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  • Telecom fraud managers fight against fraudsters during COVID-19 crisis

    Telecom fraud managers fight against fraudsters during COVID-19 crisis

    There is now a global outbreak of COVID-19 with the resultant lock-down, panic, and fear across the globe. We have been keenly following the media to keep ourselves updated about the situation. While, very reassuringly, more than 95% of the workforces have started working from home with possible secure connectivity, fraudsters have also been equally active, looking for opportunities to attack the subscribers all over the world. In the past month, there has been a sharp increase in the incidence of IRSF, Robocalls, SMS Scams, Social Engineering fraud, DDoS and cyber-attacks.

    The operators and customers have been enormously strained during the past few weeks. We need to rise to the occasion to protect their interests. In my view, the following steps may be taken to deal with the telco fraud-related challenges:

    • Subscriber awareness: A subscriber awareness programme need to be launched immediately to make consumers wary of various fraudulent schemes that are floated during the time of panic and fear. A case in point as reported by one of the Asian operators is that last week many subscribers who had installed the COVID-19 live update apps on their phones coughed up a whopping $ 0.16 Mn because they were unaware that apps would also take over the status of the phone including SMS read and write function.
    • Prioritizing the fraud alerts monitoring: Remote working would have its challenges. The fraud management teams need to prioritize the alerts, especially which would have more impact on the subscribers and act on it and fix them on priority.
    • Root-cause corrective actions: Solution devised to eliminate the causes of fraudulent activity will stem the probabilities of its recurrence. For example, in the network, the range of the high-risk destination numbers may be blocked for a short period if an IRSF fraud attack is detected.
    • Communication and collaboration: We must be connected digitally to all the stakeholders so that they act tough on fraudulent activities on the network. SLA with stakeholders may be refined and suitably tweaked for faster action. This is one of the key elements when the whole team is working remotely to support daily operations.
    • Regular updates on emerging/latest fraud patterns: Frequently visiting the fraud forums to be abreast of the emerging/ latest fraud patterns worked out by the fraudsters. Criminals are always on the lookout to ruin the processes and systems for nefarious ends. Many operators have reported an increase in the robocalls, SMS scam & cyberattack during this period.
    • Making fraud management as part of the Business Continuity Plan (BCP): It is very important to incorporate fraud management as part of the BCP in a major way and ensure we have maximum coverage during this period.

    In my reckoning, the fraud management teams ought to be more vigilant and agile than ever before to meet the new challenges of telecom fraud becoming rife during this global outbreak of COVID-19. Fraud managers are superheroes when it comes to building trust with the customers.

    Stay safe and stay healthy!

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  • ¿Cómo afecta la canibalización del producto a su negocio de telecomunicaciones?

    ¿Cómo afecta la canibalización del producto a su negocio de telecomunicaciones?

    Maximizar el valor de por vida de un cliente y analizar su rentabilidad es muy importante y esencial para el negocio de telecomunicaciones en crecimiento. Según un informe de McKinsey, las Telcos serán testigo del crecimiento de mil millones de clientes adicionales de nivel medio, principalmente en mercados emergentes, para el año 2025. Para aprovechar esta creciente base de clientes, las Telcos buscan constantemente nuevas formas de interactuar y conectarse con su audiencia. La forma más efectiva de hacerlo es mediante el lanzamiento de productos frescos y emocionantes para satisfacer las cambiantes expectativas de los clientes. Si bien esta estrategia es altamente efectiva, sin embargo, puede conducir a la canibalización del producto, donde el volumen de ventas, los ingresos o la participación de mercado de un producto se reducen como resultado de la introducción de un nuevo producto por parte del mismo proveedor. Se puede desear la canibalización cuando queremos que el cliente cambie a un producto con ARPU más alto que ofrezca un mejor servicio y no deseado cuando el cliente cambie a un producto que genera relativamente un ARPU bajo. Subex ROC Insights ha estado a la vanguardia para ayudar a los operadores a analizar los datos de los clientes y el comportamiento de uso para obtener información que se traduzca en mayores ganancias con la canibalización deseada. Aquí queremos discutir cómo minimizar el impacto de la canibalización no deseada y compartir algunos casos de uso de la vida real también.

    Impacto de la canibalización de productos

    El mayor impacto de la canibalización de productos es la pérdida de ARPU existente y los ingresos respectivos, con los clientes actuales que se mueven a un plan de bajo margen. Este resultado es debido al lanzamiento de múltiples productos tan cerca uno del otro que se comen la cuota de mercado del otro. Por ejemplo, una empresa de telecomunicaciones líder en India mantuvo los precios cercanos y entrelazados con una pequeña diferencia entre los planes para las llamadas locales a sus propios teléfonos de red. Si bien la compañía de telecomunicaciones usó sus planes de precios para aumentar estratégicamente su participación en el mercado al darles a los clientes incentivos para hablar con otros usuarios de la misma compañía de telecomunicaciones, esto, sin embargo, resultó en la canibalización del producto.

    Análisis de productos: una medida vital para prevenir la canibalización

    El impacto de la canibalización del producto puede minimizarse mediante el análisis de productos. El análisis de productos ayuda a las empresas de telecomunicaciones a obtener recomendaciones sobre cómo dirigirse a los clientes. El análisis de productos ayuda a tomar la decisión correcta con respecto a los productos que se lanzarán analizando el rendimiento del producto y optimizando los productos según los requisitos del cliente. Les ayuda a ser proactivos en términos de:

    • Estimación de la contribución de ingresos por producto: la mayoría de los ingresos de una empresa de telecomunicaciones se deriva del uso de los clientes. La analítica del producto ayuda a las Telcos a determinar varios factores, como el volumen total de datos, minutos y SMS transmitidos a través de la red y el contenido consumido en múltiples canales, como varias plataformas OTT. Dado que los operadores pueden aprovechar los análisis anteriores, podrán crear productos únicos que cautiven a los nuevos clientes.
    • Comprender el tipo de cliente que consume cada producto: la analítica del producto ayuda a las empresas de telecomunicaciones a comprender a los clientes en términos de teléfonos, tiempo de uso, la proporción de voz y datos, comportamientos de uso de SMS y tipo de contenido consumido. Esto le permitirá a las Telcos la ventaja de tener una imagen clara al desarrollar nuevos catálogos de productos. Los perfiles de los clientes y los conocimientos sobre su patrón de uso pueden ser útiles para convertirse en grandes contribuyentes. Esto puede ser aplicable para estudiantes que regresan a la universidad después de un descanso, o personas que viajan por vacaciones. Estas actividades conducen a un mayor uso, por lo tanto, si les ofrece productos relevantes, está creando una canibalización deseada que ayuda a un cliente satisfecho con un ARPU más alto. En uno de los proyectos, el equipo de ROC Insights analizó el comportamiento de uso del cliente e identificó una mayor actividad nocturna para algunos usuarios. Esta información ayudó al operador a encontrar un enfoque hiperpersonalizado para apuntar a estos clientes con paquetes nocturnos que resultaron y generaron mayores ingresos y un ancho de banda de red optimizado.
    • Mapeo del comportamiento de uso de los clientes: la analítica del producto ayuda a las Telcos a rastrear la conducta de los clientes. Obtienen información profunda sobre qué ofertas los atraerán, por qué eligieron una red, cuáles son sus comportamientos de uso de datos, voz y contenido OTT, etc. Un ejemplo de esto sería la campaña de “recuperación” que ejecutamos para un cliente después de analizar el comportamiento de éste. Vimos una caída periódica en el uso en múltiples regiones con mayor inactividad y abandono. Esto se contribuyó principalmente debido a que los estudiantes universitarios iban de vacaciones semestrales. Y después de las vacaciones, no todos los clientes estarían activos, algunos de ellos se mudarían a la red de la competencia. El operador lanzó paquetes personalizados que resultaron en una mayor actividad, márgenes y menor rotación.
    • Percibir la huella de la red de los clientes: al registrar y analizar los patrones de uso de la red por hora del día, por cliente y con un análisis preciso de los datos, los operadores pueden formar una buena imagen de cómo los diferentes tipos de clientes contribuyen al valor económico. Los nuevos productos se pueden diseñar en consecuencia.
    • Medición del impacto de la canibalización luego de nuevos lanzamientos y campañas: es vital medir de manera proactiva el impacto de la canibalización, ya que esto ayudará a las empresas de telecomunicaciones a determinar la rentabilidad y el ROI del nuevo producto. La ayuda de Product Analytics determina la cantidad de nuevos clientes que la red ha adquirido y cuántos de ellos cambiarán de productos existentes, lo que los equipará para tomar medidas correctivas para minimizar el efecto de la canibalización.
    • Segmentación de clientes en términos de contribución y huella de red: análisis precisos ayudarán a Telcos a determinar qué clientes vale la pena buscar e invertir y en qué productos pueden ayudarlos a lograr este objetivo. Ayuda a evitar la adquisición de clientes de bajo valor a un alto costo, así como a administrar selectivamente a sus clientes actuales para obtener el mejor rendimiento financiero.

    ¿Cómo controlar el efecto de canibalización?

    Para minimizar el efecto de canibalización, los Telcos deben asegurarse de que los productos estén diseñados perfectamente. Cada producto debe estar claramente posicionado para el segmento de usuarios al que está dirigido, con una diferenciación muy clara en términos de beneficios y con puntos de precio correctos para separar los segmentos objetivo considerando la necesidad del cliente y la capacidad de pago. Si nos dirigimos a un cliente de alto uso de datos con un mejor paquete de voz y SMS, es una pérdida de ingresos, esfuerzos y las posibilidades de abandono aumentan significativamente. Con menos planes de precios bien diferenciados, las posibilidades de que los planes se canibalicen entre sí son mínimas, ya que cada plan apunta a un segmento diferente.

    La canibalización de productos es un riesgo inevitable al que se enfrentan las empresas de telecomunicaciones, pero con medidas proactivas regulares y extensas, las compañías de telecomunicaciones pueden anticipar tales situaciones de canibalización y contener tales ocurrencias.

    Optimice sus productos de telecomunicaciones como Bundling, Recomendación de producto, Análisis de sensibilidad, Halo de producto y Efecto de canibalización para mejorar ARPU.

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  • Is Product Cannibalization Eating into Telcos’ Revenue

    Is Product Cannibalization Eating into Telcos’ Revenue

    Maximizing a customer’s lifetime value and analyzing their profitability is highly important and essential to the growing telecom business. According to a report by McKinsey, Telcos will witness the growth of an additional billion middle-tier customers, mainly in emerging markets, by the year 2025. To tap into this growing customer base, Telcos are constantly seeking new ways to engage and connect with their audience. The most effective way to do so is by launching fresh and exciting products to cater to changing customer expectations. While this strategy is highly effective, it can, however, lead to product cannibalization—where the sales volume, revenue, or market share of one product is reduced as a result of the introduction of a new product by the same provider. Cannibalization can be desired when we want the customer to switch to a higher ARPU product that delivers better service and undesired when the customer switch to a product that relatively generates low ARPU. Here we will talk about the undesired cannibalization.

    Impact of Product Cannibalization

    The biggest impact of product cannibalization is the loss of existing ARPU and respective revenues, with current customers moving to a low margin plan. It results due to the launching of multiple products so close to each other that they eat into each other’s market share. For example, a leading telco in India kept the pricing close and intertwined with a little difference across the plans for local calls to its own network phones. While the telco used its pricing plans to strategically increase its market share by giving customers incentives to talk to other users of the same telco company, this, however, resulted in product cannibalization.

    Product Analytics—a Vital Measure to Prevent Cannibalization 

    Product cannibalization impact can be minimized by wielding product analytics. Product analytics help telcos gain recommendations on how to target customers. Product analytics helps make the right decision regarding the products to be launched by analyzing product performance and optimizing products based on customer requirements. It helps them to be proactive in terms of:

    • Estimating the revenue contribution per product: The majority of revenue for a telco is derived from customers’ usage. Product analytics helps telcos determine various factors such as the total volume of data, minutes, and SMS transmitted over the network and content consumed over multiple channels like various OTT platforms. With operators being able to tap into the above analytics, they will be able to create unique products that captivate new customers.
    • Understanding the type of customer consuming each product: Product analytics helps telcos understand customers in terms of handsets, time of usage, the proportion of voice, and data, SMS usage behaviors and type of content consumed. This will enable Telcos the advantage of having a clear picture when developing new product catalogs.
    • Mapping the usage behavior of customers: Product analytics help Telcos track the psyche of the customers. They gain deep insights into what offers will attract them, why they chose a particular network, what their data, voice and OTT content usage behaviors are, etc.
    • Perceiving network footprint of customers: By recording and analyzing network usage patterns by time of day and by the customer and with accurate analysis of the data, operators can form a good picture of how different types of customers contribute to the economic value. New products can then be designed accordingly.
    • Measuring the impact of cannibalization post new launches and campaigns: It is vital to proactively measure the impact of cannibalization as this will help telcos determine the profitability and ROI of the new product.Product Analytics help determines the number of new customers the network has acquired and how many of them will switch from existing products – which will equip them to take corrective measures to minimize the effect of cannibalization.
    • Segmenting customers in terms of contribution and network footprint:Accurate analytics will help Telcos determine which customers are worth pursuing and investing in and what products can help them achieve this goal. It helps in avoiding the acquisition of low-value customers at a high cost, as well as selectively managing their current customers for the best financial yield.

    How to Control the Cannibalization Effect?

    Product cannibalization can be managed by understanding products that offer unique features, meets customer needs, reduces the customer’s total costs, creates a high usage value product and is innovative in being the first of its kind in the market.

    To minimize the cannibalization effect, Telcos need to make sure the products are designed perfectly. Each product should be clearly positioned for the segment of users it is aimed at, with very clear differentiation in terms benefits, and with right price points to separate target segments considering customer need and ability to pay. With fewer well-differentiated pricing plans, the chances of plans cannibalizing each other are minimal as each plan targets a different segment.

    Product cannibalization is an inevitable risk that Telcos face, but with regular and extensive proactive measures, telecommunication companies can anticipate such cannibalization situations and contain such occurrences.

    Optimize your telecom products such as Bundling, Product Recommendation, Sensitivity Analysis, Product Halo and Cannibalization Effect to improve ARPU.

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  • Capacity Planning for 4G Networks

    Capacity Planning for 4G Networks

    As the telecom industry prepares to move to the 5G, it will look forward to the benefits that come with the technology such as faster speeds, low latencies, seamless connectivity, besides the possibilities of opening new business revenue streams for CSPs. 5G will bring with more unique use cases in areas beyond the consumer realm, with enterprise being a key focus area and a new point of entry for CSPs. However, while 5G does hold this promise leading to CSPs gearing up for this new technology, are they getting 4G right? Are their existing tools for 4G Capacity Planning and Network Capacity Optimization helping them make the most out of their 4G network investments done in the past?

    Most CSPs may not have a standard 4G Network Capacity Management tool in the first place, and those that do, may not be able to realize the return on their network investments recommendations generated in the past. One potential reason could be the limitations that come with their existing tool to ingest, process, and correlate data flowing from different domains.

    Another could be their current Network Capacity Management Process does not offer flexibility to network planners to run multiple iterations and simulations before zeroing on a final plan. Along with it, network capacity planning best practices often get lost because of lack of capability of a network planning tool to take feedback from past actions and record it for future usage.

    Traditionally, network capacity management metrics focus on technical KPIs as the only set of parameters used for network capacity planning. Though the approach worked fine a few years back, the drawback of this method is that the network capacity planning process outcome only generates a list of network elements required for capacity upgrade and augmentation. It doesn’t provide any priority-based investment decisions which can help a CSP invest in the areas capable of generating quick revenue while ensuring the customer experience is not compromised. All this can be achieved only with advanced analytics-driven network capacity and performance management systems built on Artificial Intelligence and Machine Learning. Such systems would be capable of providing meaningful insights from not just technical KPIs but millions of records flowing in the form of business and customer experience metrics, which otherwise gets missed.

    To know more about how advanced analytics can redefine what is network capacity Management for the 4G era.

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  • How Advanced Analytics can help Telcos sail through the Challenges and achieve Success

    How Advanced Analytics can help Telcos sail through the Challenges and achieve Success

    Data has been moved from being a technological asset to become the most important business asset. The whole business strategy right from entering new business verticals, expanding service or product portfolio to creating marketing or sales strategies, everything revolves around data. Telecom industry has been at the forefront in terms of having huge volumes of customer data and analyzing this for different purposes. But basic analytics is the story of the past. For Telecom companies, advanced analytics brings in insights that were impossible to imagine earlier. Simple analytics talked about descriptive or diagnostic analytics but advanced analytics for telecom goes one step further. It offers predictive analytics and prescriptive analytics that can help CSPs to plan their growth with some surety on ROI.

    Why We Need Advanced Analytics for Telecom?

    The growth in terms of number of users and the magnitude and scale of services that are offered speaks for the need for advanced analytics for Telcos. The number of unique mobile subscribers has reached to 5.1 billion in 2019. Some parts of the world have already started using 5G while some are still on 4G/3G. We have innovations in IOT, M2M, AI and cloud computing as this brings another opportunity for CSPs i.e. enterprise business offering. As this will accumulate humongous amount of data and simple metrics and analysis are no more capable to offer real time insights for business problems, hence it further advocates the need for advanced analytics as the process are going to be more cumbersome. We need advanced analytical capabilities that are agile, fast and easy to execute at the same time.

    What are the various ways Telcos can use advanced data analytics?

    CSPs can apply advanced analytics in all business areas and help in achieving operational efficiency. Some of the prominent use cases that advanced analytics can solve for telecom are from revenue analytics, risk analytics, customers and campaign intelligence, product intelligence or sales and marketing campaign intelligence.  It can help with forecasting analytics to help CSPs design their action plans. The advanced analytics’ s near real time capability to provide insights can allow timely actions to avoid or tackle any unexpected challenges.

    Benefits that Advanced Analytics Offers

    Advanced analytics for telecom offer lot of value additions for all business verticals. CSPs can use advanced analytics to plan their network planning. Various metrics such as user density, usage pattern, device types will offer insights to plan their network availability. Analysing customer data will help with churn prediction, revenue forecasting, insights for new products & services.

    Advanced analytics has opened a plethora of new information that was not accessible earlier. It shares insights beyond the usual metrics and build creative models that can easily cater to the unusual business problem statements.

    Conclusion

    Subex Analytics Center of Trust (ACT) offers advanced analytics capabilities to harness the real power that data can provide. It is driven by the Trifecta approach that keeps the business goals in mind. It is agile and quick at responding to the latest trends and technical requirements.

    trifectaAnalytics to Business to help you build a future proof infrastructure that saves a significant CAPEX. The consumable outcomes approach combines the best of both worlds – human intelligence and machine learning; hence it addresses the concerns logically and accurately. The result is you get a fully automated intelligent architecture that can deliver consumable outcomes across all audience levels in a democratized fashion.

    To find out more about how domain-driven analytics can impact your ROI, Increase Customer Experience and Profitability.

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  • How big is the impact of the IRSF Fraud and 5 simple strategies to control IRSF

    How big is the impact of the IRSF Fraud and 5 simple strategies to control IRSF

    International Revenue Share Fraud (IRSF) is one of those fraud types that has been alive for two decades now, all because of the fraud being intricate in its pattern while the approach to it being still very reactive. Here, the motive of the fraudster is to receive the revenue share from the termination charge on international premium numbers. The fraudsters abuse the telecom operator’s infrastructure to artificially inflate traffic onto high-risk international destinations with the intention of non-payment. This fraud is common across geographies and has an estimated fraud loss of USD 5.04 Billion (The highest fraud loss contributor) as per the Communications Fraud Control Association (CFCA) Global Fraud Loss Survey, 2019.

    Lack of adequate steps taken to protect the network has caused this fraud to grow by leaps and bounds. In this fraud, the attacker usually tries to exploit the vulnerabilities of the Telecom Service Provider’s assets and attacks by either calling to unallocated number ranges or land calls onto international premium rated services or illegitimately route calls to short stopped mobiles. Subscription fraud, PBX hacking, Arbitrage Margin, SIM Cloning, Device theft and abuse of promotional services are often the commonly used methods for executing the fraudulent practices. The fraud is also quite common with many fixed line providers.

    In my experience of working with multiple operators, globally, I feel that the most common challenge faced by operators is in understanding the fraud pattern and method used by the attacker. The impact on the operator becomes brutal when fraudsters use unknown patterns of execution and sophisticated techniques to attack the network. IRSF attacks from roaming network, call conferencing, call forwarding, calling cards, negative margin abuse for products and services are among the more popular methods for a fraudster in launching attacks.

    Also, the lack of regulatory precedence in governing the way of carrying out business with international carriers is not sufficiently strict, setting the perfect breeding ground for fraudsters to flourish.

    Why has this fraud grown in leaps and bounds and how do I ensure control proactiveness?

    Traditional and reactive fraud countering mechanisms as of date do not have a full-proof solution, and one of the biggest reasons is that there are not enough fraud controlling strategies, mechanisms, and systems in place. IRSF, unlike other fraud types, requires a continual and proactive measure for control. More than just the “run-of-the-mill” detection techniques, the fraud type requires a well-planned control and mitigation steering strategy and here are six simple strategies, to begin with:

    • Fraudulent practices have become cleverer over time.

    If we brag of the fact that the fraud detection technologies have become quite sophisticated over time, we must not forget that the fraud practices too have gained an equal amount of intelligence. Fraudsters these days are quick to realize technology loopholes and system fault lines. It does not take much for fraudsters today to detect the fraud finding patterns and control logic of CSPs and identify the loophole in the system. In order to counter the fraudster’s attempt of IRSF, study of method and pattern become a critical process. Also use of SIP monitoring technique to identify devices/tool such as SIP vicious can help telcos to prevent IRSF. A mix of AI/ML techniques and models can be used to detect new IRSF fraud patterns with automation and build IRSF intelligence e.g.: trends in calling patterns.

    • Demoralize your IRSF attacker

    Letting your attacker attack you to dig his own grave sounds like an oxymoron? Actually not! It is, in fact, possible to have a honey-trap system in place where you lure the attacker to launch the attacks onto it without a fruitful outcome. The more the attacker’s attempts fail, the less hopeful they strive any further. Additionally, gathering intelligence from trusted suppliers who can provide information about prominent fraud groups and support surgical blocking of international number ranges has proved to be a successful strategy globally to counter IRSF.

    • Think of the customer and protect their interests

    IRSF not just drains away revenue resources but also can cause customer dissatisfaction, causing them to churn out of the network eventually. IRSF not only targets retail accounts but enterprise customer is a key risk group costing the telecom operator millions of dollars. Hence it is crucial that we don’t ignore whenever a customer complains of frequent cross-connections or call diversions for international calls.

    • Have an “Anytime-Anywhere” vigilance strategy with automation to your advantage

    The detection processes for IRSF may be complicated and resource-intensive at times. However, having the right strategies, the right processes with the right amount of automation applied to them can help the business in a significant way. I personally recommend a 24 x 7 detection strategy to be put in place to counter the IRSF attacks. From the cases that I have dealt with, it’s my observation that though IFRS attacks happen round the clock, however, the wee hours of the morning or off-business hours are critical target. Having a rotational manpower strategy can really work wonders at times. However, there could also be instances where having a 24*7 approach may not be possible owing to the lack of capital or high cost of human resources. In such instances, a mix of the automation of detection processes and human intensive operations during crucial hours will be of value.

    • Never ignore negative margins

    Negative margins can occur at any level. It could emerge while planning the pricing strategies of the products, services, use of calling cards in international destinations or interconnect agreements. Feeble margins on profits can often open a pandora’s box for fraudsters. Just the basic knowledge on negative margins is enough for fraudsters to break open mayhem. Trend reports on traffic patterns with priorities given to partnerships with frugal margins can save the day!

    • Pursue strategic knowledge partnerships to establish fraudster intelligence

    Sharing knowledge and having a supportive ecosystem for interaction with carrier partners and vendors in the value chain can be a practical step closer to proactiveness. Also, MoU’s established with industry forums and CoEs like GSMA, CFCA, RAG Blockchain for Wangiri, and others can help CSPs gain information such as PRS test numbers and services, high-risk range numbers, unallocated number series which can be used as vital sources of references to counter this fraud. Telecom operators can also build up the internal defense by establishing service controls e.g. restrictions on the use of international and roaming capabilities for certain customers. And restrict international call forwarding, multi-party calling, etc.

    When I say a reactive approach for AI / ML based IRSF fraud detection, I mean that much of the effort and systems built towards countering the fraud are in silos and so are the human efforts that go into it. By a proactive system, I mean a system that is quite unified in its approach and can perform end to end operations associated with the fraud type. A proactive Fraud Management system shall flag the first call in roaming, track significant deviation in usage behavior, high volumes of international traffic to high-risk destinations, sequential dialing, etc. and couple it with the use of knowledge databases like Subex IRSF data intelligence that includes unallocated number ranges, high-risk ranges, known fraudulent numbers to support network-based blocking and/or integration for early identification of high-risk behaviors and automated blocking, where required.

    One of the many ways of building a more proactive and unified system is to go the AI (Artificial Intelligence) way. A well thought out AI technology strategy can really help detect the fraud at a very early stage and help you choose the right controls for specific problems in question. It aims to reduce the time taken by the laborious human efforts that go into the detection stage while helping analysts and investigators concentrate on the need of the hour. Much as the famous English saying goes “Every cloud has a silver lining,” the impact of the IRSF can considerably be reduced by just broadening the organizational perspectives towards the fraud.

    Subex has recently partnered from Biaas for IRSF data Intelligence, To know how you can benefit from this partnership

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  • What is Digital Trust?

    What is Digital Trust?

    Digital Trust is a concept that enables users to carry out business transactions in a safe, secure, ethical and reliable manner.

    In a digital world, everything is ultra-fast and instantaneous. Agility, and speed are perhaps the two key benefits of living in an all-digital world and are probably the most desirable qualities of a digital interaction. However, the digital nature of today’s businesses has brought about significant changes in business models, technology enablers and customer expectations. Amidst all these rapid changes, if there is one thing that has remained constant, it is the need for trust. However, the concept of trust was different in a physical world, and it is more fluid and continues to evolve in a digital world.

    Trust underpins the success of every business, traditional or new age. Each transaction and interaction on a personal, societal and business level requires the establishment of trust. With the advent of digital disruption, the lines between digital and physical worlds begin to blur, and the contextual definition of trust also evolves accordingly. Unlike in the physical world, trust in the digital world must be established spontaneously between entities that often are unrelated to each other, and this trust must be constantly examined and re-established during the course of the interaction.

    Conventional models of trust are not flexible enough to meet the demanding requirements of digital interactions due to the high number of different relationships — often sporadic and short-lived — between different people, businesses, things, AI programs, machine learning algorithms and other entities.  Digital Trust is an evolution of traditional models of trust to cover a larger set of requirements of digital businesses by arriving at levels of measurable confidence to make risk-based decisions.

    For enterprises, Digital Trust needs to be an all-encompassing concept, being multi-directional, and multi-dimensional. This means for a business to establish great levels of Digital Trust, it needs to demonstrate trust between consumers, shareholders, partners, vendors and governing bodies. More importantly, this trust needs to be multi-directional, meaning it is as important for enterprises to be able to trust their consumers as it is for consumers to trust the enterprise.

    Currently, Digital Trust covers six key areas, namely, privacy, security, identity, predictability, risk mitigation and data integrity.

    Privacy: The ability to carry out a transaction while not dipping into personal information that is not necessary for the transaction.

    Security: The ability to carry out a transaction in a manner that protects the infrastructure and data of the transacting parties from malicious threats.

    Identity: The ability to protect the true identity of the stakeholders of a transaction unless it is exposed with the full consent of the entity.

    Predictability: The ability to be able to extract meaningful insights and make scientific forecasts, to foresee business risks and support planning.

    Risk Mitigation: The ability to identify, evaluate, and prioritize risks followed by coordinated and economical application of resources to minimize, monitor, and control the probability or impact of unfortunate events or to maximize the realization of opportunities.

    Data Integrity: The maintenance of, and the assurance of the accuracy and consistency of data over its entire lifecycle.

    Given the market dynamics where trust is at an all time low, businesses can truly unlock their potential by focusing on the above mentioned tenets of Digital Trust.

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  • How Enterprise Blockchain will Change the Telecom Intercarrier Settlement Process

    How Enterprise Blockchain will Change the Telecom Intercarrier Settlement Process

    Enterprise Blockchain solution for telecom seems to be a promising development for the telecom industry as it strives to solve the challenges faced by Telcos in their settlement process. It is based on Distributed Ledger Technology (DLT) which has attracted lot of attention in the recent time to offer a  Way to record transactional data that should become a single source of truth to establish digital trust in the partnerships.

    Why Telcos are looking at blockchain as a possible solution for partner settlement? Telecom network operators across the world gets into interconnect agreement which enable a seamless communication among their customers. These agreements are executed between domestic and international operators for mobile, fixed and internet services. Telecom operators collect and store detailed activity information as events. Interconnect partners share these CDRs for the purpose of verification and settlements. This process is cumbersome, inefficient, lengthy, costly, and error-prone. Missing CDRs and discrepancies in CDRs are very common problems.

    As the interconnect revenue continues to decline it has become essential to address the blocked revenue due to disputes and to optimize the overall cost involved in resolving these discrepancies. The enterprise blockchain present a possibility that can make the settlement process error free and help the Telcos a faster and efficient access to the blocked revenue. Subex is actively working with multiple enterprise blockchain technologies to address the need.

    Subex is chairing the Linux Foundation’s Hyperledger Special Interest Group (SIG) Intercarrier Settlement subgroup to develop DLT based solution for partner settlement process. The purpose of the Special Interest Group (SIG) is to help Telcos understand the key issues in partner settlement and offer possible solutions for the same. Subex has been a key contributor in creating the solution brief. The group has been successful in defining a solution based on Hyperledger Fabric developing a working PoC which is available for demonstration for those who are interested.

    The proposed solution broadly addresses how a DLT-based solution can:

    • Converts the reactive dispute management process to more proactive process
    • Create a single source of truth, which allows network operators to access and verify billing and cross-charging data in real-time.
    • Reduce overall costs by replacing tedious processes, reducing dependency on intermediaries such as clearinghouses with simple, near real-time and error-free reconciliation and settlement process.
    • Help in evidence collection and fraud mitigation.

    DLT has shown great potential in solving issues related to fraud, errors and creating a secure data source. Given the possibilities mentioned in the solution document, the likelihood of extending it as a full-fledged solution is very high which means faster dispute resolution, reduction in overall cost and an efficient partnership that will help Telcos embrace the new technologies and innovate their services as per the need of the market.

    Link to access solution brief: Here

    Link to the Hyperledger Blog: Here

  • Collaboration – The key to combat IRSF fraud

    Collaboration – The key to combat IRSF fraud

    Fraud continues to be a major problem for telecom operators, costing them billions of dollars annually. While telecom operators are continuously innovating to create new avenues of revenue streams to fight declining revenue margins from Voice and SMS services, technological advances are empowering fraudsters to evolve their fraudulent practices to tamper into the network. Telcos need to have access to the right threat intelligence information to combat fraud.

    International Revenue Share Fraud (IRSF) is one of the frauds which telcos have been trying to overcome for decades but still struggle to solve. Fraudsters usually exploit the vulnerabilities of the Communication Service Providers (CSPs) assets and attack by either calling to unallocated number ranges, landing calls onto international premium rated services, or illegitimately routing calls to short stopped mobiles. Subscription fraud, PBX hacking, Arbitrage Margin, SIM Cloning, Device theft, and abuse of promotional services are often the commonly used methods for executing fraudulent practices. IRSF attacks from the roaming network, call conferencing, call forwarding, calling cards, negative margin abuse for products and services are also some of the more popular methods for a fraudster in launching attacks. CSPs need to look to overcome the IRSF fraud menace to avoid revenue losses, network clogging, poor customer, and partner experience and negative impact on the brand image.

    While the Fraud Management (FM) system needs to be in place to overcome IRSF, one of the ways to tackle IRSF fraud is to have access to global number threat intelligence information. CSPs can configure their FM system to utilize this threat intelligence to detect and prevent fraud. To empower Subex ROC™ Fraud Management customers with threat intelligence information, Subex has recently partnered with RAG Wangiri blockchain consortium to provide its customers access to real-time threat intelligence to combat Wangiri fraud.

    As a next step, Subex is now partnering with Biaas, a leading expert in global number plan management for Pricing, Assurance, and Fraud Management within the telecommunication industry for IRSF threat intelligence. Through this partnership, Subex aims to provide its customers access to a powerful global number intelligence database that uses real-time information to battle International Revenue Sharing Fraud (IRSF). CSPs will have access to the following by subscribing to this database:

    • IRSF Test Number Database : Intelligence numbers gathered from IPRN websites and other sources. This will enable the CSP to identify if calls on their networks are being made to any IRSF Test Numbers as calls to IRSF Test Numbers are often an indicator that a fraud is about to happen.
    • Unallocated Destinations Database : Number ranges that are not allocated in any National Numbering Plan and should therefore see no legitimate traffic – any calls made to these destinations can confidently be flagged as fraudulent. This data even includes Unused Destinations, which appear allocated and valid but are not used by any operators currently. CSP will able to identify calls to expensive unallocated or Unused/Unassigned International destinations. CSP can use this data in many ways to pro-actively prevent or reduce such IRSF and other international voice frauds.
    • Allocated Destinations Database : Number ranges that are currently allocated to various operators. CSP will have access to tailored lists of International Higher Cost destinations (e.g. depending on geography or call types/tariffs) which can be utilized to assign higher priority to those potential frauds which would cause losses.
    • Digit String Length Database : Intelligence on the length of the numbers that are gathered from traffic analysis which can allow detection of fake calls made by fraudsters to destinations of invalid lengths.

    CSP will also have access to international fraud helpdesk run by expert Biaas professionals to facilitate fast and accurate issue resolution and decision making. By having access to this critical intelligence from Biaas, telecom fraud management teams will be able to effectively configure multiple types of defenses in the form of rules and real-time actions to keep fraudsters at bay. Combining this effective number intelligence with rich fraud detection capabilities provided by ROC Fraud management, CSPs will now have greater control in fighting IRSF fraud thereby directly protecting their revenue losses.

    To know more about how you will benefit from this partnership

    Download the flyer now!

  • What are the 5 ways for telcos to minimize the impact of scam calls and messages

    What are the 5 ways for telcos to minimize the impact of scam calls and messages

    More than 50% of the calls made to mobile phones today are scam calls, according to recent research. These scam calls have grown exponentially in the last decade. With technological advances, scamsters are also evolving and finding newer ways to lure customers.

    These are some of the most common ways how scamsters try to trick the customers:

    • Callers use fake names and pose as officials from government agencies like IRS, Border agency and threaten arrest, prosecution, and imprisonment
    • In some cases, callers demand thousands of dollars to be wire transferred immediately as there are pending dues are in the customer names to avoid arrest
    • Calls and SMS saying customer has won the incredible prize of millions of dollars and need to share personal data like DOB, address, account details, financial information and bear the tax/wire transfer charges to claim the amount
    • One ring scam alias Wangiri wherein caller gives a missed call from PRS number and when the customer calls back they are charged heavily for these calls
    • Caller ID spoofing is also one of the common ways to make a customer believe that this is a legitimate number

    The key objective of scammers include stealing personal data from customers only to misuse later to attempt other telco frauds like account takeover, subscription fraud, handset fraud, and so on. Though customers are required to be vigilant to these scams, the responsibility lies with the operator to put measures in place to prevent these frauds as fraudsters use telco network as a medium to carry out this fraudulent activity. These frauds severely impact customer experience and damage the brand image of the operators. Recently a middle east operator reported that customers are receiving scam messages over OTT applications as well. Do not Call registry does not seem to solve the problem anymore and there is a need for telcos to implement new and advanced methodologies to combat these frauds arising from scam calls.

    Here are 5 ways how telcos can combat these frauds:

    1. Advanced machine learning methodologies

    Leverage machine learning and develop advanced supervised and unsupervised models with historic data and can help the operator to profile the calls and SMS for any deviations and detect anomalies in real-time with an accuracy of 98.5%. Machine learning allows the operator to make decisions based on information as it happens, empowers them to anticipate and take proactive action.

    2. Signaling Security

    Operators FMS system should monitor signaling traffic from layer 3 to layer 7 in real-time to secure the network signaling exploitation on Voice, and SMS services. With signaling security operator can detect and prevent scam calls like Wangiri, IRSF and CLI spoofing in real-time.

    3. Real-time threat Intelligence

    Operators should have access to real-time threat intelligence of hotlists to block the scam calls in real-time. Subex honeypot network deployed in 64 locations in the world helps ROC FMS to be updated with threat Intelligence. And also, our recent tie-up with RAG Wangiri blockchain consortium aims to provide our FMS customers with real-time Wangiri hotlists to prevent Wangiri fraud.

    4. Voice and SMS Firewalls

    Operators should install a carrier-grade threat-focused firewall capable of subverting threats. The firewall monitors the outgoing and incoming traffic from/to your network and blocks malicious/spam calls depending on the rules configured within the firewall.

    5. Subscriber/Customer Awareness

    As a proactive approach, the operators should frequently make the customers aware of the increased scam calls and how not to be the victim of these calls. This will help in improving the customer experience by reducing the monetary losses of customers.

    While scam calls can not be completely eliminated, having the right fraud protection strategy in place to address these frauds will ensure that operator protects customers from falling prey to these scams and deliver high quality service to their customers.

    To understand how you can detect and prevent scam calls using advanced machine learning models

    Download the Case Study