Atteindre la maturité en Business Assurance et en gestion de la fraude
Maîtriser les cinq piliers : Organisation, Personnel, Processus, Outils et Influence
La fraude et les pertes de revenus représentent des menaces constantes pour les opérateurs télécoms et les régulateurs, et évoluent au même rythme que les technologies et services. Pour les opérateurs soucieux de sécuriser leurs revenus et protéger l’intégrité de leur activité, une fonction mature de Business Assurance et de gestion de la fraude (BAFM) n’est pas seulement une bonne pratique, c’est une nécessité.
Dans cet article, nous vous présentons les cinq piliers fondamentaux qui doivent être alignés pour développer une fonction BAFM mature et durable : Organisation, Personnel, Processus, Outils et Influence.
Organisation : Structurer pour l’efficacité et l’indépendance
Le premier pas vers la maturité en BAFM est de disposer de la bonne structure organisationnelle. La fonction doit être clairement définie dans l’organigramme de l’entreprise, idéalement opérant de manière indépendante des unités opérationnelles et génératrices de revenus, pour maintenir la neutralité et l’objectivité.
Points clés :
- Établir la BAFM comme département autonome ou l’intégrer à l’audit interne, aux finances ou à la gestion des risques.
- Définir des rôles et responsabilités clairs pour les équipes en charge de la détection de fraude, de l’assurance des revenus et du reporting.
- Garantir un accès direct à la direction pour une meilleure visibilité et influence.
Astuce : L’alignement avec les normes réglementaires ou de gouvernance du groupe renforce la crédibilité et pose les bases d’un déploiement élargi.
Personnel : Développer les compétences et une culture de vigilance
Les ressources humaines sont le moteur d’une fonction BAFM efficace. Même les meilleurs systèmes ne peuvent pas détecter ou empêcher les fraudes sans des professionnels qualifiés et conscients de l’évolution des menaces.
Points clés :
- Recruter ou former des experts en opérations télécom, analyse de données, audit et cybersécurité.
- Promouvoir une culture de responsabilité et de vigilance à tous les niveaux.
- Favoriser l’apprentissage continu et les certifications (ex : CFCA, ACFE).
Astuce : Allier expertises internes et consultants externes pour des perspectives renouvelées et une meilleure capacité d’adaptation.
Processus : Formaliser et standardiser les flux de travail
Des processus bien documentés et reproductibles sont essentiels pour la maturité de la fonction BAFM. Sans procédures opérationnelles standardisées (SOP), même les équipes les plus compétentes peuvent rencontrer des difficultés.
Points clés :
- Documenter les flux de travail pour la détection, l’investigation, l’escalade et la clôture des fraudes.
- Aligner les contrôles d’assurance des revenus sur les principales sources : voix, SMS, data, et mobile money.
- Intégrer les processus BAFM à la gestion des incidents et aux pistes d’audit.
Astuce : Utiliser des indicateurs de performance (KPI) et des journaux d’audit pour mesurer l’efficacité des processus.
Outils : Exploiter l’automatisation et l’intelligence
Le bon système technologique est l’épine dorsale d’une fonction BAFM moderne. Les processus manuels ne peuvent plus suivre le rythme et la complexité des services télécoms actuels.
Points clés :
- Investir dans des outils de surveillance en temps réel, de détection d’anomalies via l’IA et de tableaux de bord personnalisables.
- Assurer l’intégration avec les différentes sources de données : CDRs, facturation, IN, MFS, CRM.
- Automatiser les tâches répétitives : seuils d’utilisation, rapprochement, génération de rapports.
Astuce : Nos solutions S-ONE RA et S-ONE FRAUD sont conçues pour offrir une couverture complète de l’assurance télécom, avec des alertes intelligentes et une détection des fuites de revenus.
Influence : Créer un impact au-delà de l’équipe BAFM
Une fonction BAFM mature exerce une influence au-delà de ses frontières. Elle collabore de manière transversale, obtient le soutien de la direction, et contribue aux décisions stratégiques via l’analyse des données.
Points clés :
- Mettre en place un reporting régulier pour informer les dirigeants des tendances et risques.
- Collaborer avec les départements ventes, marketing, IT et produits pour intégrer la prévention dès la conception.
- Entretenir des relations avec les parties prenantes externes : régulateurs, auditeurs, forums sectoriels.
Astuce : L’influence ne se résume pas à l’autorité, elle repose sur la crédibilité. Des résultats concrets et réguliers renforceront votre légitimité.
En conclusion : La maturité est un parcours, pas une destination
Le développement d’une fonction BAFM ne se fait pas du jour au lendemain. Il s’agit d’une évolution stratégique nécessitant un investissement continu dans les compétences, les processus et la technologie. Mais les bénéfices sont significatifs : augmentation des revenus, réduction des pertes frauduleuses, et renforcement de la confiance des clients et partenaires.
Chez Synaptique, nous accompagnons les opérateurs télécoms dans le renforcement de leurs capacités d’assurance grâce à des outils intelligents, des services experts et des stratégies adaptées.
Achieving Maturity in Business Assurance and Fraud Management
Mastering the Five Pillars: Organization, People, Process, Tools, and Influence
Fraud and revenue leakage are constant threats for telecom operators and regulators that evolve just as quickly as the technology and services we offer. For telecom operators committed to secure their revenues and protect their business integrity, a mature Business Assurance and Fraud Management (BAFM) function is not just a best practice, it’s a necessity.
In this article, we’ll walk you through the five foundational pillars that must be aligned to achieve a truly mature and sustainable BAFM capability: Organization, People, Process, Tools, and Influence.
- Organization: Structuring for Efficiency and Independence
The first step toward maturity in BAFM is having the right organizational structure. A mature function must be clearly defined within the company’s organization chart, ideally operating independently from operational and revenue generating units to maintain neutrality and objectivity.
Key Considerations:
- Establish BAFM as a standalone department or within Internal Audit, Finance, or Risk Management.
- Define clear roles and responsibilities across fraud detection, revenue assurance, and reporting teams.
- Ensure direct access to senior leadership for visibility and influence.
Pro Tip: Alignment with regulatory or group governance standards adds credibility and sets a strong foundation for expansion.
2. People: Building the Right Skills and Culture
People are the engine of a successful BAFM function. Even the best systems can’t detect or prevent fraud without skilled professionals who understand both the business and the evolving threat landscape.
Key Considerations:
- Hire or upskill professionals in telecom operations, data analytics, audit, and cybersecurity.
- Foster a culture of accountability and vigilance across all departments.
- Promote continuous learning and certifications (e.g., CFCA, ACFE) to stay ahead of fraud trends.
Pro Tip: Combine internal experts with external consultants or technology partners for fresh insights and scalability.
- Process: Defining and Standardizing Workflows
Having well-documented, repeatable processes is critical to a mature BAFM function. Without standard operating procedures (SOPs), even skilled teams can falter under pressure.
Key Considerations:
- Document workflows for fraud detection, investigation, escalation, and closure.
- Align revenue assurance checks with key revenue streams: voice, SMS, data, and mobile money.
- Integrate BAFM processes with incident management and audit trails.
Pro Tip: Use KPIs and audit logs to measure process effectiveness and demonstrate value to leadership.
4. Tools: Leveraging Automation and Intelligence
The right technology stack is the backbone of modern BAFM functions. Manual processes can’t scale to handle the volume, speed, and complexity of telecom services today.
Key Considerations:
- Invest in tools that provide real-time monitoring, AI-based anomaly detection, and customizable dashboards.
- Ensure integration across multiple data sources: CDRs, Billing, IN, MFS, and CRM systems.
- Automate repetitive tasks such as usage threshold checks, reconciliation, and report generation.
Pro Tip: Our S-ONE RA and S-ONE FRAUD solutions are purpose-built to provide end-to-end assurance for telecom environments, including intelligent alerting and revenue leakage detection.
- Influence: Driving Change Beyond the BAFM Team
A mature BAFM function extends its influence beyond the boundaries of its own team. It works cross-functionally, gains executive support, and helps shape company-wide decisions through data-driven insights.
Key Considerations:
- Establish regular reporting mechanisms to share trends and risk insights with C-level executives.
- Partner with sales, marketing, product, and IT to embed fraud prevention and assurance early in the service lifecycle.
- Cultivate relationships with external stakeholders like regulators, auditors, and industry forums.
Pro Tip: Influence is not only about authority, it’s about credibility. Consistently delivering results will earn you a seat at the strategy table.
Final Thoughts: Maturity is a Journey, Not a Destination
Maturing your BAFM function doesn’t happen overnight, it’s a strategic evolution that demands investment in people, processes, and technology. But the payoff is significant: stronger revenues, reduced fraud losses, and higher trust from customers and stakeholders.
At Synaptique, we specialize in helping telecom operators level up their assurance capabilities with intelligent tools, expert services, and tailored strategies.
How AI is Transforming Revenue Assurance Systems for Telecom Operators
Smarter, Faster, and More Proactive with S-ONE RA
As margins are thin and services are increasingly complex, revenue assurance (RA) has become a mission-critical function and revenue leakage and fraud continue to pose serious threats to operators’ profitability. Operators are constantly seeking more accurate, efficient, and proactive ways to detect and eliminate revenue leakages across their networks. And today, artificial intelligence (AI) is emerging as the game-changer.
But how exactly is AI transforming revenue assurance systems? What tangible benefits does it offer to RA specialists? And how can telecom operators harness its power to protect every dollar they earn?
Let’s unpack it.
From Reactive to Proactive: Why AI is a Game-Changer for Revenue Assurance
Traditionally, revenue assurance relied heavily on post-event reconciliation and rule-based systems. These systems, while valuable, often reacted to revenue losses after they occurred. Manual audits, static KPIs, and fragmented data sets made it hard to detect issues in real-time, let alone predict them.
AI changes the game. With machine learning algorithms and intelligent data processing, operators can now:
- Analyze massive volumes of transactional and network data in real-time
- Detect anomalies and irregularities as they happen
- Predict potential leakage points before they cause losses
- Automate reconciliation between network, billing, and IN systems
Instead of relying on static rules or periodic audits, AI empowers telecoms operators with systems that adapt to evolving patterns, detect subtle discrepancies, and act faster than ever before.
Key Use Cases: Where AI is Creating Real Value
AI-powered revenue assurance platforms like S-ONE RA by Synaptique are already helping telecom operators secure their revenue in several key areas:
- Intelligent Reconciliation: By leveraging AI, S-ONE RA can reconcile CDRs across the core network (MSC, SGSN/GGSN, SMS-C) and IN in near real-time. This dramatically improves the accuracy of voice, SMS, and data usage billing, preventing discrepancies that often slip through traditional rule-based checks.
- Anomaly Detection: Rather than relying solely on static thresholds, AI models learn from historical data patterns to identify outliers. These could be unexpected usage spikes, mismatched billing entries, or suspicious traffic flows that may indicate configuration errors or fraud.
- Revenue Leakage Prediction: Predictive analytics help identify where future leakage is most likely to occur – whether from faulty provisioning, delayed billing, roaming errors, or even system integration issues.
- Operational Efficiency: AI reduces the need for manual audits by automating routine controls and surfacing only high-priority issues. This allows RA teams to focus on investigation and strategy rather than firefighting.
- Real-Time Fraud Detection and Revenue Protection: One of the biggest advantages of AI in Revenue Assurance Systems is the ability to detect fraudulent behavior in real time. Machine learning models can process vast datasets across services (voice, SMS, data, mobile money), identifying inconsistencies or usage patterns that would go unnoticed by traditional systems.
- Examples of AI-powered detection:
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- Suspicious call routing patterns
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- SIM box fraud detection
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- Unexpected revenue drops or service anomalies
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- Inconsistent IN vs. MSC vs. billing data
These real-time alerts allow operators to act before damage is done, minimizing losses and increasing customer trust.
- Automation and Predictive Insights: Automation is at the core of an AI-enabled revenue assurance strategy. With AI, operators can streamline repetitive tasks such as:
- Reconciliation of transaction logs, CDRs, and billing records
- Threshold-based alerting
- Root cause analysis for discrepancies
Even more powerful is AI’s predictive capability. These systems can learn from historical patterns to anticipate issues like fraud spikes, system bottlenecks, or revenue dips — enabling proactive resolution before they affect the business.
What RA Specialists Need to Know
Revenue assurance teams often ask:
- Can AI replace traditional audit processes? Not replace, but enhance. AI amplifies your control framework by making it smarter and more responsive.
- Will AI increase our workload? On the contrary. AI streamlines monitoring and triage so you can focus on analysis, not chasing false positives.
- Is implementation complex? With the right platform and partner, deployment can be incremental and non-disruptive.
S-ONE RA: Synaptique’s AI-Powered Revenue Assurance System
At Synaptique, we’ve built S-ONE RA to meet the real-world needs of modern telecom operators. It’s more than a tool — it’s an intelligent, scalable platform designed to bring clarity, control, and confidence to your revenue assurance function.
Key Capabilities of S-ONE RA:
- Real-time reconciliation across network elements
- AI-powered anomaly detection and automated alerting
- Customizable dashboards and KPIs
- End-to-end visibility across voice, data, SMS, and mobile money
- Modular design to adapt to your network and services
If you’re looking to modernize your Revenue Assurance System, Synaptique is here to help. Whether you’re just starting or optimizing a mature RA function, S-ONE RA brings the automation, intelligence, and agility you need to stay ahead.
Download the S-ONE RA brochure to learn more, or Schedule a call with our experts to discuss your revenue assurance strategy.
Final Thoughts: The Future is AI-Assisted
Revenue assurance in telecom is no longer just about plugging leaks, it’s about building resilient, intelligent systems that adapt to evolving risks. AI is not a buzzword here; it’s a fundamental shift in how we protect revenue, ensure service accuracy, and build trust with customers.
In the telecom industry billions of transactions occur every day, so ensuring accurate revenue capture and minimizing leakage is essential. Revenue Assurance (RA) teams play a critical role in this effort, relying heavily on actionable insights derived from data. Dashboards are central to this process, offering RA teams the ability to monitor, analyze, and act on key metrics in real-time. Here, we explore the importance of dashboards in revenue assurance and provide a detailed breakdown of the essential dashboards S-ONE RA offers, the metrics they include, and their importance.
1. Revenue Assurance Dashboard
Metrics Included:
- Total revenue generated (daily, weekly, monthly)
- Revenue breakdown by service (voice, SMS, data, roaming)
- Anomalies in revenue trends
- Comparison of projected vs. actual revenue
Why It’s Needed:
This dashboard provides a bird’s-eye view of revenue streams, allowing RA teams to monitor overall performance and detect irregularities quickly. Identifying revenue declines or unexpected spikes ensures that any underlying issues, such as system misconfigurations or fraudulent activities, are addressed promptly.
2.Data Reconciliation Dashboard
Metrics Included:
- Volume of reconciled vs. unreconciled call detail records (CDRs)
- Data reconciliation success rates
- Discrepancies between network records and billing systems
- Mediation system logs for dropped or rejected records
Why It’s Needed:
Accurate reconciliation of data ensures that all usage is billed correctly. This dashboard helps RA teams identify gaps in data processing, such as missed CDRs, and fix issues before they impact revenue. By highlighting reconciliation discrepancies, the dashboard minimizes revenue leakage.
3. Fraud Detection Dashboard
Metrics Included:
- Number of flagged fraud events
- Types of fraud detected (e.g., Simbox bypass,CLI bypass fraud)
- Locations and timestamps of suspicious activities
- Revenue impact of identified fraud
Why It’s Needed:
Fraudulent activities pose significant threats to revenue. This dashboard provides real-time alerts and detailed analyses of fraud patterns, enabling RA teams to take swift action to mitigate risks. It also helps in evaluating the effectiveness of anti-fraud measures over time.
4. Interconnect and Roaming Revenue Dashboard
Metrics Included:
- Revenue from interconnect agreements
- Roaming revenue breakdown by partner and region
- Settlement discrepancies with partner operators
- Trends in interconnect and roaming traffic
Why It’s Needed:
Revenue from interconnect and roaming agreements can be complex to manage. This dashboard ensures accurate tracking and settlement of revenue with partner operators. By identifying discrepancies in real-time, RA teams can avoid disputes and recover potential losses effectively.
5. Customer Complaint Analysis Dashboard
Metrics Included:
- Volume of billing-related complaints
- Average resolution time for disputes
- Financial impact of resolved and unresolved complaints
- Trends in complaint categories
Why It’s Needed:
Customer complaints often highlight gaps in billing accuracy or network performance. This dashboard helps RA teams identify recurring issues, assess their financial impact, and implement measures to improve customer satisfaction and revenue assurance processes.
6. Network Performance Dashboard
Metrics Included:
- Call drop rates and their financial impact
- SMS delivery success rates
- Data session completion rates
- Alerts for network element failures (e.g.,SMS-C, MSC, SGSN, GGSN)
Why It’s Needed:
Technical issues in the network can lead to unbilled usage and lost revenue. This dashboard provides visibility into network performance, allowing RA teams to collaborate with technical departments to resolve issues that impact revenue capture.
How S-ONE RA Delivers Exceptional Dashboards
S-ONE RA, powered by advanced machine learning, offers pre-configured and customizable dashboards tailored to the unique needs of telecom operators. Here’s how it stands out:
Real-Time Data Integration
S-ONE RA seamlessly integrates with mediation systems, billing platforms, and network data sources to provide comprehensive, real-time insights.
AI-Driven Anomaly Detection
Machine learning algorithms continuously analyze data streams to detect and highlight anomalies, enabling proactive resolution of issues.
Customizable Dashboards
Operators can customize dashboards to focus on their specific priorities, such as high-value customers or roaming revenue analysis.
Automated Reporting
Dashboards include automated reporting features that generate summaries for stakeholders, complete with visualizations and actionable recommendations.
Dashboards include automated reporting features that generate summaries for stakeholders, complete with visualizations and actionable recommendations.
Download our S-ONE RA brochure to discover more about the solution to unlock the full potentiel of our dashbords.
For a live demonstration of S-ONE RA’s capabilities, including its powerful dashboards, Book a Call today and see how we can transform your revenue assurance processes.
Conclusion
Dashboards are indispensable tools for revenue assurance teams, offering clarity, control, and actionable insights to safeguard revenue and enhance operational efficiency. With S-ONE RA’s advanced dashboards, telecom operators gain the power to monitor critical metrics, identify revenue leakage, and drive sustainable growth.
For a live demonstration of S-ONE RA’s capabilities, including its powerful dashboards, contact us today and see how we can transform your revenue assurance processes.
Ensuring Accuracy in Data Reconciliation between CGSN and IN for 2G/3G and 4G Networks
Introduction
Data usage records are logged by various network nodes, such as SGSN/GGSN in 2G/3G networks and SGW/PGW in 4G networks. These records, known as data session EDRs (Event Detail Records), capture critical information about data sessions, including the volume of data used, session duration, and charging details. Meanwhile, the Intelligent Network (IN) records the billing details associated with these data sessions. Reconciliation between between CGSN and IN sources is essential to ensure accuracy in billing, revenue assurance, and network management. In this blog post, we will explore the importance of reconciling these data records, the challenges involved, and how Big Data tools like Apache Spark can streamline this process.
Why Data Records Reconciliation is Important
- Accuracy in Data Billing: Each data session, whether in a 2G/3G or 4G network, must be accurately billed to the customer. Discrepancies between the volume of data recorded by the CGSN and the charges recorded by the IN can lead to billing errors, causing revenue loss and customer dissatisfaction.
- Revenue Assurance: Ensuring that all data usage is correctly captured and billed is crucial for preventing revenue leakage. Reconciliation helps identify missing, duplicated, or incorrect records, allowing operators to correct discrepancies proactively.
- Network Performance Monitoring: Reconciliation can also provide insights into network performance by comparing the expected usage (as recorded by SGSN/GGSN or SGW/PGW) with the actual charges. This helps operators in network planning and optimization.
How to Achieve Data Records Reconciliation between CGSN and IN?
- Matching Using MSISDN, IMSI, and Timestamp:
- MSISDN and IMSI are unique subscriber identifiers that link data sessions across network and billing systems.
- The timestamp is a crucial attribute that captures the start and end times of a session. Matching records based on MSISDN, IMSI, and timestamp helps in accurately linking data usage records from CGSN and IN.
- Using a Unique Correlation ID:
- Some systems generate a unique correlation ID for each data session, linking records between the network and billing nodes seamlessly. This ID makes reconciliation straightforward by directly associating each data session with its corresponding billing record.
- However, in many instances, this unique ID is not available, complicating the reconciliation process.
Challenges in Data Records Reconciliation?
- Absence of a Unique Correlation ID:
- When there is no unique ID linking records between CGSN and IN, operators must rely on MSISDN, IMSI, and timestamp for matching. This approach is prone to errors, especially when dealing with sessions that start and stop frequently or overlap.
- Time Synchronization Issues:
- Even a minor time discrepancy between SGSN/GGSN (or SGW/PGW) and IN can lead to unmatched records. These discrepancies can arise due to differences in system clocks, network delays, or processing times.
- To address this, operators often use a time window to match records, where sessions are considered correlated if their timestamps fall within a predefined range, such as ±10 seconds.
- Handling High Volumes of Intermediate Records:
- Data sessions often generate multiple intermediate records, especially during long or fragmented sessions. These records need to be consolidated into a single session record before reconciliation.
- For 4G networks, SGW/PGW may generate separate records for different parts of a session, further complicating the consolidation process.
Leveraging Big Data Tools for Efficient Reconciliation?
- Using Apache Spark:
- Apache Spark’s distributed processing capabilities are ideal for handling large volumes of data records from both CGSN and IN. It allows for efficient matching of records based on multiple keys like MSISDN, IMSI, and timestamp.
- Spark’s in-memory processing reduces latency, enabling near real-time reconciliation, which is critical for maintaining billing accuracy and revenue assurance.
- Consolidating Intermediate Records:
- Spark can aggregate multiple intermediate records into a single session based on MSISDN and IMSI, while applying business rules to filter out duplicates and handle overlaps.
- For example, all records with the same MSISDN and IMSI within a session can be grouped together, and their data volume and duration summed to create a consolidated record.
- Handling Time Differences:
- Spark’s window functions allow for flexible time-based grouping and aggregation. A time window can be defined to match records with slight timestamp differences, accounting for system clock discrepancies between CGSN and IN.
- This helps in accurately correlating records, even when exact timestamps do not match.
- Scaling with Data Growth:
- As data usage continues to grow, the volume of EDRs from SGSN/GGSN and SGW/PGW increases exponentially. Spark’s ability to scale horizontally by adding more nodes to the cluster ensures that reconciliation processes can keep pace with the growing data volumes without compromising performance.
Introducing S-ONE RA: Your Trusted Reconciliation Engine
At Synaptique, we understand the complexity of reconciling data across diverse telecom environments. That’s why we developed S-ONE RA—our powerful, vendor-agnostic reconciliation solution designed to ensure end-to-end accuracy in your telecom data, whether you’re reconciling MSC vs. IN for voice and SMS or CGSN vs. IN for data sessions in 2G, 3G, or 4G networks.
What Makes S-ONE RA Different?
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Multi-Technology Support: Handles CDRs and EDRs from MSC, SMSC, SGSN/GGSN, SGW/PGW, and IN for 2G, 3G, and 4G networks.
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Correlation Without IDs: When correlation IDs are missing, S-ONE RA intelligently matches records using MSISDN, IMSI, and timestamp-based logic.
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Consolidates Intermediate Records: Automatically groups and aggregates intermediate or fragmented records into a single session—perfect for long calls or data sessions with multiple handovers.
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Built on Big Data Tech: Powered by Apache Spark, S-ONE RA processes high volumes of data in near real-time, ensuring performance and scalability.
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Audit Trail and Reporting: Every reconciliation result is logged with explanations, summaries, and drill-down capabilities for audit and compliance purposes.
Whether you’re tackling billing accuracy, revenue assurance, or data integrity challenges, S-ONE RA provides you with the automation, scalability, and intelligence you need.
For a live demonstration of S-ONE RA capabilities, Book a Call today and see how we can transform your revenue assurance processes.
Conclusion
Reconciliation of data records between SGSN/GGSN (or SGW/PGW) and IN is crucial for accurate billing, revenue assurance, and network management. Despite the challenges such as the absence of a unique correlation ID, time synchronization issues, and high volumes of intermediate records, big data tools like Apache Spark provide a robust solution. Spark’s distributed processing, in-memory computation, and advanced aggregation capabilities enable efficient and scalable reconciliation, ensuring data integrity and billing accuracy.
In the next blog post, we will provide a step-by-step guide on implementing a Spark-based data records reconciliation pipeline, complete with code examples and best practices. Stay tuned.
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