Case Studies · Property & Real Estate
Property Developer (Jakarta)
South Jakarta · 8 weeks of implementation
- 15-20 days → 3 days
- Invoice Cycle
- < 0.5%
- Error Rate
- -65%
- Finance Hours
- +18 days faster
- Cash Flow
end-to-end processing
down from 8-12% previously
time spent on manual entry and validation
average time to receive payment
Challenge
A 3-person finance team processed 200-300 invoices a month manually: entry into accounting, validation, approval, and delivery to tenants. The process took 15-20 days per cycle. An error rate of 8-12% caused disputes and late payments.
Solution
AI Document Processing for automated invoice data extraction + a digital approval workflow + integration with the accounting system. Monthly financial reports are generated automatically.
Business Context
This company manages a portfolio of office buildings and commercial shophouses in Greater Jakarta (Jabodetabek) with more than 180 active tenants. Every month, the finance team has to process rent, service charges, parking, and utilities for hundreds of units. Each one has a different formula based on its contract.
The existing manual process was highly error-prone: a wrong amount, a wrong tenant name, or an invoice sent to the wrong email address led to disputes that took 1-2 weeks to resolve.
Solution Architecture
The implementation covered three layers of automation:
- Document Intelligence: AI extracts data from input documents (lease contracts, utility meter readings, maintenance POs) and calculates the charges automatically according to each tenant's contract terms
- Approval Workflow: invoices above a certain threshold require digital approval from the Finance Manager before they are sent. A process that used to go through email/WA manually is now centralized in a dashboard
- Delivery & Tracking: invoices are sent automatically to the tenant's email on the configured date, with automatic reminders 3 days before and on the due date
- Payment Reconciliation: once a payment comes in, the system matches it against outstanding invoices and updates the status automatically
Operational Impact
The most noticeable change is the speed of the invoice cycle. Tenants now receive invoices 1 day after the period closes, instead of 15 days after as before. With more time to process payments, the average time to receive payment improved by 18 days.
On the quality side: the error rate fell from 8-12% to below 0.5%. Most of the remaining errors come from input data from external sources (such as incorrectly recorded meter readings), not system errors.
“Our finance team used to work overtime at the end of every month. Now the system compiles, validates, and sends the invoices. They can focus on cash flow analysis and planning.”
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Related services: AI Document Processing, AI Finance Automation, AI Workflow Automation.
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