THE AI LOOP
Hi everyone,
If you’ve sat with a finance team during close, you’ve seen the pattern.
Long days. Late nights. Large volumes of journals.
Everyone is busy, but no one is sure they reviewed the right entries.
Month-end doesn’t fail because of effort.
It fails because attention is spread across too many items.
That’s the issue this week’s idea addresses.
01. The Use Case: Pre-Posting Journal Risk Review
The Problem: During close, finance teams review everything because they don’t know which journals actually need scrutiny.
They rely on: Amount thresholds, Habit & Gut feel.
Risky journals are often found late, or by auditors. That adds cost and fatigue.
The Solution
Add a lightweight AI layer before posting.
It scans draft journals and flags a small subset that show higher risk:
Unusual size or timing
Manual entries late in close
Weak or repeated justifications
Patterns that were reversed in prior months
The system does not approve or reject entries.
It directs senior reviewers to higher-risk items.
What Changes
Before
4,000+ journals
Broad review effort
Issues found after posting
After
~100–150 journals flagged
Each flag includes a reason
Review ordered by risk
Same team.
Same controls.
Less overload.
Why This Matters
Review effort drops ~70–80%
Close review time moves from days to hours
Fewer post-close fixes
The work doesn’t increase.
The focus improves.
Where This Fails
If explanations aren’t auditable, reviewers won’t trust it
If historical data is poor, risk signals degrade
If it sits outside existing systems, it’s ignored
It only works when it’s explainable and embedded.
Bottom Line
This is not accounting automation but a smart review prioritisation strategy.
Teams using AI before posting won’t close faster by skipping work.
They close faster by reviewing fewer, higher-risk entries.
Want the code? I will publish of exactly how to build this pipeline (Python + OpenAI) on my Medium blog and Github later this week. I'll share the link on LinkedIn when it's live.
Question for you: Which part of your month-end feels most reactive?
Reply and tell me I’ll break one down next.
Until next week,
Asim - The AI Loop