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Tag Archives: Fraud Management

What is Wangiri Fraud and how does it impact telecom operators?

Wangiri fraud, a callback scam dates has its origin to the Japanese word which means “one ring and cut”. Telecom operators are facing this for over a decade now and this is only growing exponentially year on year around the globe. In Wangiri, a fraudster gives a missed call to several victim’s phone numbers of different countries from an international or unusual number. To the user, the CLI (caller number ID) is modified in such a way that it looks like a genuine call and when the victim calls back, it turns out to be a premium rate service (PRS) number owned by fraudster for which the victim is charged heavily for the calls. The fraudster intends to keep the victim on hold to increase the billed amount. The premium rate service provider pays the fraudster a certain share of the call revenue for each minute of call received by the premium rate number.

As per the CFCA 2019 fraud loss survey report, Wangiri is one of the top 5 fraud methods used by fraudsters to carry out fraudulent activities. It is also estimated that telcos are losing close to USD 1.82 billion globally to this fraud.

FIGURE 1.1: Wangiri Fraud

Impact of Wangiri fraud on telecom operators

Telcos incur both direct and in-direct loss due to Wangiri Fraud. Wangiri impacts the customers adversely resulting in customer churn due to high customer dissatisfaction from bill shocks and bad customer experience. It also has a negative impact on the operator brand image as subscribers would complain about the high call rates charged to them without them being aware of it. There is also an impact on the cost due to the increase in customer management.

Why Wangiri cannot be eliminated?

The two main reasons due to which Wangiri cannot be eliminated but can be managed are:

  • There is no regulation defined on the carrier business causing the fraudster to take advantage of the vulnerabilities of the carrier network.
  • The lack of visibility on the end carrier who is terminating the call is another reason why Wangiri can’t be eliminated.

The end carrier who terminates a fraudulent missed call is not aware of the fraudster details and the country from which call has originated is a high-risk destination or not. Better awareness at the carrier level can significantly decrease many Wangiri cases.

As is clear from the statistics, Wangiri is eating a good chunk of the overall telecom revenues globally and needs to be addressed by the operator. Here is an interesting blog which talks about 8 simple strategies for telcos to combat Wangiri fraud. We conclude that Wangiri fraud cannot be eliminated, but its adverse impact of direct and indirect losses to the operator can be minimized to a large extent by having a robust fraud management system that can monitor the calls at source and tear down the calls in real-time.

A tier-1 Middle East based telecom operator leveraged Subex’s ROC Fraud Management’s signaling intelligence to detect and prevent Wangiri frauds.

Read the case study now!

SIM SWAP FRAUD: Stepping into the fraudster’s shoes!

“Lose a credit card and the loss may be in thousands… Lose a SIM Card, the loss is irreparable”

Last week, Twitter CEO Jack Dorsey became the latest high-profile account to be targeted by SIM swappers. Dorsey’s account sent several tweets, including some with racial slurs and others that defended Nazi Germany. Luckily for him, his account was secured soon after, and the consequences weren’t catastrophic. However, there have been many instances where SIM swappers have left victims in a really troubled state – especially the ones targeted for monetary gains.

SIM swap is a type of phishing fraud that poses a serious threat to customer along with the telecom and the banking environments. The SIM SWAP fraudster in here obtains an individual’s banking details through vishing/smishing/phishing techniques or by purchasing these from organized crime networks. They then use this information, including personal details sourced via social media, to pose as the victim to the mobile network operator and fool them into cancelling and reactivating the victim’s mobile number to a SIM in their possession. As a result, all calls and texts to the victim’s number are routed to the fraudster’s phone, including one-time passwords for banking transactions. After receiving a one-time pin or password from a bank, the fraudster can then potentially access the customer’s bank account and transfer funds. The SIM SWAP fraud impacts not just the victim, financially but also the telecom operator and the bank, equally. As non-adherence to consumer interests and protection, in many countries, both the entities (the telco and the bank) are legally liable to compensate the victim for his/her financial losses. When the loss is in millions, the impact is very grave!

Have you ever taken a moment to pause and think from a fraudster’s perspective to counter the fraud? Well most blogs that you will find on the internet on SIM SWAP will tell you ways (in bulletin points) as how to protect your assets from the SIM SWAP fraud. However, I am quite sure that there will only be a handful of blogs that will tell you how a SIM SWAP fraudster thinks in-order to be able to protect your customers from such attacks.

Without much ado, let me take you through the 4 vicious stages involved in the SIM SWAP fraud attack which will help you understand your SIM SWAP fraudster better and stay ahead of them on any given day!

Stage 1 – “Cherry picking and stalking”

Fraudsters are always on the loom to pick on their fraudsters and the social media, has, in a great way helped them in getting away with their desired schemes. A SIM SWAP fraudster may look for a high-profile customer or a prosperous and wealthy business personnel who generally solicits with prospective clients over social media. The SIM SWAP fraudster here could impersonate one such client, send out a connection request and start to closely monitor the victim’s activities. The SIM SWAP fraudster can even hijack an account of the victim’s affiliate to initiate conversations/get more information about the victim. In events where the victim does not have enough digital footprints, SIM SWAP fraudsters have even taken the road of dumpster diving and shoulder surfing!

Stage 2 – “Impersonating the victim”

At this stage, the fraudster has got all the information he/she needed to pass through the authentication protocols required to get hold of the victim’s assets. Once he/she has managed to convince the bank and Telecom Operator of his/her false identity, he/she goes on to take-over the customer’s personal assets such as his/her sim card or his bank account.

Stage 3 – “Swindling at once”

Having gained total control over the victim’s assets, the SIM SWAP fraudster now tries to extract monetary benefits from the victim’s assets at a single go. Here the victim is totally cut-off from his/her mobile network even without knowing it. By the time the victim gets to know that there are transactions carried out on his/her account without their knowledge, the damage is done!

Stage 4 – “Covering it up”

After having caused enough damage to the victim, the SIM SWAP fraudster lets go of the victim’s assets and goes on to hunt for another victim. The SIM SWAP fraudster makes sure that he/she makes enough improvisations to his/her fraudulent schemes so as not to appear like a serial offender, thereby leaving the law keeping forces with very little clue of the fraudster’s whereabouts!

SIM SWAP fraud, unlike many other telecom/bank frauds requires a joint effort from the customer, the bank and the telco. However, catching hold of the SIM SWAP fraudster doesn’t require the brains of Sherlock Holmes! Vigilance and a little proactiveness on how a fraudster might possibly behave can help catch them at a very early stage. To counter the ill-effects of the fraud, top Telecom Service providers like AT&T, T-Mobile, Verizon and other are harping on customer authentication through the 2-Factor method even during telephonic conversations.

However, I personally believe that not much is being done to study transactional pattern anomalies to identify potential fraudsters in the network and its high time bank authorities joined hands with telcos in countering the fraud. E.g. the telcos can notify the banks of change in a customer’s IMEI/MAC address/addition or modification of accounts/transactional abnormalities and then the banks can monitor the customer’s transactions for that week, in priority! Masking methods can be used during exchange of information to protect consumer interests. Telcos and banks can be more proactive by creating a database for reference where any changes made to the consumer’s profiles can be stored and looked up for instances of abnormal transactions. As preventative measures, customers can be advised by both the telcos and the banks to take enough care while sharing very personal and integral information such as card details, social security number etc. on social media or the public internet.  The SIM Swap fraud is known to cause serious collateral damage and reputational loss, however, a little care taken at the right point in time can work wonders!

To know more about how you can stay vigilant about SIM Swap fraud, view this video.

Artificial Intelligence and Machine Learning - the key to combating Identity Fraud

In an increasingly digitally connected world, identity fraud is a growing problem. According to the Communications Fraud Control Association’s (CFCA) annual fraud survey, identity fraud took the top spot as the number one fraud method present globally and at individual companies. Also featuring as the first among the top ten fraud methods, identity fraud in telecommunication during the subscription process (subscription fraud) resulted in costs of $2.03 billion.1

Identity theft, where the use of fabricated identities at point of sale, enables the fraudulent use of telecom services and/or perpetuates subsequent fraudulent activities, can result in serious implications in the present age. With highly interconnected 4G and soon to be launched 5G networks enabling not just value-added services but also financial services like mobile payments and banking, it opens up access like never before.  Identity theft can work as an entry point for myriad types of fraud or even terrorism. With access to secondary authorizations (PIN code verification), subscription fraud can be used for any number of illegal activities.

This has facilitated an urgent need for a proactive and dynamic response to fostering digital identity security.

Securing against Identity Fraud

The answer to fighting fraud lies in detecting data anomalies in real time. For example, to tackle telecom fraud, the Technology Research Institute (TRI) has stated that, real-time point-of-sale identity verification services are an invaluable aid to stopping fraudsters from exploiting identity theft.2 Historically, rules have always been in the system. But in the increasingly connected world, effective fraud coverage is only possible with a combination of rules and applied Artificial Intelligence (AI) and Machine Learning (ML) technologies.

With AI and ML technologies, companies are able to detect data anomalies in real-time and make decisions based on information as it happens, empowering them to anticipate and take proactive action. For instance, AI/ML techniques can use facial recognition technology to identify high risk by making checks against blacklists. ML can augment traditional rule-based systems to develop and train algorithms to determine the characteristics of traffic and identify anomalies that could end up being fraud.

Furthermore, the immense amounts of unsecured data flowing in from connected devices onto operator networks can be secured only with AI and ML. AI technologies are equipped with the capacity to scale up efforts and enable fraud detection at a massive scale by handling the management of millions of customer or network data points.

As networks continue to expand and new fraud schemes continue to evolve, a combination of rules and applied AI/ML models will serve as the most effective way in combating identity fraud.

If you are interested to learn how AI /ML techniques can help you combat Identity Fraud

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1 . https://v2.itweb.co.za/whitepaper/Amdocs_LINKED_2017_CFCA_Global_Fraud_Loss_Survey.pdf

2 . https://technology-research.com/products/fraudmgt/telecom_fraud_management_executive_summary.pdf?_sm_au_=iTHSrnwsn4HFwT3q

8 Simple Strategies for Telcos to counter Wangiri Fraud

Wangiri is not new rather; it is one of the most commonly occurring telecom fraud. In a recent case, a fraudster gave a missed call to several users of different countries. When the users viewed the missed call on their mobiles, they thought that it was a genuine missed call and called the number back. That is where they got tricked! The fraudulent numbers were unusually long and originated from an array of exotic countries. These were premium rated numbers so when the users called back, the fraudster’s intention to extract maximum payment out of them was successful.

In such scenarios, it is not just the subscribers but their operators as well who bear the losses. There is both a direct and an indirect loss for the operator. As per the latest CFCA 2017 global fraud loss survey, Telcos have lost close of 1 Billion USD to Wangiri Fraud alone, which is quite a lot!

In my point of view, Wangiri cannot be eliminated entirely for two main reasons- there is no proper regulation on the carrier business, and there is lack of visibility on the end carrier who is terminating the call. The end carrier who terminates a fraudulent missed call is not aware of the fraudster details and whether the country from which call has originated is a high-risk destination or not.

So, let’s look at how can telcos protect revenue and provide great customer experience?

  • Subscriber Awareness

A pro-active approach to minimize Wangiri fraud would be, making the consumers aware of the fraud scheme. If a number appears to be suspicious, a quick search of the number in several free apps available online, would tell the customer if the number is a part of any ongoing scams or not. Several Fraud Management tools are readily available in the market to detect and prevent Wangiri.

  • Customer Experience Management

As the customer is the king of any business, and hence Telcos need to manage the customer complaints effectively, which will, in turn, reduce customer churns. All employees in the customer care department should be well informed about the Wangiri fraud and how the customer care executives should manage the complaints related to this fraud.

  • IVR (Interactive Voice Response) Facility

IVR Facility is a pro-active approach that can be adopted by the operators. Whenever a subscriber calls back to a high-risk destination upon receiving a missed call, the operator should have an IVR voice informing him about his called destination. This IVR voice message would make the subscriber cautious to drop the call.

  • Removal of International Services as the default service for a Subscriber

In India, Telecom Regulatory Authority of India (TRAI) has announced a new mechanism to effectively protect the common interest of mobile subscribers. TRAI has said that international service calling facility should not be activated on prepaid SIM cards without the explicit approval of the consumer. This measure is yet to be adopted by several other regulatory bodies globally.

  • Technology

To protect customers from phone scams, T- mobile has introduced a new network technology. They have rolled out a scam ID by which customers are automatically alerted when an incoming call is likely a scam.

Several other vendors are also coming out with similar technological solutions.

  • Routing Management of carrier:

When a fraudster carries out the Wangiri fraud and gives missed calls to multiple subscribers, high amount of increased traffic can be observed on the carrier who routes these calls. If an operator monitors this activity, there will be a repetitive trend of increased traffic observed on the same carrier to route these calls. In such cases, an operator must take necessary precautions to route all the traffic through an alternative carrier. Routing the calls through a different carrier will help in breaking the chain between the fraudster and the linked carrier.

  • Control designing through FMS tool:

Control designing through an FMS tool is required as it helps in early detection of Wangiri activity. An FMS tool assists in the discovery of Wangiri cases by monitoring the number of calls made by the fraudster. Artificial Intelligence & Machine Learning can play a significant role in detecting the Wangiri fraud.

  • Negative Margin Prevention

In case of a negative margin occurrence, the number needs to be blocked by the operator immediately as it leads to direct impact in the revenue.

I would conclude by saying the famous quote by Bill Gates, “Treatment without prevention is simply unsustainable”- though Wangiri fraud can never end completely, right preventive measures can minimize it significantly.

If you are interested to learn how AI /ML techniques can help you combat Wangiri Fraud

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Account Takeover – Fraudster Intelligence

Account takeover fraud is one of the most common fraud types across the world. Fraudsters use the various methods to takeover an existing open account within the mobile operator or the banking instrument. The commonly used method of committing this type of fraud is vishing or smishing. As per CFCA fraud survey, account takeover accounted for an estimated fraud loss of 1.7 Billion US Dollars in the year 2017.

In all these scenarios, the primary goals of the fraudster are to gain access to the account and (by-) pass the validation steps. In many situations, such validation may only require low-level knowledge-based authentication, so basic information obtained by the fraudster is used to validate and by-pass controls in place and to takeover the targeted account.

I was investigating an Account takeover fraud case for one of the leading telecom operator in the APAC region wherein the fraudster used a different type of methods to commit this fraud. Many customers lost millions of dollars from their bank accounts without the knowledge after their account was taken over by the fraudster. On investigation, we identified that the fraudster’s primary motive was to takeover both mobile and banking account and then initiate multiple fraud transactions. He used Social Engineering, CLI spoofing, Spoofed website & Malware to commit the fraud.

The Fraudster sequentially executed his schemes. He targeted only the high-profile subscribers in a region. He acquired all the information of the subscribers using social engineering methodology and called up the subscribers pretending to be a Bank executive and Mobile operator security officer. He asked the subscribers to download a malware-infested application from a spoofed website, following which he gained remote access to their mobile phones.

The malware would read the SMS’s & call logs from the subscriber’s mobile and forward the details to fraudulent server. It also deleted the SMS & call logs from the mobile handset before the subscriber knew the same. The intention behind the reading of the SMS & Call log is to Bypass the second level authentication for completing the banking transactions. With this method in place, he was able the execute multiple transactions without the knowledge of the subscribers.

Impact to Telcos?

When subscribers approached law enforcement agency, the Law penalized both Telco and the bank and recovered from them, the amount lost by the subscriber. The Law took this action to protect the interest of the customers and secondly it was negligence from the service provider that led to the revenue losses of the subscribers.

Telecom & banking service need to protect the subscribers from such fraud attacks by providing awareness to subscribers. Fraud management systems need have intelligence built into them to detect the fraud attack and control damages at an early stage.

Dealing with Bypass Fraud : Think beyond the boundaries

Amid the fierce competition facing the telecom industry, sometimes we listen to stories how lack of forethought of one Telco brings on illegal traffic on the network, leading to aggressive open wars and blame games among the operators affected by the fraud. The Telecom Regulatory Authority could intervene in such scenarios and encourage a competitor to block suspicious outgoing traffic if it finds out that not enough care is being taken to avert the fraud.

Interconnect Bypass fraud is one such telecom scam costing the industry several billion dollars every year. It brings collateral damage to the networks involved, and the impact will be huge. The Telco could be imposed hefty penalty for its failure to detect and resolve the issue on time. Further, it could bring serious business implications for all participating telcos. In the process of rampant blocking of suspicious traffic, sometimes traffic of genuine customers could get blocked, leading to customer dissonance and dissatisfaction along with loss of other business opportunities.

Here’s an example of a West African Telco who suffered massively due to Bypass fraud.

Why did this happen?

The West African telecom operator had been massively impacted by off-net Bypass fraud where the network of the operator was being misused to land fraudulent calls on the competitor’s network. Over time, the problem became so grave that the Regulatory Authority of the country had to step in and take charge of things. This eventually ended with the competitors blocking both fraudulent and genuine traffic from the Telco affected by the interconnection fraud.

Investigations conducted confirmed that the huge differences between the International termination rates and local termination rates made the environment suitable for fraudsters to run their schemes. There aren’t enough KYC controls in the country to facilitate certain onboarding checks which distinguish a genuine customer from a fraudulent one.

Impact on business

There were multiple warnings and memos issued to the operator from the Regulator, indicating that the operator would have to face penalties if amendments are not made in time.

Customers flooded the operator with complaints saying that their off-net calls were being barred without prior notice and for no fault of theirs and threatened that they would eventually churn out of the network if their services weren’t restored.

The atmosphere grew so tense that instead of cooperating, the operators became more aggressive and indulged in a rat-race in trying to prove a point to the Regulator as to how better and efficient they were from the rivals in terms of detecting Bypass fraud cases.

The solution

With the understanding that Bypass scams are rampant, Telcos need to direct their efforts towards building knowledge-sharing forums where they can share insights on fraudster behavior and geographical locations from where most of the fraudulent calls are generated and what kind of products tend to get misused by these fraudsters to nip things in the bud.

Telcos should understand that indulging in rat race or blaming each other will not help solve issues arising from such frauds; rather they should adopt a proactive approach to identify and prevent such scenarios in future. Instead of the Regulatory authority dictating terms to the operators, the operators must drive the authority to create nationalized framework for user identity governance.

Why Artificial Intelligence Powered Fraud Management

Artificial Intelligence (AI) is not new and it has been around for decades. However, with the advent of big data and distributed computing that is available today, it is possible to realize the true potential of AI. From what started as an interesting story line in SCI-FI movies to programs like Alpha-Go which has been beating humans, AI has been evolving. AI also has branched out into multiple sub categories such as Machine Learning, Deep Learning, Re-enforcement learning etc.
FM-1

FM-2
An effective Fraud Management (FM) strategy includes 3 important pillars: Detect, Investigate & Protect. We believe AI can positively influence all the 3 pillars of fraud management, from reducing false positives to helping in mining root cause analysis to creating enhanced customer experience in protection.

In this post I would like to look at the starting pillar of the Fraud Management strategy – “Detection” and look at AI’s influence in this very important step. A traditional approach to Fraud detection has been through Rule Engines which could be:

  • If-Else Conditions
  • Thresholds
  • Expressions
  • Evaluating Data Patterns
These are widely known as deterministic solutions where an event triggers an action. The biggest pros and cons with this approach is that human intervention is needed to feed the logic.

For eg: for a threshold based detection humans have to feed the rule engine that count of records above a certain threshold is suspicious.

Following diagrams shows how this looks like

rule-engine

After looking at the diagram above an important question arises, should this threshold value be a straight line or can it bend based on how data behaves. Now there are ways for rule engine to behave like mentioned in the diagram,

variable-threshold

for eg, instead of having a single rule lets have multiple rules

  • Per Customer Category
  • Per Destination
  • Per Age of Customers

And multiply that with other dimensions in data which are

  • Phone Number
  • Caller Number
  • Called Number
  • Country Code

And multiple that with other set of measures per dimensions

  • Count
  • Duration
  • Value

And throw an additional billion volumes at the datasets

Quickly FM teams ends up with something like this
AI Blog1
But what they wanted or dreamt was this
AI Blog2

Now I am not saying FM teams are not skilled enough to fly, but a fraud team in a modern Digital Service provider should be more focused on other important factors.

machine-learning
So, let’s look at how a very evolved class of Artificial Intelligence known as Machine Learning looks at this problem statement. Rather than humans feeding domain information or thresholds, Machine Learning Algorithms mine data from historic fraudulent behaviors and create models. These models are then used to evaluate real production datasets to score whether they certain activity is fraud or not. An advantage is that these models are very good at looking the datasets from multiple dimensions and measures at the same time and concluding whether event is fraud or not.

This approach thereby helps in achieving multiple KPI’s of fraud management teams there by increasing efficiency.

  • Higher Accuracy – Because AI can learn and adapt to Business scenarios faster, AI can significantly increase True Positive ratio
  • Reduced time to detect – How fast a fraud event can be detected
  • Self-Learning – How over a period changing business scenarios and seasonality in data can be adopted to Fraud detection
  • Fraud Intelligence– How customer or any other entity behaviors can be learnt and categorized for better fraud detection
  • Proactiveness – Ability to mine for unknown patterns not seen in the data earlier
FM-4

Application of Artificial Intelligence has its own significant challenges and requires a new frame of thought, however looking at the Data Tsunami that has hit the fraud management teams, it looks an AI pro approach would only help Fraud Management teams to scale further.

Why SIM Box Fraud is Rampant in Africa?

The second fastest-growing continent after China, Africa owes much of its recent economic growth to the use of telecommunications services. However, over the past few years, telcos in Africa have been hit by several telecom frauds. SIM box fraud, also known as the interconnect bypass fraud, is one of the major frauds affecting the dynamic telecom market in Africa. The impact is huge in terms of the loss in revenues to telcos and taxes to the government. It is estimated that Africa loses up to 150 million US dollars every year to interconnection frauds. Reports suggest that two years back SIM box fraud had brought in losses of 12 to 15 million minutes’ worth of revenue to Kenyan government and operators, and about US$5.8 million to Ghana government.

Why SIM Box Frauds Target Africa?

  • As per the industry reports, mobile subscriber growth in Africa is largely driven by the lower call prices and availability of cheaper handsets. The competition arising from over-the-top (OTT) providers has put an additional pricing pressure on telcos, forcing them to design new bundled offerings encompassing data, voice and SMS. Such bundles bring much lower per-minute revenue for the operators as compared to traditional services. Fraudsters operating the SIM boxes are taking advantage of this scenario to bypass the formal call termination systems that fetch higher tariffs to telcos.  The calls routed through the IP networks are terminated using local SIM gateways, thus compromising the formal interconnection networks and bringing heavy losses to the telcos who have invested in building the networks. Traditionally, African countries are known to have higher interconnection tariffs compared to other regions, which further explains why such frauds are prevailing in Africa.

 

  • If I were to look at data from google trends, one can also make out that Ghana in Africa seems quite buzzy about “Simbox Fraud” as a term to be searched on Google (till Nov, 2017)

 

simbox-fraud1

 

 

  • Technological advancements have also contributed for the rise in interconnection frauds. The growing sophistication around SIM box technologies has made fraud detection difficult using traditional methodologies. SIM boxes are programmed to mimic the activities of a normal call user. The equipment can have SIM cards of different operators installed, so a single SIM box can operate with several GSM gateways located in different parts of the world. The availability of SIM cards at cheaper prices and the lack of law enforcement over the sale of prepaid SIM cards have also favored the growth of SIM box fraud, further.

 

  • Globally, the difference in approaches adopted by different countries to deal with the fraud makes it difficult for operators to develop a unified strategy to fight these frauds. IP interconnection services are treated as legal in a few countries whereas they are banned in other countries due to the regulatory issues associated with such activities. For example, the Ghanaian government has declared SIM boxes illegal and made several arrests in this regard. However, SIM boxes are now available in several open markets including popular e-commerce platforms for around $1000 per unit. To make the matter worse, OTT providers like Viber are now explicitly selling their call termination capabilities to lure roaming customers to such bypass activities. Another such OTT development I recently noticed is Skype offering Free calls to mobiles and landlines in the United States and Canada from India These evolving trends convey the scale at which the SIM fraud is growing, calling for immediate action from telcos to safeguard their revenue streams.

Unified approach for addressing Sim-box fraud:

To conclude, the recent developments around SIM box fraud have further aggravated the challenges faced by African telcos. With no scope for regulatory remediation, the only way forward for them is to prevent these attacks using advanced technologies. Traditional approaches like Call Detail Record (CDR) analysis are becoming ineffective in dealing with modern SIM box strategies due to the latency and false positives associated with those methods. As the market evolves, operators are looking toward a unified approach that can help them address the crisis in a much proactive manner. The developments around machine learning and test call group (TCG) analysis have favored the growth of an integrated solution that can help telcos combat the fraud in a cost-effective manner. The approach builds the capabilities of the traditional models but integrates the advancements in artificial intelligence and self-learning rules.

Watch this space for more updates on SIM box fraud management with cognitive analytics capabilities.

Why Telcos could never overcome Simbox Fraud since a decade Now

Simbox, Bypass Fraud/ Or Interconnect bypass Fraud has been one of the fastest growing Fraud Types In recent few years.  As per 2017 Global Fraud Loss Survey by CFCA, Global Fraud Loss Estimate stands at $29.2 Billion (USD) annually which is 1.27% of global telecom revenues.

global bypass

Source CFCA Survey Results

Simbox Fraud / Bypass Fraud has been a significant fraud issue for more than a decade now. CFCA survey results across 2009 till 2017 clearly shows an increase of more than 100%  in Bypass fraud since 2013. In this blog, we shall discuss about factors that has contributed to this continuous increase in Bypass Fraud and reasons, operators have not been able to effectively mitigate Bypass Fraud.

Factors for continuous Increase in Bypass / Simbox Fraud:

  • Reduced barrier for entry

Buying and operating SIMBoxs has never been easier with online stores, e-commerce websites,courses, forums and instant support availability.  This has led to an increased spread of VOIP based startups and subsequent increase in bypass fraud. VOIP based calling apps have also made customer acquisition easy by making them  easily available on  AppStore for Android & IOS users. For instance, a recent news from India covered the similar trend wherein those who wanted to make international calls from Gulf countries has to download an app called ‘dial to India’ Once this app is downloaded, they get a password for monthly subscriptions. The person sitting abroad will just dial the number in India, the call will bypass the VSNL gate and will directly route through the SIM box and will get connected from there. Read More

Few more such examples as below:

Illegal phone exchanges thriving on SIM boxes

VOIP exchanges used by ISI busted in Andhra Pradesh, India

  • Competitive Landscape

Reduced margins on international traffic has resulted in wholesale traffic being mixed with internal traffic. Wholesale providers have also been increasingly offering non-CLI based options which could potentially end up in Grey routes. This fierce competition had led to increase in bypass traffic particularly in countries with higher landing costs.

Reasons Operators have not been able to effectively mitigate Bypass Fraud:

  • Advancement in Sim-server Technology

Simbox have evolved from being a simple single box setup to a complex modular architecture. This architecture allows fraudsters to maintain all the simcards in a single place and using Antenna modules and multiplexers, fraudsters are able to distribute their operations in the market. In fact, Latest Simservers also comes with inbuilt anti-fraud detection solutions allowing fraudsters to  distribute his operations in multiple locations. This makes fraud detection very complex as fraud management teams have to device multiple strategies to beat fraudsters at their game.

  • Regulatory Changes

Regulatory changes in certain markets have fueled increase in traffic for Bypass. Recent changes of regulations in European Union has also resulted in traffic with E.U been heavily being differentiated in price from traffic outside E.U thereby causing significant increase in Bypass traffic.

  • Raising Concerns in Simcard Sales

Increased pressure to maintain sales and activation of new connections have resulted in dealers colluding with Bypass fraudsters. Bypass operations requires lot of sims to be activated in bulk and lack of effective subscriber acquisition controls have led to fraudsters taking advantage of it.

Fraud Management teams further have an uphill task in the Bypass fraud space as new technologies such as virtual sim’s would only increase the impacts on bypass of international traffic. It is hence important that they adopt a comprehensive fraud detection methodology to fight simbox frauds.

Device Journey Management: the next frontier for Device Assurance

In recent years operators have scaled their thinking into hundreds of millions – but not in terms of data volumes, but instead in the numbers of devices now utilizing their networks.  Smart handsets have led the charge of devices, followed (and soon to be surpassed) by IoT devices, and an army of small cells that will serve to densify the upcoming 5G network rollouts around the world.

Why are these devices capturing more and more operator attention?  With over 1.5 billion smart phones shipped from manufacturers in 2017, the amount of investment by telecom operators just in this device category alone amounts to approximately 20% of their overall operational budget.  However, each year tens of millions of dollars of this opex are being written off as losses by operators due to issues with logistics (forward and reverse), fraud, and process misalignments; device journey oversight doesn’t exist as a discipline today.

Subex has invested almost two years researching this domain, including talking with operators of all sizes around the world.  What we have found is an expanding set of exploitable gaps that current systems and practices are incapable of closing.  Points of risk exist across internal processes, channel partners, distribution and supply chain, and various other areas leading to (and sometimes even originating from) the end consumers.  These risk points accumulate losses for operators that range between $500K USD to over $10M USD per month, per operator, depending on size of the operator.

The device growth area today is not only in smart handsets, but also in a wide array of small cells, sensors, and various other categories.  With already significant gaps existing in oversight, this new breed of devices puts an even greater risk on operating budgets.  Under current estimates, deployed IoT devices alone in the next 5 years will exceed 200 billion units, dwarfing the handset counts worldwide.  Can losses be sustained, or even ignored, at these levels?

Subex will be speaking about a comprehensive strategy and methodology for Device Journey Management during a presentation at the CFCA Winter Conference in Las Vegas on February 6th, 2018.  We will also be at the Mobile World Congress in Barcelona later in February where we look forward to speaking with operators encountering the same problems.

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