Revenue Assurance
Validating how revenue, billing, payments and transactions flow across complex systems. This includes reconciliation, exception analysis, billing validation, payment controls and identification of potential revenue leakage.
Revenue assurance · Financial analytics
Rahul
Revenue Assurance │ Financial Analytics │ Automation │ AI
20+ years across Telecom, Technology & Revenue Assurance — revenue controls, reconciliation, billing validation and financial analytics across Telecom, DTH and OTT, strengthened by automation and AI-driven solutions.
I find where revenue quietly leaks, prove it with data, and build the controls and reports that stop it.
Noida, IndiaFinance · Operations · Data
20+ yrsRevenue AssuranceReconciliationBilling ValidationRevenue LeakageFinancial ControlsAgentic WorkflowsExecutive MISProcess Automation
Revenue AssuranceReconciliationBilling ValidationRevenue LeakageFinancial ControlsAgentic WorkflowsExecutive MISProcess Automation
01 / Capability
What Iwork on.
My work sits at the intersection of revenue processes, financial controls, data analysis and automation. I focus on how transactions move across systems, where mismatches or risks can occur, and how validation and reporting can be improved.
Financial Analytics
Analysing operational and financial data to support reconciliation, variance analysis, forecasting, performance tracking and executive decision-making across high-volume transaction data, MIS and reporting.
Process Automation
Reducing repetitive validation, reconciliation and reporting effort through structured workflows that improve consistency, speed and exception investigation.
Applied AI
Applying Generative AI, LLM workflows, RAG, MCP integrations and agent-based approaches to practical validation, reconciliation, knowledge-based analysis and reporting processes.
Current focus: Applying AI to strengthen business controls and automate knowledge-intensive financial processes.
02 / Professional snapshot
0+
Years across telecom, technology & revenue assurance0%
Reduction in financial discrepancies after post-merger payment-system migration0%
Reduction in reconciliation discrepancies0%
Improvement in revenue forecasting accuracyFigures reflect outcomes from roles held since 2002 across software testing, telecom operations, customer lifecycle management and revenue assurance.
03 / Perspective
A career built around theflow of value.
My career has followed the path of the transaction itself: from the systems that create an event to the financial records that account for it.
Technology & software testing→
Telecom billing & provisioning→
Customer lifecycle & analytics→
Revenue assurance & reconciliation→
DTH & OTT controls→
Automation & applied Generative AI
This progression developed a practical understanding of how operational events affect customer accounts, provisioning, billing, payments, revenue, financial records, reconciliation and management reporting. Today, I use that context to build more reliable controls and more useful analysis.
04 / Career history
Experience withcomplexity.
2011 — Present
Dish TV India Ltd
Deputy Manager, Data Analysis, Finance & Accounts
Promoted to Lead position in 2024
End-to-end EPRS payment and balance assurance across bank entries, DS wallets and customer transaction flows. Leads primary, secondary and tertiary reconciliation, billing validation, financial controls, MIS and reporting support.
- Built a four-agent EPRS validation workflow, reducing manual effort by ~24 hours in monthly and quarterly audit cycles.
- Led post-merger revenue assurance and payment-system migration, reducing financial discrepancies by 60%.
- Improved forecasting accuracy by 30%, reduced reconciliation discrepancies by 70%, and shortened monthly close by 2 days.
2007 — 2011
Bharti Airtel Ltd
Ops Specialist, Customer Lifecycle Management
Managed revenue-focused customer lifecycle initiatives, customer segmentation and campaign analysis across IVR, USSD, SMS, WAP and VMS.
- Improved retention by 12% and ARPU by 15% for targeted segments.
- Improved campaign ROI by 23%.
2003 — 2007
Bharti Airtel Ltd
Executive
Managed customer account creation, service provisioning and billing activation. Validated provisioning, tariff and VAS configurations; supported Switch-to-ARBOR reconciliation and reporting.
- Reduced billing escalations by approximately 12% through improved provisioning-to-billing traceability.
2002 — 2003
Snaz Tech India Ltd
Tester
Performed functional, compatibility and performance testing for e-wallet, e-commerce and CRM applications.
- Identified and tracked 150+ serious software defects.
05 / Selected work
Projects that makecontrols work harder.
Project descriptions abstract internal workflows and do not disclose confidential company data or proprietary systems.
01Case studyReconciliation
AI-assisted EPRS reconciliation & audit workflow
Problem: high-volume distributor wallet-to-customer flows needed repeated manual audit. Approach: a four-agent workflow for source authentication, transaction-flow validation, reconciliation and final reporting.
Outcome~24 hours saved in relevant monthly and quarterly audit cycles.
02Case studyValidation
AI-assisted daily revenue validation
Problem: daily dunning, processing-fee and billing checks were slow and inconsistent. Approach: structured source data, raw MIS, SOPs and knowledge bases feed an LLM-assisted validation that flags exceptions for investigation.
Outcome~6 hours saved per run.
03Case studyAutomation
CAS invoice validation automation
Problem: invoice data arrived as PDF, image, Markdown and CSV. Approach: extract and structure the financial data, reconcile it with source-system records and produce an exception summary.
Outcome~6 hours saved per monthly cycle.
04Case studyReporting
AI-assisted executive reporting
Problem: weekly and monthly management packs drew on 18 product and KPI data sets. Approach: consolidate, validate and gap-check the sources to produce management-ready presentations.
Outcome~4 days of preparation effort saved.
05PrototypeControl tower
DishTV AI Operational Intelligence Platform
Problem: KPIs across business, sales, service, retention and call-centre functions were reported manually. Approach: automated KPI retrieval, analysis and dashboard delivery using n8n, MCP, Python, Azure and interactive dashboards.
OutcomeAutomated daily KPI reporting and AI-assisted operational analysis.
View Project Document ↗06Live productRevenue controls
OTT revenue & billing validation
Validation and revenue-control work for the Fliqs digital content product under Watcho OTT: provisions, tariffs, CAS, payouts, reconciliation, forecasting and MIS.
OutcomeFinancial validation and controls for a live OTT product.
Watcho ↗07Case studyAnalytics
Telecom customer lifecycle analytics
Problem: retention and campaign spend lacked segment-level visibility. Approach: customer segmentation and campaign analysis across IVR, USSD, SMS, WAP and VMS channels to target revenue-focused lifecycle initiatives.
Outcome+12% retention, +15% ARPU for targeted segments, +23% campaign ROI.
06 / Practical applications
AI applied tobusiness controls.
Hands-on work with Generative AI is grounded in real validation, reconciliation and reporting use cases.
Generative AI
Tools in active use
Claude, Claude Cowork, ChatGPT, ChatGPT Codex, Google AI Studio and Gemini.
Workflows
Structured for practical work
Claude Skills, AI-assisted reconciliation, validation workflows, executive MIS, structured and JSON-based prompting, and agentic workflows.
RAG & MCP
Connected context
Experience using retrieval-based approaches with local databases, structured data, folders and knowledge bases, plus connecting and using MCP integrations.
Custom solutions
Built and deployed
Custom GPTs, StockPreditor, dynamic online dashboard concepts, Gemini Gems and Claude Skills.
Python: learning / developing hands-on capability.
07 / Toolkit
Depth acrossthe workflow.
Revenue & Financial Assurance
Revenue AssuranceFinancial ReconciliationRevenue Leakage DetectionBilling ValidationPayment ReconciliationFinancial ControlsAudit ControlsException ManagementRoot Cause Analysis
Data & Analytics
SQLMicrosoft ExcelPower BIMS AccessRevenue AnalyticsForecastingVariance AnalysisAOP vs ActualMISExecutive Reporting
Domain
TelecomDTHOTTSVODTVODTelecom BillingCASProvisioningTariff ValidationCustomer Lifecycle Management
Automation & AI
Process AutomationClaude SkillsGenerative AIAgentic WorkflowsRAGMCP IntegrationsCustom GPTsGemini GemsPrompt Engineering
08 / Selected publications
Writing beyondthe spreadsheet.
The Illusion of Conscious AI
When intelligence becomes measurable, we begin to mistake it for consciousness.
“Intelligence is visible. Experience is not. And we confuse one for the other.”
One Reality, Two Paths
Two paths through suffering, one question: what must we see, and what must we release?
“One path asks, What is always present? The other asks, What happens when we stop clinging?”
08 / Journal
Notes on assurance,numbers and applied AI.
AI & Consciousness02 Sept 20266 minWorking draft
Intelligence is visible, experience is not
A model that answers every question fluently tempts us to call it conscious. The fluency is real; the leap is not. Notes from writing The Illusion of Conscious AI.
Read article↗Consciousness11 Aug 20267 minWorking draft
Two paths, one question
Advaita Vedanta asks what is always present; Buddhism asks what happens when we stop clinging. Two paths through suffering — and what they taught me about framing problems.
Read article↗Applied AI28 Jul 20266 minWorking draft
AI in the workday: solving real problems, not demos
The useful version of AI is not a chatbot on a landing page. It is the boring workflow that gives back six hours before lunch. How I decide what to automate — and what to leave human.
Read article↗Revenue Assurance18 Aug 20266 minWorking draft
Where revenue quietly leaks
Leakage is rarely a single dramatic failure. It is a hundred small mismatches between what was provisioned, what was billed and what was actually collected.
Read article↗Reconciliation02 Jul 20265 minWorking draft
Reconciliation that explains itself
A reconciliation that only proves two totals match is half a control. The useful half is the one that tells you why they did not.
Read article↗Applied AI21 May 20267 minWorking draft
Practical AI for financial controls
AI has not replaced judgement in revenue assurance. It has removed the hours of preparation that used to sit in front of the judgement.
Read article↗Perspective09 Mar 20265 minWorking draft
From billing support to revenue assurance
A career that moved from testing software to owning payment assurance, and what each step contributed to how I read a number today.
Read article↗09 / Contact
Let's discuss thework that matters.
For revenue assurance, reconciliation, financial analytics, controls, automation or relevant opportunities, please get in touch.