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Client Outcomes, Without the Hype

These anonymised examples show how teams use ReconcileIQ, CodeIQ, and LedgerIQ to reduce manual effort and improve confidence in month-end numbers.

To protect confidentiality, company names are withheld and outcome figures are shown as customer-reported ranges from early rollout periods.

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UK D2C Retailer Stabilises Month-End Reconciliation

An online retailer (name withheld) taking payments through Stripe, PayPal, and direct bank transfer.

The Challenge

The owner was spending around 6-8 hours each month reconciling payout batches and processor fees. Differences between settlement dates and order dates created frequent mismatches, so month-end checks often rolled into weekends.

The Solution

The team implemented ReconcileIQ Pro to match processor exports against bank and ledger records, then added LedgerIQ for cash-flow visibility. The rollout focused first on transaction matching quality, then on reporting consistency.

The Results

80-90% Reduction in Reconciliation Effort
45-60 Minutes per Month
£1.2k+ Historic Fee Gaps Identified

After onboarding, month-end reconciliation moved from a half-day task to a short monthly review. The team also corrected previously missed processor-fee entries and gained more reliable cash position reporting.

"Before this, month-end was a Saturday job. Now it is a short checklist and we trust the numbers."

— Founder, UK D2C Retailer (anonymised)

Regional Accounting Practice Standardises Reconciliation Across the Team

A 14-person practice supporting SME clients across Xero, QuickBooks, and Sage.

The Challenge

The team relied on manual reconciliation and manual transaction coding for most clients. Month-end close regularly slipped, partner review queues grew, and onboarding new clients increased pressure on delivery timelines.

The Solution

The practice rolled out ReconcileIQ for a common reconciliation process, then introduced CodeIQ for coding support and LedgerIQ for variance checks and reporting reviews. They deployed in phases by client segment to maintain quality control.

The Results

65-75% Less Reconciliation Time per Client
15-20% Increase in Active Client Capacity
1-2 Days Faster Month-End Close

Per-client reconciliation shifted from hours to a structured review cycle, with more work completed by exception rather than line-by-line checking. The practice expanded capacity without immediate hiring and reported more consistent review quality across managers.

"We did not buy this to replace people. We bought it to remove repetitive work so seniors can review exceptions and advise clients properly."

— Practice Manager, UK Accounting Firm (anonymised)

Multi-Entity Logistics Group Improves Control Across High-Volume Operations

A UK/EU logistics group with multi-currency banking and several regional finance teams.

The Challenge

Finance teams were reconciling high transaction volumes across multiple entities with inconsistent workflows and heavy manual coding. Audit preparation required significant back-and-forth to evidence adjustments and inter-company movements.

The Solution

They implemented ReconcileIQ and CodeIQ in staged rollout by region, then introduced LedgerIQ for consolidated variance and cash-flow monitoring. The emphasis was governance first: consistent matching rules, clear exceptions, and repeatable reporting.

The Results

60-70% Less Daily Reconciliation Effort
50-60% Reduction in Manual GL Coding
~40% Faster Audit Prep

The finance function reported clearer month-end ownership, faster preparation of audit evidence, and less time spent on repetitive coding work. Internal reporting cadence improved because teams could spend more time reviewing exceptions instead of building reconciliations from scratch.

"The biggest gain is control, not just speed. We can explain adjustments quickly, and auditors can follow the trail without extra reconciliation packs."

— Group Financial Controller, Multi-Entity Logistics Group (anonymised)

Want Similar Outcomes in Your Workflow?

If you want a realistic view of fit, we recommend starting with one workflow (reconciliation, coding, or reporting), measuring baseline time and error rates, then expanding once results are proven.

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