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  • Five key reasons why telcos need to focus on Margin Assurance

    Five key reasons why telcos need to focus on Margin Assurance

    Digital disruption, technology innovation, and the hyper-evolving telecommunication market influence a CSP’s ability to maintain long-term profitability.

    Margin assurance is a field that draws on many streams to balance costs and spends. It includes handling a complex mix of service offerings, defining a holistic view for cost allocation, enabling real-time visibility, margin automation, etc.

    What makes margin assurance a key ask for CSPs today? Here are five reasons:

    1. Unidentified contributory costs in a multi-partner ecosystem 

    With the rise in debt collection, depreciation, and other activity costs, it is becoming increasingly difficult to optimize gross regulated margins. The proportion of different direct and indirect expenses increases as the number of partner systems increase. Improper cost allocation models, in addition to the bundling of network and business costs, increase the complexity of costing.

    2. Deficient view of capacity, utilization, and profitability across network elements 

    While operators dedicate significant spend on planning and capacity optimization, they also need to keep an eye on profitability. Profits, too, must grow along the network value chain. This is done by analyzing multi-channel provisioning behaviour to determine the best way to improve margins and optimize utilization.

    3. Absence of granular level visibility into costs and revenue parameters 

    Technology advances are encouraging product innovation for next-gen communication needs. CSPs must identify different product costs and map them to revenue to fully understand the total cost for each product, customer, and business segment. With limited insights into the cost and revenue segments, CSPs struggle with cost allocation parameters. Telecom employees need the right skillsets in cost accounting and telecom knowledge to map the cost of individual products or bundled segments of voice and data traffic. Discrepancies in profit increase with the inability to determine the accurate price of a particular product or technology.

    4. Lack of real-time insights into new-age product profitability, pricing, and performance 

    With data on the rise, CSPs must bridge the gap in data reconciliation across various sources such as networks, partners, and products. Dearth of insights into the real-time performance of products can negatively impact the organization’s profit and loss. Strong data management increases efficiency in identifying and tracking the profitability of services, devices, and other entities, cementing the need for margin assurance.

    5. Bundled Products & technologies results in complex cost allocation models 

    Operators are trying to merge/bundle multiple services and technologies, resulting in the creation of complex cost allocation models. This leads further product complexity and revenue differentiation due to the bundling of multiple products and technologies. It is important to give a strong consideration to the product line and build cost allocation models in line with industry-leading practices support to arrive at near real cost allocations for profitability computation.

    Margin assurance enlists the metrics to handle the bottom-line complex mix of service offerings defining the holistic view for cost allocation, real-time assurance, margin automation, etc. This helps to achieve the benefits in terms of ‘profit computation,’ ‘flexible cost allocation,’ and ‘effortless cost modelling,’ which further lead the operator to widen its scope of work with a massive increase in the number of cost line items

    Margin Assurance To Ensure Profitability For New-age Telcos

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  • 2021: The Year of accelerated network transformation

    2021: The Year of accelerated network transformation

    “The secret of change is to focus all of your energy, not on fighting the old, but on building the new.”
    – Socrates

    2020, a year that redefined many aspects of our lives and challenged every individual, industry, and nation to rethink, re-strategize, re-innovate, and revive the brutal impact of one of the most gruesome pandemics in the history of humanity. On the one side, the pandemic led to loss in various forms. On the other, it led us to shift focus towards building something new, which would better equip us in challenging times.

    As we look forward to 2021, it is essential to note that while COVID-19 accelerated digital transformation initiatives, the pandemic also reiterated that true digital transformation in the mobile communication industry could only happen through a holistic network transformation strategy execution.

    As we move forward, networks across the globe will witness an acceleration in the transition from LTE to LTE-advanced/pro to 5G-NSA (Non-Standalone) to 5G-SA (Standalone) deployments. The stage may vary from one CSP to another, but one thing is evident: the adoption of 5G is gaining momentum and shaping the telecom sector outlook like never.

    In many ways, 2021 will see some significant 5G milestones that will redefine a CSP’s quest to disrupt the digital economy. It does not matter where you are or will be in your network transformation journey; the below critical trends will drive innovations to help CSPs realize the true digital value derived from the network. It will redefine a CSP’s journey for the decades, not merely years, to come.

    Key trends towards the network transformation from LTE to 5G SA

    1. Cloud adoption: A focused cloud-led investment in business and technology domains where cloud platforms can enable increased revenues and improved margins will be a mandatory step towards the 5G journey. A telco can either adopt a public cloud or a private cloud or hybrid cloud to transit from their existing on-premise infrastructure. Companies that adopt the cloud well will bring new capabilities to the market more quickly, innovate more easily, reduce risks effectively, and scale more efficiently.

    One cannot realize the true potential of 5G without moving to the cloud. Some of the significance and relevance of the cloud in the 5G are:

    • 5G edge computing: 5G technology opens a new business segment for CSPs, i.e., enterprises. 5G edge computing will be quintessential to realize these opportunities as it will provide distributed cloud infrastructure resources closer to a location where it is required and will help CSPs tap into new business opportunities by supporting a variety of use cases in a distributed cloud environment.
    • 5G core: As per the new 3GPP standards for 5G core, most of the functions will be cloud-native and container-based. Cloud-native, a modern approach to building and running applications that fully exploit the advantages of the cloud computing model, will require a robust cloud infrastructure for successful 5G standalone deployment. The cloud-native approach of application development to support 5G functions will be established in containers, microservices, and dynamic orchestration and will leverage the scalability and high-availability characteristics of the cloud.
    • 5G experience: To offer a superior 5G experience to consumers and enterprises, CSPs need to consider the exponential growth in network, devices, and data volume, which will result in enormous complexities that can be significantly simplified and managed through cloud adoption. This will help CSPs roll out new services quickly, innovate, and scale faster to meet the customer demands in the shortest time.

    A recommended cloud adoption journey is shown below:

     

    “In order to be cloud-native, you need to first immerse yourself completely into the cloud”

    2. Open RAN Evolution: “Open RAN,” which is seen as a revolution in the mobile communication industry, disaggregates hardware and software and creates open interfaces between them, creating new avenues for innovation, eventually resulting in Capex as well as Opex efficiencies. Before I get into “why” open RAN is a crucial trend for network transformation, let’s look into below key predictions by some of the established firms:

    GSMA:

    • Globally, it is forecasted that CSPs will spend 80% of the sector’s Capex ($890 billion) on 5G networks over the next five years
    • 57% of CSPs intend to introduce new vendors into their network supplier roster

    Omdia:

    • 2021 will see 5G RAN investments will exceed those in LTE RAN, and it predicts that 5G will account for more than half of all RAN investments during the year

    Deloitte:

    • There are currently 35 active open RAN deployments across the globe
    • Many of these involve MNOs testing open RAN in greenfield, rural, and emerging markets.
    • Open RAN deployments could easily double in 2021.

    RAN (Radio Access Network) has always been an investment-intensive domain, consuming more than 70% of overall network investments. To ensure profitability, it is now time for CSPs to look for an alternative and innovative option. CSPs see open as a way to accelerate service introductions and potentially drive new service combinations. Open RAN could, in turn, unlock new business opportunities by enabling new ways of building networks.

    As per Heavy Reading’s 2020 Open RAN operator survey, 20% of operators with revenues greater than $5 billion will have 1000+ Open RAN macro-outdoor sites by the end of 2023.

    As we look ahead, Open RAN is not merely a concept anymore; it is now a reality. From 2021 onwards, most of the Open RAN commercial deployments will be centered around RUs (Radio Units) and DUs (Distributed Units). From 2022 onwards, RIC (RAN Intelligent Controller) commercial deployments will be expected to start.

    “Let’s revolutionize the most complex and cost intensive part of the network: the RAN.”

    3. AI/ML-driven Closed-Loop Automation: As CSPs plan to transit from 5G NSA to 5G SA, end-to-end (e2e) network slice management will become mandatory. Network slice complexity will be extremely high as it consists of RAN, transport, and core network slice subnets. Each of these subnets possibly consists of further subnets. For example, the RAN subnet can be decomposed further into fronthaul, midhaul, and RAN network functions. Managing such a complex network slice environment manually will not be a feasible option; it will require a hyper-level of automation.

     Network automation has evolved significantly over the last few decades. A simplified view of this evolution is shown below:

    “It is time to bring intelligence in automation across every part of the network.”

    Closed-loop automation powered by machine and deep learning models is an emerging and promising stage of automation. It will redefine the overall network management and orchestration ecosystem.

    The Open Network Automation Platform (ONAP) project, an open-source project, provides a platform for designing, implementing, and managing different network services. The latest ONAP release (Guilin release) has taken a significant step by implementing the fundamental aspects of the 3GPP-specified NSSMF (Network Slice Subnet Management Function) for the RAN, transport, and core subnets, and also connecting to an external RAN NSSMF for the RAN subnet. Enhancements were also made to NSMF (Network Slice Management Function) functionality in stitching together an end-to-end slice.

    A couple of basic closed-loop scenarios (one with Machine Learning done offline) involving the RAN subnet and initial steps to monitor KPIs by the operator/slice tenant have been implemented.

    We will see significant enhancements in upcoming releases, and ONAP, being an open-source project, will be an open ground for innovation, not just for incumbents but for start-ups as well.

    The COVID-19 pandemic has changed both the trajectory and the pace of digital transformation and will likely continue to do so into 2021. The key trends associated with network transformation are an open invitation to innovate and disrupt. It will see many organizations trying to solve some of the critical business challenges and helping CSPs realize the true potential of 5G. It offers a unique opportunity to bring a fresh change in the telecom industry by building something new, something never tried before, something radical and revolutionary.

    To understand the key pillars, and unlock the full potential of your network

    Read The Whitepaper

  • Adiós 2020 … 2021, ¡no puedes venir lo suficientemente pronto!

    Adiós 2020 … 2021, ¡no puedes venir lo suficientemente pronto!

    A medida que nos acercamos al final de un 2020 unánimemente desastroso, en Subex recordamos todo lo que habíamos presenciado durante el año pasado, con un renovado sentimiento de optimismo por lo que está por venir. En conclusión, ¡vaya, qué año tuvimos!

    Más allá de los asuntos personales donde muchos de nosotros nos tomamos el tiempo para renovar nuestras casas, comprar una bicicleta indoor para hacer ejercicio (que para muchos terminó siendo un perchero multifuncional) o aprender un nuevo instrumento, en el mundo de las Telcos sucedieron muchas cosas. Es emocionante analizar cuántos negocios nuevos y viejos se han consolidado y muchos proyectos pospuestos, pero este año ciertamente no pasó desapercibido ni será olvidado.

    Si tuviéramos que resumir las principales observaciones de este año en particular en el que vivimos, serían las siguientes:

    • Fue el año de la consolidación y expansión de la digitalización debido a la pandemia
    • Se sentaron las bases fundamentales para el despegue de tecnologías como 5G.
    • El ciberdelito y el fraude fueron testigos de un aumento en el número y la complejidad
    • En mitigación de riesgos, finalmente se inició la adopción del Business Assurance
    • El inevitable aumento de la relevancia de la confianza digital

    La Expansión Digital – Haga una virtud (de) la necesidad – Piense en el crecimiento de la tecnología dentro de los hogares. Uno de los operadores más grandes de EE. UU. Informó que los juegos en línea crecieron más del 257% y el uso de herramientas de colaboración más del 1200%. Hoy, todo el mundo le cantaría feliz cumpleaños a una tía o abuela a través de Zoom o WhatsApp. Esta tendencia está aquí para quedarse, y en 2021 seguramente veremos un crecimiento más significativo. Muchas oficinas dejarán de existir porque el teletrabajo es ahora una realidad. Empresas (y personas) se han dado cuenta de que se puede trabajar de forma remota, y este hecho afectará a varios sectores, como el inmobiliario y sin duda, el de telecomunicaciones. Quizás esta “nueva normalidad” creará un empujón final, el impulso que le da a la 5G el ímpetu para la consolidación.

    5G – Más allá de las promesas En nuestra región (CALA), el 5G, con más histeria que historia, avanza lentamente, pero al menos avanza. Ya se han registrado pruebas exitosas y algunas implementaciones pequeñas en Chile, Uruguay, Surinam, Trinidad y Tobago. Quizás la pandemia haya provocado retrasos en el despliegue en los países más poblados como México o Brasil.

    Aún así, todos albergan presupuestos, realizan pruebas iniciales u ofertan por espectro para implementar esta tecnología. También hay datos alentadores como el caso de Entel Chile y Ericsson, que realizaron una prueba 5G y alcanzaron una velocidad de transferencia de datos de 24,7 Gbps, un récord absoluto en Latinoamérica.

    Amenazas crecientes de la ‘digitalización forzada’: La pandemia esencialmente ha llevado al modo de operaciones fuera de línea a pasar a Internet. Con las empresas adoptando rápidamente los canales de venta en línea y los usuarios haciendo un uso intensivo de ellos, los ciberdelincuentes se han abierto a oportunidades para aprovechar la situación y nuevos consumidores digitales que tienen menos experiencia en la prevención de ataques. Según el informe IOCTA (Evaluación de la amenaza del crimen organizado en Internet) de Europol 2020, el grado de sofisticación de los ciberataques ha mejorado significativamente a raíz de la pandemia de COVID-19. Estos cambios han acelerado la confluencia que se ha visto en los últimos años entre la ciberseguridad y la gestión del fraude. 2020 fue testigo del aumento de amenazas de diversas técnicas que van desde Malware hasta Ransomware, IRSF, malware, DDoS, Spamming y Compromiso de correo electrónico empresarial. El fraude de pagos, especialmente el intercambio de SIM, se ha considerado una tendencia este año desde el punto de vista del fraude. Este aumento del fraude y el ciberdelito ha exigido una estrategia integral de gestión del fraude que debe incluir detección, validación de identidad y autenticación como un conjunto de capacidades integradas.

    Business Assurance – ganando adopción – Desde el punto de vista de Revenue Assurance, continuamos en transición hacia la consolidación de la práctica hacia Business Assurance. Business Assurance proporcionará una visión más holística de los indicadores comerciales que más afectan nuestras actividades. Quizás COVID-19, debido a elementos de mayor prioridad, ralentizó la transición y pospuso la implementación de muchos controles nuevos, modernizando la infraestructura de mitigación de riesgos o simplemente aliviando la curva de aprendizaje de los equipos de RA. Probablemente, la digitalización expansiva en el hogar, la alta demanda de recursos de red que requieren los usuarios empresariales o particulares hizo imperativo que las Telcos se centraran en esta nueva realidad, dejando de lado algunos proyectos que sin duda se tendrán en cuenta el próximo año.

    Esta avalancha de digitalización, donde ya están surgiendo servicios como video OTT, proyectos de IoT y 5G, creará muchas oportunidades de negocio para las empresas de telecomunicaciones, pero también traerá muchos riesgos asociados que tendrán que ser mitigados. Estaremos ahí para ayudarte.

    El auge de la confianza digital: con la colaboración de todas las formas en el ámbito digital, un aspecto clave ha surgido como la pieza central de cada interacción a nivel personal, social y empresarial: la confianza. En tal escenario, la confianza digital se considera el elemento vital o la moneda del negocio digital. La confianza digital es la capacidad de una organización para inspirar confianza dentro de su ecosistema digital sobre su intención y capacidad para brindar los servicios prometidos. La confianza digital se ha convertido en el habilitador fundamental para las interacciones digitales de alta calidad en el nuevo mundo digital valiente al medir y cuantificar las expectativas de una entidad, validando explícitamente quién o qué dice ser, y si se comportará como se espera dentro de una transacción comercial digital. En la actualidad, Digital Trust está ocupando su lugar como pieza central del éxito, desde la mejora de la imagen de marca y la adopción de nuevas tecnologías hasta la incorporación de inversiones, el despliegue de nuevas ofertas y la expansión del ecosistema de socios. Creemos que este concepto adquirirá mayor relevancia en los próximos años.

    Feliz 2021: ¡será un año emocionante! – Después de la tormenta, sale el sol; aquí en Subex, también tuvimos un año desafiante como todos los demás, pero lo aprovechamos muy bien. Hemos estado muy cerca de nuestros clientes, creando los mejores planes posibles para mejorar sus prácticas y brindándoles el apoyo que merecía esta situación excepcional. Y una cosa superlativa fue que desafiamos nuestra cartera de productos para modernizar nuestra plataforma de mitigación de riesgos con un enfoque esencial en la confianza digital. Este equipo, a través de la innovación y el esfuerzo -el talento por sí solo no es suficiente- está creando la plataforma tecnológica del futuro que actuará como catalizador entre las demandas del mercado y las necesidades de nuestros clientes. El año que viene, esperamos unirnos a usted y contarle (con suerte, cara a cara) más sobre el progreso de este proyecto, que está destinado a interrumpir nuestra industria tal como la conocemos.

    ¡Te deseamos un muy buen 2021 y esperamos que esta experiencia que vivimos nos ayude a tener otra perspectiva de las cosas y de la vida!

    Habilitar la confianza para ofrecer experiencias digitales inspiradoras

    Descargar punto de vista

    Adrian Plohn
    Adrián es uno de nuestros especialistas de Gestión Fraude y Business Assurance en Latinoamérica. Él es responsable de asesorar a nuestros clientes en la implementación de las mejores soluciones tecnológicas para la gestión de riesgos y maximización de beneficios. Adrián posee más de 26 años en el área de Tecnología de la Información y Gestión de Riesgos en el mercado de Telecomunicaciones.

  • Enfrentando el fraude de bypass: piense más allá de los límites

    Enfrentando el fraude de bypass: piense más allá de los límites

    En medio de la feroz competencia que enfrenta la industria de las telecomunicaciones, a veces escuchamos historias sobre cómo la falta de previsión de una Telco genera tráfico ilegal en la red. Esto tiene serias implicaciones, como pérdida de ingresos y acusaciones injustificadas entre los operadores afectados por el fraude.

    El fraude de Interconnect Bypass es una estafa de telecomunicaciones que le cuesta a la industria varios miles de millones de dólares cada año. Trae daños colaterales a las redes involucradas, junto con un impacto masivo en su rentabilidad. A las empresas de telecomunicaciones se les podría imponer una fuerte sanción por no detectar y resolver el problema a tiempo. Además, podría traer serias implicaciones comerciales para todas las empresas de telecomunicaciones participantes. En el proceso de bloqueo desenfrenado del tráfico sospechoso, a veces el tráfico de clientes genuinos podría bloquearse, lo que provocaría disonancia e insatisfacción del cliente junto con la pérdida de otras oportunidades comerciales.

    A continuación, se muestra un ejemplo de una empresa de telecomunicaciones que sufrió enormemente debido al fraude de Bypass.

    ¿Por qué pasó esto?

    La empresa de telecomunicaciones se había visto enormemente afectada por el fraude de Bypass fuera de la red, en el que se utilizaba indebidamente la red del operador para realizar llamadas fraudulentas en el sistema de la competencia. Con el tiempo, el problema se volvió tan grave que la Autoridad Reguladora del país tuvo que intervenir y hacerse cargo de las cosas. Esto finalmente terminó con los competidores bloqueando tanto el tráfico fraudulento como el genuino de la Telco afectada por el fraude de interconexión.

    Las investigaciones realizadas confirmaron que las enormes diferencias entre las tarifas de terminación internacionales y locales hicieron que el entorno fuera adecuado para que los estafadores ejecuten sus esquemas. Además, también se identificó que no había suficientes controles KYC en el país para facilitar ciertos controles de incorporación que distinguen a un cliente genuino de uno fraudulento.

    Las Repercusiones

    Hubo múltiples advertencias y memorandos emitidos al operador por parte del Regulador, lo que indica que el operador tendría que enfrentar sanciones si las enmiendas no se realizan a tiempo.

    Los clientes inundaron al operador con quejas diciendo que sus llamadas fuera de la red estaban prohibidas sin previo aviso y por causas ajenas a ellos. También amenazaron con salir de la red si no se restauraban sus servicios.

    La atmósfera se volvió tan tensa que en lugar de cooperar, los operadores se volvieron más agresivos y se entregaron a una carrera de ratas al tratar de demostrarle al Regulador cuán mejores y eficientes eran de los rivales en términos de detección de casos de fraude de Bypass.

    La solución

    Con el entendimiento de que los fraudes de Bypass son rampantes, las empresas de telecomunicaciones deben dirigir sus esfuerzos hacia la incorporación de tecnologías avanzadas como IA / ML en sus sistemas de gestión de fraudes. Esto ayudaría a las empresas de telecomunicaciones con la detección temprana de fraudes, tan rápido como dentro de los 10 minutos de uso. Además, esto permitiría a las empresas de telecomunicaciones identificar los diversos patrones complejos ocultos que, de otro modo, podrían pasar desapercibidos utilizando métodos tradicionales basados ​​en reglas. Estas tecnologías también pueden ayudar a monitorear el comportamiento cambiante sin intervención manual.

    Además, las empresas de telecomunicaciones deben generar conocimiento en términos de comportamiento fraudulento y las ubicaciones desde donde se generan. Las empresas de telecomunicaciones deben comprender qué tipo de productos tienden a ser mal utilizados por estos estafadores. Esto ayudaría a las empresas de telecomunicaciones a cortar las cosas de raíz, ahorrando así millones y manteniendo intacta su imagen de marca.

    Seminario web On-Demand: Abordar el fraude de bypass a través de la inteligencia artificial

    Ver ahora

  • How cybersecurity challenges and trends will mark 2021?

    How cybersecurity challenges and trends will mark 2021?

    As 2021 emerges on the horizon, here are the top trends that our threat researchers feel will define the New Year.

    Ransomware propagation: the first quarter of 2021 will provide some respite to cybersecurity teams battling ransomware. Already we are seeing signs of a slowdown as malware developers are investing more time in developing new ransomware. This respite is however temporary as new and stronger ransomware and variants will start emerging from April.

    Attack fatigue: nation state actors have shown signs of fatigue setting in. After ruthlessly targeting vulnerable sectors such as healthcare and manufacturing during the pandemic, many hackers have retreated to the comfort of their basements. This trend is expected to continue till the end of Jan 2021.

    Manufacturing, retail and healthcare on the radar: attacks on these sectors will intensify.

    Media and entertainment (M&E) industry will be most impacted sector in 2021. This is based on the trends we are currently seeing especially the activity in the malware forums we are tracking.

    Deep fake videos will be weaponized with greater intensity as part of multi-stage phishing campaigns

    Botnet farms to increase: as 5G rollout gathers pace, more IoT devices will be added some of which will not have the bare minimal levels of security in place.

    Industrial control systems to bear the brunt of sophisticated attacks. Industrial espionage at a large scale will hit energy, power, oil, gas and manufacturing companies

    Data stored on public cloud will be the target of cloud jacking in a more organized manner

    Subex is here to help

    We will be glad to help you address your security challenges in the New Year. At Subex, we have a robust and evolved IoT and OT security solution backed by consulting and SoC services tailored to your unique cybersecurity needs.

    Subex is today securing the business of its customers around the world. Our suite of solutions bring features such as cyber deception, device discovery, threat detection and deflection and prevention of lateral movement of threats. These are essential to keep your business safe and protected.

    The article is originally published at Subex Secure

    Learn the important considerations for improving IoT security outcomes and digital trust

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  • Augmented Analytics: The future of data analytics

    Augmented Analytics: The future of data analytics

    One of the latest data and analytics trends which has gained considerable traction these days is Augmented Analytics. The term was coined by Gartner in 2017, goes well beyond the world of data and analytics, bringing in the wave of disruption in the market. By leveraging AI/ML techniques, it transforms how analytics content is developed, consumed, and shared.

    There are compelling reasons why organizations must adopt augmented analytics technology. Many organizations have realized the importance of Big Data and its role in decision making across the business. However, this sheer volume of data available to organizations is making effective interpretation a real challenge. According to Forrester Research, less than 0.5% of all data is ever analyzed and used. While a mere 12% of enterprise data is used to make decisions. This will only make it worse with the growth in IoT connected devices which is expected to generate 79.4 Zeta Bytes (ZB) of data across 41.6 billion devices, according to IDC Forecast.

    To date, many processes remain largely manual and prone to bias across the data value chain. This includes managing and preparing the data for analysis, building ML/AI models, interpreting the results, and making insights actionable.

    Using the current analytics approach, business users find their own patterns, and data scientists build and manage their own models. This results in exploring their own hypotheses, missing key findings, and interpreting incorrect conclusions. This will adversely affect decisions, actions, and outcomes. According to Forrester Research, only 29% of organizations are successful at connecting analytics to action.

    Augmented Analytics promises to ease this bottleneck. It democratizes AI across the data value chain. It automates the data preparation process, key aspects of data science, and ML/AI modeling using ML (AutoML) techniques and narrate relevant insights using NLP and conversational analytics. It includes:

    • Augmented data preparation uses AI/ML automation to accelerate manual data preparation tasks like data profiling and quality, enrichment, metadata development, and data cataloging, and various aspects of data management like data integration and database administration.
    • Augmented data science and machine learning uses AI/ML techniques to automate key aspects of data science such as feature engineering and model selection (AutoML), as well as model operationalization, model explanation, and model tuning.
    • Augmented analytics as a part of BI platforms embed AI/ML techniques to automatically find, visualize the data and narrate the relevant findings via conversational interfaces, including natural language query (NLQ) technologies, supported by natural language generation (NLG).

    This leads to an increase in productivity, efficiency, and smart decision-making across the organization. One of the greatest benefits of augmented analytics is that it democratizes data analytics for less business-savvy users i.e., Citizen Data Scientists without any specialized training or skills in data science or analysis. Augmented Analytics also enables the adoption of actionable insights for the executive team across the organization.

    So, every organization will need an augmented analytics platform to connect disparate and live data sources, find relationships within the data, create visualizations, and help human users effortlessly share their findings across the entire organization. It will change how users experience analytics and BI and the world by serving up insights that humans could ever imagine.

    Did your organization adopt Augmented Analytics? If yes, how it has benefited the organization? Feel free to share your thoughts and some interesting statistics about augmented analytics in the comments section.

    Learn how augmented analytics can help transform your approach to enterprise AI

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  • Automated Revenue Assurance: Helping CSPs Do More

    Automated Revenue Assurance: Helping CSPs Do More

    Revenue assurance (RA) is a common business activity for telecommunication service providers. It utilizes data quality and process improvement methods to increase profits, revenues and cash flows without influencing demand.

    In 2008, when I began my career journey in the telecom industry, I observed that telecom service providers mostly focused on the aspect of revenue enhancement with the aim of gaining strong revenue market share (RMS) and customer market share (CMS). This was done to augment their coverage in almost all the circles across India. ‘Circles’ refer to service areas, largely divided according to states/population index by the Telecom Regulatory Authority India (TRAI). The point to note is that there was not much of a focus on cost reduction as an objective.

    At this time, most organizations did not possess any specific tool for revenue assurance either. Even if they did, it was rarely geared to the enterprise needs, leading to sub-optimal performance. For some, revenue assurance fell under the sole purview of finance departments.

    Without a focused RA tool, risk assurance teams (or people like me in my earlier days) used to sit for half a day to manually execute revenue assurance activities in MS Excel or Access!

    In some cases, performing control activities, reconciliations and analysis of exception needed a few more hours, meaning the day was almost over by the time the reports were prepared and the final consolidated dashboard was circulated to other teams like network, marketing, service provisioning, etc., for taking the necessary corrective actions. One dismaying effect on such delays was that case closure would get pushed to another day. A study by TM Forum underscores this inefficiency: it showed that 1% of the gross revenues are lost due to open cases pushed to the next day. Significantly, this excludes losses due to fraud.

    Thus, lengthy turnaround time for case management impacts the entire organization.

    Compared to the relatively nascent field of revenue assurance among small and large telcos in India, the area of fraud management was well understood. This here was a mature field that was seeing significant growth with many telcos outsourcing fraud management tasks to external vendors like Subex.

    Fast forward to more than a decade later, CSPs are now always in a hurry to release modern features and keep pace with what’s new in the market. But while they do this, they must also ensure profitability. Having worked with some of the leading telecom operators across India, I believe the industry needs revenue assurance systems or tools that save manual effort by performing automatic reconciliations across a gamut of technologies, services and products. Armed with these tools, revenue assurance experts can focus solely on analytics and close cases with timely corrective actions.

    AI/ML-based Revenue Assurance solution helps telecom operators get revenue assurance automated and data driven capabilities at low latency. Apart from automated reconciliations, the solution also delivers output across all revenue streams such as prepaid, postpaid, interconnect, data, VAS, roaming, etc., giving risk assurance managers a holistic and accurate picture of revenues.

    Most important capabilities of an AI/ML-based Revenue Assurance solution include:

    • Data gathering from all sources
    • Reconciliation/auditing
    • KPI dashboard
    • Leakage analysis
    • Operational workflow management
    • Problem correction
    • Business reporting

    This solution generates tremendous value for customers by bridging the gaps and addressing the challenges of traditional revenue assurance processes.

    Automated reconciliation truly gives telcos a sharper edge for cost reduction as well as revenue enhancement.

    GCC operator leverages Subex ROC Revenue Assurance to improve margins and profitability

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  • Evolution of BI Platforms

    Evolution of BI Platforms

    We live in an era of Big Data. Around 1.7MB of data is created every second by every person. 2.5 quintillion bytes of data are produced by humans every-day. This sheer volume of data has become so huge, complex, and fast-moving, that to make sense of this vast amount of data is a challenge. So, Business Intelligence (BI) tools are used to analyze this humongous amount of data to uncover the insights that are crucial for the business. It makes data of any kind, easy to digest with stunning visualizations, detailed historical analysis, and customizable reports.

    Over the decades, BI technology has evolved, and the market shows no signs of slowing down. While the inherent meaning has remained the same, but BI as a set of processes, technologies, and tools has changed a great deal, right from Traditional BI to AI-powered BI which uses Augmented Analytics. Before understanding how augmented analytics will change the analysis and business intelligence process, let us have a look at the evolution of business intelligence.

    Traditional BI

    The first generation of BI technology often referred to as “Traditional BI” was a centralized guardian tool for all enterprise data largely owned and driven by the IT and data specialists. Legacy deployments of multiple components such as data marts, data warehouses were technically complex and required extensive IT staff to maintain and manage it. The Extract Transform and Load (ETL) paradigm integrated data from disparate sources into a central repository for storage. Once stored, data was normalized and structured before it is further utilized to run queries and retrieve data for reporting.

    Ultimately, the IT department generates and delivers static reports to the business owners. The analysis was usually descriptive and performed by specialized data analysts with restricted access to the reports. This entire process could take days, weeks, or even months to produce insights due to dependency on skilled IT staff. And thus, unable to make timely data-informed decisions. To make BI more accessible to business users, self-service BI became the next generation of analytics and BI.

    Self-Service BI

    The main drawbacks of traditional BI were the need for highly skilled technical analysts, lengthy time-to-insights, and poor quality of the data being analyzed. These drawbacks were overcome by a more agile approach that favored self-service capabilities: Modern Self-Service BI. This eliminated the technical stack designed for IT users and focused on providing data discovery and visualization tools to business users. It also provides business users the ability to conduct ad hoc analysis of data from disparate sources without any advanced technical skills. As compared to traditional BI, they can handle larger volumes of data drawn from multiple sources allowing for deeper analyses. They replaced the rows and columns of traditional data presentations with graphical pictures and charts.

    In addition to historical reporting, it provides predictive and prescriptive reporting and insights in real-time. With these tools’ users get the information to make better decisions, with greater ease, and without having to rely a lot on data analysts and IT professionals. Modern BI solutions also make data governance, security, and access control simpler for IT teams.

    Need for an AI-powered BI tool

    Despite being more insightful and easier-to-use than traditional BI, self-service BI tools do have few limitations. As the volume of data rises, there is a requirement of data scientists to make sense of huge datasets. But scarcity of data scientists and manual data preparation makes the process highly inefficient and prone to error. Also, the insights provided by self-service BI systems are limited to the type of queries made by business users. This is where the need for a new AI-powered BI i.e. Augmented Analytics BI system arises. It not only automates the data preparation tasks but also parts of data insights and the data discovery process.

    Augmented Analytics BI

    Augmented Analytics integrates AI into the analytics and BI process to help the user to prepare their data, identify relationships within the data, discover new insights, and easily share them with everyone in the organization. It reduces the dependency on highly skilled data scientists by automating insight generation using machine learning and artificial intelligence algorithms. Gartner states that more than 40% of the data scientists’ roles to be automated by 2020. Augmented Analytics BI tool can help less technical experts like Citizen Data Scientists to provide recommendations and suggestions based on their domain and primary skills to understand and gain insights from the trends and patterns. It will be free of human biases and reveal hidden insights crucial for the business. Also, the use of Natural Language Generation (NLG) can enhance the BI reporting process by allowing users to query the system and present the insights narratively.

    Augmented Analytics will help move organizations beyond the dashboard paradigm to a new way of consuming insights i.e. data story. These will help the user understand just the insight and context that they need at the right moment to make the decision. By 2025, 75% of the data stories will be automatically generated using augmented analytics techniques.

    Every organization will need an augmented analytics platform to create visualizations, aid in storytelling and then help users to effortlessly share their findings across the entire organization. This will boost the adoption of Augmented Analytics BI across teams, especially among non-technical users. Augmented Analytics will change how users experience analytics and BI.

    Does your organization still use Traditional BI and Self-Service BI? Do you plan to adopt Augmented Analytics BI in future? If yes, then how it will benefit an organization. Feel free to share your thoughts in the comments section.

    Learn how augmented analytics can help transform your approach to enterprise AI

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  • Why ML-based fraud detection is the way forward for Telco Fraud Management?

    Why ML-based fraud detection is the way forward for Telco Fraud Management?

    The telecoms industry has always suffered from the malicious impacts of fraudsters. In this digital era, traditional telecom services are replaced with new services, giving rise to new fraud types. Therefore, technology to support fraud management operations has changed significantly, with an increased reliance on Artificial Intelligence and Machine Learning as a means for uncovering and identifying fraud. In one of its recent reports, Gartner estimated that by 2022, new implementations of ML within CSP fraud management would reduce fraud losses by 10%.

    Will AI/ML be the future for Fraud detection & prevention?

    To help us understand this further, it gives us immense pleasure to have interviewed Joseph Nderitu

    How has the telco fraud landscape changed in recent years?

    There has been significant evolution into new technologies, different access methods, and the proliferation of IP technologies. This means the fraudster may be seated inside the telco premises or half-way around the world and has the flexibility to “hit” the telco in any number of ways. For operators who are offering mobile money, they have suddenly found themselves running a bank on top of their IP network, something that was not in their corporate DNA, so to speak. To cap it all, as we move into the 5G and IoT landscape, the volume of data will be very high whilst the response time to fraud and leakages will be expected to be faster.

    Why do telcos need to continuously innovate and invest in newer technologies to address the risks?

    The pressure to address risks is higher than ever. Customer expectations are high, and with rising competition, failure to address risk means a reduction in market share. Shareholder value thus gets eroded if risks are not well managed. Regulators are also keeping a keen eye on service providers. This essentially means the challenges are increasing on the one hand, and the service providers’ responsiveness is expected to increase amidst reduced budgets for tools. Innovation is the only way out. We need better tools and methods, which help us to manage risks better.

    Do you think AI/ML is the way forward for telco fraud management? And why?

    Certainly – if you look at telcos, they are a goldmine of data, always have been. The trends and patterns are there, but we have not been doing a great job of detecting them because the human capacity to see trends is limited. AI/ML technologies remove that limitation – or, at the very least, reduce is significantly. Thus, we are at a sweet spot of sorts – a confluence of rich data, superior ways of looking at the data, and telco businesses that are hungry for insights that will help them manage risks better. As we place everything on IP technologies, it also means we are at a point where the greying of lines between revenue assurance, fraud management, and cybersecurity is happening much faster. The interplay between these areas is a good area for AI/ML.

    What are some of the critical fraud areas, which can be covered to a larger extent with AI/ML?

    There is a pattern to each fraud. The fact that we do not always do a good job of spotting it with our traditional systems (which are very much rule-based) does not mean the pattern is not there. With that in mind, it means one can apply supervised and unsupervised learning in a lot of areas. There are operators, in Africa, for example, deploying basic learning models on mobile money frauds and using them to identify commission frauds perpetrated in the distribution chain. The features used in such a model would combine the pattern of records obtained from both the GSM systems and the mobile money systems – something that was quite unwieldy to do using conventional FMS. Thus, there is no problem that is too small or too big to be addressed in this new mode of fraud management. 

    Likewise, with IoT, smarter devices do not mean less fraud, for example – it might just mean an expanded landscape where we (operators and customers) can be hit from any angle.

    Does the introduction of AI/ML mean reducing team size, more focus on other areas, and complementing the team with other teams?

    There will always be a need for warm bodies. Proper use of AI/ML means we can free human beings to do things that machines still cannot do, or at least cannot do so well. For example, resolving issues still calls for people to talk to each other, negotiate, agree, implement, and track progress. There will always be room for that, so in a sense, and we just need to let the machines do what machines do best and leave humans to do what only humans can do(for now).

    While there is a need, are telcos really investing in these technologies?

    As always, some will move faster than others. However, regardless of the speed of implementation (which is a function of budgets, organizational politics, and other organizational peculiarities), by and large, this is the direction the telcos are taking. Some are approaching vendors to update tools; others are doing their in-house experiments using freely available resources such as python. All in all, I doubt there is anybody who is sitting with their arms crossed, hoping that the advent of AI/ML is a fad that will pass. The technology is and will keep on evolving, whether we keep up or not.

    On-demand Webinar: AI Master Class for Fraud Management

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  • Six ways to mitigate Enterprise Business Risks in Telecom

    Six ways to mitigate Enterprise Business Risks in Telecom

    The telecommunication industry is not just about providing voice, data, and SMS services to individual consumers but also includes an enterprise segment. One could say that the enterprise business line is more like a wholesale business or B2B of telecom involving interconnect billing and roaming agreements.

    But again, wholesale is only a subset.

    Take the example of BT that, in 2018, delivered a global SD-WAN solution for a water treatment and chemicals manufacturer that improved network visibility, connectivity, and security as part of the manufacturer’s digital transformation program. Indeed, these services were offered through BT’s enterprise business model. Clearly, the breadth of the telecom B2B segment extends into numerous areas like network services, software-defined network platforms(like Ethernet and SD-WAN), content delivery networks, the internet, multi-protocol label switching (MPLS), connected data centers, ATM connectivity, access service, and private lines, to name a few.

    Then, the idea of risk is very different here as revenue is not based solely on transactions. In the enterprise business revenue model, managed contracts are signed between service providers and enterprise customers and often include bulk usage-based or connection-based plans.

    Having worked with telecom clients across the globe on numerous risk detection solutions, we have put together a list outlining how operators can secure themselves from risk within the enterprise business segment.

    1. Automate contract management 

    For each enterprise partner and customer, telcos have voluminous master and delivery contracts that often reside in physical formats, i.e., in hard copies, making validation and mapping to NSS/OSS/BSS a lengthy, error-prone, and manual process. While digitization of contracts has brought in some efficiency, operators should consider investing in automated contract management solutions that dilute risk through smart features that validate invoices, pre-empt disputes, track contract performance, and more.

    2. Focus on customer experience

    Customer experience teams for B2B telecom must be highly skilled and adept at coordinating with internal teams to ensure timely accounting, seamless network availability, and enhanced online customer journeys. This CX personnel require best-in-class tools that alert them on severities, updates on resolution time, and proactively inform clients about service disruption or degradation. Ensuring a good customer experience is vital since attrition translates to a penalty of millions of dollars.

    3. Streamline invoicing and accounting workflows 

    Invoicing is a complex affair for telcos due to the multi-partner nature of business. Invoices that are received from partners must, in turn, be raised to customers. Some may even need last-mile delivery in countries depending on the nature of the partnership. Each invoice must be validated and matched with the respective contract, and then the cost updated in the general ledger. From invoice validation to accounting, this entire process continues to be a significant pain point for telcos and a source of vulnerability.

    4. Consistent quality of service

    Quality of service is imperative to the customer experience. Distinct from service availability, quality of service must always be above the committed levels. It calls for regular network monitoring, big data analytics, automated reporting, and threat predictions, which, in turn, entail always-on access to data stores, call detailed records, network logs, network usage, etc.

    5. Robust cybersecurity and anti-fraud protocol

    Telecom enterprise business should provide threat management, intruder detection, real-time alerts in a round-the-clock manner or as part of managed services. These provisions are imperative to deter cyber-crime like DDoS attacks and fraud. Protocols like SIP, diameter, and deep packet inspection are handy here, provided they are used in a manner that adheres to standard regulations.

    6. Asset optimization and capacity planning

    Optimizing asset utilization is one way to combat stagnating telecom revenues. Adopting end-to-end monitoring solutions of ever-expanding enterprise networks can ensure that the asset register is continuously updated on the status of reserve assets. This also prevents loss of revenue from an inability to provision new ports due to outdated information of unused ports/assets. Such a 360-degree asset view also optimizes capacity planning, directly reducing cost.

    A solid risk mitigation strategy that addresses the above vulnerabilities can make a huge difference in safeguarding operators from reputational losses and penalties associated with fraud and breaches. Chiefly though, it helps deliver a great customer experience that ultimately improves revenue.

    Webinar: Business Assurance in 5G: 5 controls you cannot do without

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