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Use case

Reconciliation Automation

Month-end means humans matching lines between systems that almost agree — high-skill people doing find-the-difference puzzles under deadline.

What can be automated in reconciliation automation? With current AI and integration tooling: rule-based matching across sources; ai-assisted matching on fuzzy/partial cases with confidence; aging and escalation of unmatched items; journal suggestions for standard differences. What should remain under human control: approval of all journal entries; investigation of true exceptions; write-off decisions. Olyra implements this with confidence scoring, audit logging, and human-review gates matched to risk.

The manual reality

What this work looks like today

Who does it

Accountants, controllers, finance ops — during exactly the days they can least spare.

Typical systems

GL/ERP, bank feeds, payment processors, subledgers, and the master spreadsheet of shame.

The cost

Measured before we touch anything: Match rate automated · Hours per close · Days to close

What changes

What gets automated — and what stays human

Automated (with logging):

  • Rule-based matching across sources
  • AI-assisted matching on fuzzy/partial cases with confidence
  • Aging and escalation of unmatched items
  • Journal suggestions for standard differences

Stays under human control:

  • Approval of all journal entries
  • Investigation of true exceptions
  • Write-off decisions
Measurement & governance

How value and risk are managed

Measure

What we baseline and track

Match rate automated · Hours per close · Days to close · Aged unreconciled items

Governance

Risks designed for

Segregation of duties preserved; every auto-match traceable to its rule; audit-ready logs by design.

Typical implementation path: One reconciliation (bank or processor) piloted on last quarter; expand account by account. Implementation follows the Olyra 120: pilot on real historical volume, parallel run, then measured cutover.

Find out what AI can actually do for your operations.

Start with an AI Operations Audit — a fixed-scope diagnostic that maps your workflows, scores your AI readiness, and hands you a prioritized 120-day roadmap. If we don't find real opportunities, you'll know that too.

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