收入保障与欺诈管理（RAFM）调查报告

kpmg.com/in KPMG. Make the Difference. Tableofcontents Chapter01 Survey methodology How technology has influenced andtransformed revenue assurance Chapter02 Key focus areas of transformationfrom RA to BA Chapter03 Leveraging the business assuranceframework across and beyond telecom Acknowledgements Foreword KPMG in India conducted a detailed RAFM Survey to evaluate the evolving maturity of Revenue Assurance and Fraud Management (RAFM) functions withinorganisations, with a focus on how these traditional control-centric domains are transforming in response to digital acceleration, advanced technology adoption,and shifting business priorities. The survey was driven by the need to understand how telecom enterprises and adjacent industries are adapting their assurancemechanisms in an increasingly automated, data-rich, and risk-prone environment. Over the past decade, RAFM has shifted from being a reactive gatekeeper for revenue leakage to an intelligence-led framework that must proactively assure notonly revenues but also broader value flows and operational integrity. This survey sought to capture that shift and examine the extent to which organisations areembracing this evolution in their internal governance, systems, technology investments, and strategic outlook. Generative AI is gaining traction in BusinessAssurance, but Agentic AI is emerging fast.Within the next 18 months, Telcos and MVNOsworldwide will start using Agentic AI toenhance decision-making and human-agentcollaboration—freeing up time to scale intomore advanced assurance areas. PurushothamanKGPartner – Advisory Head - Technology Transformation& TelecommunicationKPMG in India Ataglance KPMG’s RAFM survey insights at a glance… Ramping up investments in AI-drivenRAFM transformation Assessment of the current control environment for AI enabled deploymentswill be key to a transformative journey Organisations increasingly see AI-enabled RAFMas a strategic asset organisationsassess risks annuallyand have stressed upontheimportance of AI in real timerisk monitoring have realized theimportance ofAI enabledintelligence for fraudthreat preparedness are currently able toderivefull scale valuefrom their existing AI,ML and RPA tools 26% 47% 14% 30% haveapportioned budgetsfor AI, ML and RPA drivenBusiness Assurance (BA)transformation believe thatAI will drivetransformation in RAFMoperationsdespite currenthurdles organisationsrate risk coverage as“good”while harping on theimportance of continual maturityimprovement with AI haveapprovedplans on improvingtheir analyticspipeline for RAFM agree on the fact thatautomation of theFM environment isseeing growth 42% 53% 40% 76% Transformative BA success depends on matching the right tech and partner to each use case. Awareness of BA challenges drives smarterprioritization have identifiedpartial control testingas a major challengein the current BAenvironment 30% 72% 53% have identified use-cases ofapplicationof block-chain for billing integrity checks haveensured data lake readinessfor ML deployments identify that there arebudgetlimitations in BA areassuch asregulatory reporting, new productdevelopment & asset assurance 36% 48% 35% Are utilizing RPA for workflow automationssuch as alarms and exception closure havecited vendor technology dependenciesas a major bottleneck for BA transformation Surveyfindings Strategic alignment & governance Survey insights into the strategic coherence, governance maturity, and operational robustness of the RAFM function across organisations, including roadmap alignment, risk reviewcadence, control frameworks, and budgetary adequacy. RAFM practices show partial strategic alignment. While some organisations have defined roadmaps andgovernance processes, many rely on reactive risk assessments and face budget constraints. Strengtheningalignment, proactive monitoring, and funding is key to improving RAFM maturity. Technology, automation & AI/ML adoption More than ever before, AI-enabledRAFM is significantly enhancingoperational efficiency and reducingrevenue leakage whilst expandingthe function’s coverage The survey highlights a significant shift in RAFM functions, with widespread adoption of advanced technologies such as ArtificialIntelligence (AI), Machine Learning (ML), Robotic Process Automation (RPA), and Data Analytics. These tools are being leveragedto drive end-to-end automation, enhance fraud detection capabilities, and optimize revenue assurance processes across industries. ThomasGouwsPartner, COO AdvisoryKPMG SA In a fast-paced transformative world from RA toBA, the objective of RAFM operations would not bespend time on how to build insights with complexqueries but what insights can one bring to businessfor informed decision making. AI can prove to be apower catalyst for the same, drastically improvingTAT on operations and becoming outcome driven. RahulHakeemPartner, TMT,Risk AdvisoryKPMG in India RAFM operations are increas