated records, inconsistent data capture and no single unique identifier tying a client's many engagements together.
The firm had recently received a series of negative audit reviews driven by these legacy systems, siloed data and heavily manual processes. A lack of system integration, thousands of duplicate client records without a unique identifier, and outdated tooling meant the firm was tied to inefficient workflows and unable to migrate confidently to modern platforms and ways of working.
Without a single source of truth, data quality and confidence were low and reporting was unreliable. It undermined decision-making, increased compliance effort and limited the firm's ability to scale or onboard complex clients.
Critically, AML and KYC activity depended on inconsistent data spread across its practice management system, AML tooling, spreadsheets, SharePoint and shared drives, making every compliance review slower and harder to evidence.
Objectives
The programme set out to give the firm a clean, trusted and scalable client data foundation. The purposed was to create the underlying data and architecture layer the firm needed to modernise. The core objectives were to:
- Establish a single source of truth for client data, with a unique identifier across every client group.
- Rationalise tens of thousands of duplicated and fragmented records into a structure the firm could understand and report on.
- Cut the time and manual effort involved in onboarding and AML/KYC review.
- Strengthen compliance evidence, data governance and access control.
- Build a modular, API-ready architecture that avoids single-vendor lock-in and prepares the firm for future integrations and AI.
Approach
Pace partnered with the firm's leadership team to shape a shared vision for a scalable, secure client lifecycle model. Through a series of leadership interviews, workshops and technical deep dives, we identified the core system and data constraints that were limiting operational efficiency and compliance capability. The process surfaced 112 potential improvements across 17 initiatives, with 77% of process pain points relating to onboarding.
Rather than reach for an off-the-shelf product that would simply impose another vendor's data model, Pace took a holistic, end-to-end view. We designed a client lifecycle system of record on Microsoft Dataverse, Power Platform and Fabric, underpinned by a rationalised data model capable of linking companies, individuals, client codes, services and compliance information, with the firm's own clean data as the stable layer beneath every future technology decision.
Implementation
Pace delivered a targeted data cleanse and migration exercise across the firm's practice management system and related datasets, untangling years of legacy complexity, clarifying data ownership and eliminating duplicated and misplaced records. Every record was reviewed, cleansed and assigned a rationalised ID and rationalised name: a single unique identifier across each client group. As a result, each client now appears once in the system of record, with full visibility of which teams across the firm are working with them.
In parallel, Pace designed and built the supporting architecture and governance: an AML/KYC screening process that reduces manual compliance effort and supports ongoing monitoring; RBAC controls and data-ownership steps to strengthen security; and Fabric-based reporting and storage patterns, including support for lost clients and historic data visibility. The data was also enriched and validated against external reference sources, (including Companies House and Charity Commission numbers, address fields, individual and corporate details) and the whole solution was handed over with full technical, compliance and operational documentation.
83% Reduction in onboarding and AML review time.
Cut complexity. Improve compliance. Free up fee-earners.
Results
The programme delivered a measurable step-change in data quality, compliance efficiency and architectural readiness:
- Client records rationalised from 45,374 fragmented client codes to 26,476 grouped records, removing 18,898 duplicate or fragmented records and cutting record complexity by approximately 42%.
- Onboarding and AML review time reduced by around 83%, from roughly 30 minutes per review to under 5 minutes, saving an estimated 50 hours per month, or around 600 hours per year, across approximately 120 monthly checks.
- Companies House coverage transformed: records with a valid, cleansed Companies House number rose from 1,038 to 16,720, with 15,682 numbers newly matched and validated through the cleanse.
- Charity Commission data captured for the first time: from 0 to 4,126 validated Charity Commission numbers.
- 10,000+ existing clients imported into the AML screening platform for ongoing monitoring.
- Approximately £192.7k of quantified annual benefit identified, around £150k in capacity savings and £42.7k in licence savings.
- An estimated £424k in avoided annual cost (roughly 87% lower) by enabling a screening-based route (~£61.9k p.a.) rather than an alternative market option (~£486k p.a.).
Beyond the numbers, the firm now has a cleaner, more secure and more scalable client data model. It can link individuals and organisations across its client base, run more consistent AML checks, report with confidence, and integrate external data sources such as Companies House, the Charity Commission and address APIs. The modular, API-ready architecture means the firm can upgrade its practice management system, swap or add future AML vendors, and adopt AI-enabled tools — without being locked into any single vendor's proprietary model.
Before Pace, the firm's client lifecycle data was fragmented across legacy systems, duplicated records and manual compliance processes. Pace delivered a foundational system-of-record architecture and data transformation that rationalised 45,374 records into 26,476 grouped, cleansed client and entity records — reducing record complexity by approximately 42% and creating a more secure, efficient and future-ready operating model.
