The Biryani Heist
Why a ₹70,000 Crore Scam is a System Failure, Not a Data Victory
Usually, the worst surprise hiding in a plate of authentic Hyderabadi biryani is a rogue cardamom pod that ruins your bite.
But recently, revenue authorities uncovered something much harder to swallow, a staggering ₹70,000 crore tax evasion scam, served hot from a routine restaurant inspection.
The recipe for this fraud?
Over 1 lakh restaurants manipulated their billing software to quietly delete cash transactions before filing their returns. It took an intensive investigation, the deployment of AI, and the parsing of 60TB of data to finally catch the scent.
Headlines are painting this as a massive win for data analytics. But if we pull back the curtain on public sector revenue management, a more uncomfortable truth emerges.
The Post-Facto Fallacy
When you uncover evasion of this magnitude post-facto, more than half the battle is already lost.
Identifying a ₹70,000 crore hole years after the money has vanished isn’t a victory; it’s a financial autopsy.
Recovering dispersed, hidden, or spent capital is a massive drain on government resources, often yielding pennies on the dollar.
In my work leading Financial Forensics & Intelligence initiatives across the Asia Pacific region, my core mandate is to empower government and state authorities to prevent exactly this type of systemic leakage.
By arming tax administrations with proactive, forensic-grade Data & AI insights, we shift the paradigm from reactive audits to proactive, surgical intelligence. The result?
Usually billions in actual revenue recovery, secured before the funds ever leave the ecosystem.
We cannot afford to keep building better nets just to catch the fallout. We need predictive infrastructure that stops the leak before the drop falls.
Proactive Management & Financial Forensics
When 1 lakh entities coordinate to hit delete on their ledgers, standard auditing fails. Here is how Data & AI must be engineered to transform tax administration from a reactive trap into a proactive, forensic engine:
1. Managing Taxpayer Data
The Bedrock of Intelligence Fraud thrives in data silos.
The biryani scam worked because point-of-sale data wasn’t talking to broader financial networks. A cohesive data strategy begins with unified ingestion. By integrating GST networks, digital payment gateways, property records, and vendor supply chains into a centralized data lakehouse, we create a single, immutable source of truth. AI steps in here to sanitize data, handle fuzzy matching across disparate ID systems, and stitch together a comprehensive 360-degree financial profile.
2. Establishing Behavioral Patterns & Tracking Deviances
Static rules are easily bypassed by anyone who understands where the tripwires are hidden. We must move toward adaptive AI oversight. By establishing hyper-personalized baselines for every taxpayer, machine learning models continuously monitor operational behavior. Instead of waiting for a quarterly batch-run, these systems flag anomalous patterns, like a sudden spike in cancelled invoices or a divergence between utility consumption and reported output in real-time.
3. AI-Driven Financial Forensics: Reconstructing the Shadow Ledger
Data doesn’t just vanish. Financial forensics is the art of untangling the web to reconstruct the “shadow ledger.” When businesses attempt to erase digital paper trails, advanced forensics utilizes Natural Language Processing (NLP) to parse unstructured data—emails, contracts, and audit logs—flagging discrepancies between internal communications and official filings. It reconstructs the timeline of financial events to prove intent, transforming a suspicion of deleted data into an evidentiary trail that holds up in a tribunal.
4. Unmasking Collusions & Tracing Beneficial Ownership
Evasion at the ₹70,000 crore scale is rarely a lone-wolf operation. It requires syndicates. AI-driven graph network analysis is the ultimate forensic tool here.
It maps complex relationship webs to uncover both external and internal collusions. Externally, it peers through layers of shell companies to identify the Ultimate Beneficial Owner (UBO), tracking illicit capital flights across borders. Internally, it can track anomalies within the tax administration itself flagging if specific officers consistently approve unusual deductions, or if access logs show inappropriate modifications to taxpayer records.
5. Prioritizing to Maximize Recovery Yield
Not every red flag deserves the same deployment of forensic resources. If an AI system flags 50,000 anomalies, how do you decide where to send your human auditors first?
Predictive models assess the propensity to pay and the likelihood of recovery. By evaluating the scale of the evasion against the complexity of the audit and the asset liquidity of the evader, AI ranks cases by their projected ROI. This ensures public sector resources are surgically deployed where they will yield the maximum actual recovered revenue, not just the highest theoretical assessment.
6. Intelligent Enforcement and Tailored Recovery
This is perhaps the most critical component of applied AI ethics in public governance. When we look at compliance, we must acknowledge that not all non-compliance is syndicated malice. Sometimes, defaults stem from systemic friction, complex regulatory burdens, or temporary operational struggles.
Instead of swinging a blunt enforcement hammer, like blanket account freezes at every flag, intelligent forensic systems trace the anomaly to understand the why.
For genuine struggles, the system carves out personalized recovery paths:
Automated nudges
Tailored payment installment plans, and
Proactive compliance assistance.
We reserve the heavy forensic artillery, deep-dive audits and legal asset seizure for calculated, large-scale evasion. Needless to say, optimzation principles must be deeply baked into ensure where we put in our efforts to maximize the recovery.
Managing the Kitchen
Innovation in public sector revenue isn’t just about deploying a shiny new algorithm to audit old data.
It’s about systemic integration, continuous behavioral monitoring, and deep financial forensics that protect the public purse ethically and effectively.
We need to stop trying to un-cook the biryani, and start managing the kitchen better. If not for anything, for the beloved Biryani’s sake!
Link to the News Article: https://www.hindustantimes.com/india-news/how-a-biryani-joint-check-in-hyderabad-uncovered-a-rs-70-000-crore-tax-evasion-scam-across-india-101771478527422.html