Most finance teams treat all accruals as equally complex. They are not. The monthly software subscription accrual is not a judgment call - it is the same number every month until renewal. The legal reserve accrual requires attorney input and CFO judgment. Treating them the same means the finance team spends equal time on both. AI fixes this by handling the predictable ones automatically.

Step 1: Categorize Your Accruals

Pull the last 6 months of accrual journal entries from the ERP. Sort by account and vendor. For each recurring entry (same account, same vendor or department, posted every month), ask: does the amount follow a predictable pattern? If yes, it is a recurring automatable accrual. If the amount requires business judgment each month (legal estimate, restructuring reserve, warranty calculation), it is judgment-intensive.

Expected result: 60-70% of monthly accrual entries will be recurring. These are your automation candidates. The remaining 30-40% remain manual - and after automation, the finance team has the time to do them properly instead of rushing because close is already 4 days in.

Step 2: Build the Recurring Accrual Baseline

For each recurring accrual, document: GL account, vendor or department, calculation basis (monthly flat amount, formula based on a driver, percentage of revenue), 12-month history of posted amounts, and any known future changes (contract renewal date, price adjustment).

This baseline document is the input for AI configuration. It is also useful for its own sake - most finance teams discover they have never had a complete documentation of all recurring accruals in one place. Some discover accruals that have been posting for years that are no longer appropriate.

Step 3: Configure AI Accrual Proposals

ChatFin is configured with the recurring accrual baseline. For each entry, the AI is set to query the ERP for prior period data, calculate the proposed amount using the documented formula, and generate a proposal entry with the calculation displayed for finance review. The finance team sees: account, vendor, proposed amount, calculation basis, prior period amount, and any variance flag.

Variance flags trigger automatically when the proposed amount deviates significantly from the trailing average. Finance decides whether to accept the proposal, override it, or investigate the variance. See AI for Accruals .

Step 4: Run UAT and Adopt

Month 1: AI generates proposals alongside the manual accrual process. Finance compares AI proposals to their manual entries. Document matches and investigate variances. Most variances are calculation differences (AI uses 12-month average; finance used last month's amount). Adjust the AI formula where the variance represents a better approach.

Month 2: run parallel again with formula adjustments applied. This month should show 95%+ match rate. Finance signs off on the AI accrual proposals and transitions to proposal review mode: AI generates, finance reviews and approves, no separate manual calculation.

60-70%
of accruals automatable
30 min
accrual review vs 4-6 hours manual
0
accruals posted without finance approval

What Results to Expect

Accrual processing time: from 4-6 hours of manual calculation and entry to 30-45 minutes of proposal review. Quality: AI proposes 100% of recurring accruals every month - no missed accruals due to staff turnover or close-week time pressure. Finance team capacity: 3-5 hours per close redirected from routine accrual calculation to judgment-intensive accruals and analysis.

The judgment-intensive accruals that remain manual actually get better attention after automation - the finance team has time to research the legal reserve properly instead of estimating because they ran out of time. This is the quality improvement that does not show up in the time savings metric but matters significantly for financial statement accuracy.

Automate the Predictable, Invest in the Judgment

Accrual automation is not about removing human judgment from the close. It is about directing human judgment to the accruals where it matters. The 60-70% that are predictable do not need judgment - they need consistency. AI provides that. The 30-40% that require judgment get the full attention of the finance team instead of being rushed through a tired close-week process.

See ChatFin Accrual Automation

Frequently Asked Questions

What percentage of accruals are automatable?

Based on ChatFin customer data, 60-70% of monthly accruals are recurring and pattern-based - the same account, same vendor or department, with a predictable amount. These are automatable with AI pattern analysis. The remaining 30-40% are judgment-intensive estimates that require human assessment.

How does AI know what amount to accrue?

For recurring accruals, AI queries the prior 12 months of accrual history for that account and vendor from the ERP. It calculates the 12-month average, the most recent 3-month average, and any trend. It proposes the current period amount with the calculation displayed for finance review.

What triggers a manual override of an AI accrual proposal?

Finance overrides AI proposals when: the current period has a known one-time change (a vendor price increase, a new contract, a change in service volume), the prior period pattern is not representative (seasonal business, implementation year), or the proposed amount is above a materiality threshold that triggers additional review.

Does AI post accruals directly?

Not by default. ChatFin proposes accrual entries with supporting calculations. Finance reviews and approves. Write-back posting capability is available for approved recurring accruals after UAT sign-off, but this requires explicit configuration and finance team authorization.

How long does accrual automation take to set up?

The accrual baseline documentation (Step 2) takes 2-4 hours to complete for most mid-market finance teams. Configuration (Step 3) takes 1-2 days. UAT (Step 4) takes 2 months of parallel comparison. Total time to full AI-assisted accrual processing: approximately 10 weeks including UAT.