What the hospital was dealing with
The hospital chain was losing 4.2% of its total billable revenue to insurance claim denials — a figure that translated to ₹1.1 Cr in annual leakage. Claims were submitted manually by a 6-person billing team who logged into multiple insurer portals individually each day.
Errors — wrong patient IDs, missing authorisation codes, incorrect ICD-10 codes, or incomplete discharge summaries — were only discovered when denial letters arrived 3–5 weeks later. By then, the claim had aged significantly, and resubmission was time-consuming.
The CFO had no real-time view of pending collections or denial patterns. Financial reporting was done monthly in Excel, making it impossible to identify systemic billing errors quickly enough to correct them.
How Goolk AI approached it
Goolk AI built a claim-scrubbing and submission automation engine that sits between the hospital's billing system and insurer portals.
Pre-submission Scrubbing: Every claim is automatically validated before submission — checking patient ID formats, ICD-10 code validity against treatment records, authorization code presence, and insurer-specific formatting rules. Any claim that fails validation is flagged to the billing team with an actionable error code before it is submitted.
Automated Submission: Validated claims are batched and submitted to insurer portals via robotic process automation. The system handles 12 different insurer portals used by the chain's patient mix.
Status Monitoring: A daily scraper checks claim statuses on all portals and automatically identifies denials or pending queries within 24 hours of occurrence — versus the previous 3–5 week discovery window.
CFO Finance Dashboard: A real-time collections dashboard gives the CFO daily visibility into pending claims, denial trends, aging buckets, and department-wise billing performance.
Measured results at 90 days
In the first 90 days post-launch, the system pre-screened over 400 erroneous claims before they were submitted, preventing denials that would have previously cost weeks of recovery effort.
The hospital recovered ₹85 Lakhs in previously denied and delayed claims through accelerated resubmission. Total denial rates dropped 25% compared to the pre-deployment baseline. Average claim reimbursement cycle improved from 42 days to 31 days. The billing team — previously overwhelmed with error chasing — was reassigned to higher-value revenue optimization tasks.
The system recovered its full investment cost in the first 3 weeks through ₹85L in recovered denied claims.
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What we built it with
How we delivered it
Denial history deep audit
Audited 2,400 historical denial letters across all 12 insurer partners. Extracted and categorised the top 34 recurring error patterns and code mismatches.
Scrubbing engine & ICD-10 validation build
Built the rule engine with 340+ validation checks covering ICD-10 validity, CPT code mapping, authorisation requirements per insurer, and patient ID format rules.
Insurer portal RPA integration
Configured RPA bots for 12 insurer portals. Built status scrapers with daily automated denial detection and alert routing to the billing team lead.
CFO dashboard & billing team training
Launched the real-time finance dashboard. Trained billing teams to triage scrubbing alerts and retrained on correct ICD-10 coding for top-denial procedure types.
We recovered our entire software investment in Goolk AI within the first three weeks of deployment. The pre-submission scrubbing algorithm is extraordinarily robust. Our CFO now has daily visibility she never had before.Chief Financial OfficerBangalore Care Multi-Specialty Chain
Ready to see results like these for your hospital?
Book a free clinical IT consultation. We will audit your workflows, analyze your existing systems, and give you an honest roadmap — no sales pitch, no obligation.
