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Tag Archives: Fraud

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

Fraud Management

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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

DOWNLOAD WEBINAR RECORDING NOW!

 

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

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

5 Key Reasons Why Telcos Should Turn to Digital Methods to Combat Fraud

Fraud Management, General

Telcos are losing millions of dollars every year to frauds. Of late, we see that fraudsters have become smarter and the tactics used by them have evolved into a more sophisticated level aided by the smart technologies. Further, with digital services entering the new mix of offerings, traditional strategies no longer fit the bill. Digital services, especially those offered on IP networks, are more susceptible to attacks as evident from the recent hike in SIP-based attacks.

The growing complexity in the digital services ecosystem demands a future-proof approach to secure the networks and prevent revenue losses.

Let’s look at the top five reasons why you should invest in digital fraud prevention technologies.

  1. Proactive versus Reactive

Traditional fraud management systems are post facto; they rely on transaction records such as CDRs, payment vouchers, provisioning details, etc., which are generated post an event. Hence, fraud teams can never get ahead of an attack and can only react to it. However, with digital methods, the network is monitored in near real time and fraud teams can tear down a call and prevent frauds before they occur.

  1. Increased coverage to prevent frauds

SIP attacks are inherently complex; they range from Layer 3 based IP attacks, all the way to Layer 7 based SIP protocol attacks. All of the Layer 3 attack reconnaissance need not translate to a breach, but by keeping track of the origination of these attempts and then correlating it to high-risk behavior at the higher network layers, modern digital fraud prevention techniques can automatically prevent such attacks.

  1. Combat Zero-Day Threats

Of late, fraudsters are increasingly exploiting the vulnerabilities in fraud detection mechanisms and duping the system with malicious inputs. To avert such frauds, you need to employ an intelligent system that can detect such attacks in real time and prevent them before they impact the customers. With advanced Machine Learning (ML), you can create a defense against such attacks and future-proof the algorithm.

  1. Scenario Planning

Security and Fraud is an afterthought while new digital products are launched by telcos as the focus is initially on product functionality and the rush to go to market. This makes new digital services highly susceptible to attacks and breaches which are more often than not exploited very quickly by fraudsters. It is important that new digital services are put through vulnerability assessments and scenario planning so that obvious holes are plugged, and then continuous monitoring is put in place to detect any new threats to ensure profitability and prevent revenue leakages from fraud.

  1. Future Proofing to address the complex scenarios

As the digital framework grows complex, threat management becomes even more challenging.  With advanced ML capabilities, the new threat management systems allow you to gather threat intelligence from across the globe covering a wide range of digital products. This will help you identify new trends and malicious patterns. Further, it also gives insights on the specific tools and tactics employed by hackers, so you can bolster the system well in advance.

Stay tuned to get more updates from Subex.

To know more about our Digital Fraud prevention Solution Click here !

Selling devices – A boon or bane for Telcos?

Fraud Management, General, Revenue Assurance

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Smartphone flashes in mind, when device is mentioned.  Devices, however, are a large ecosystem beyond smartphones – a range of equipment like dongles, routers, customer premise equipment (CPE) and IP phones, to name a few.  Devices are a great tool for telco to lock their customers in. For instance, the bundled offers with contracts spanning months provide predictable revenues for the telco’s.

The next wave of opportunity

With IoT and 5G making inroads, telco’s are preparing for the next-generation devices for home and office networks. A lucrative opportunity for telcos, as devices are critical to the IoT/5G penetration. Newer devices will be introduced, like small cells to boost network capacity and improve indoor coverage. It’s no wonder that telcos are investing into devices.

Are telcos benefiting from devices ?

Devices are an attractive opportunity as they improve customer stickiness and ARPU. Devices are good promotional tools to attract new customers and gaining traction even in emerging economies. Many customers extend their relationship with telcos beyond contract period.

Yet, procuring, selling and managing devices is riddled with risks. Fraud, leakages and unmanageable debt are hampering the revenues and profits.

A survey across telco’s states:

telcos stats

What are the risks?

Telco’s on an average spends 20% of their OPEX on procuring and servicing devices. The entire supply chain covering the forward and reverse logistics is prone to risks. The supply chain not only involves stakeholders within the telco (marketing, sales, operations, logistics, finance), but many external parties –manufacturer, supplier, financing partner, distributor, shipping partner, warehousing network, retail agents, repair/refurbish partner, and the end-customer.

risk

The technology stack is complex with at least 10 different applications and platforms involved. Leakages of stock in ordered vs received, inventory gaps, devices ageing at inventory, gaps at POS are a few technological risks to highlight.

Bane to boon – Manage the risks

How could telco’s control the risks & leakages, and make the best of the opportunity? It is important that Telcos have Device Assurance strategy in place to manage the device related risks. Stay tuned for more updates about Device Assurance Solution.

Cash in on Reverse Logistics

General

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Reverse logistics has long been the problem child of supply chain management. Increasingly that child has been in need of some serious help. This is due to two factors. The way in which the internet has transformed how we shop, and the short lifecycle of consumer goods. Although most consumers still like to shop in high street stores to find the products they like, at least 8% of sales are now from consumers just clicking on a picture to buy a product, comfortable in the knowledge that they can return it if necessary. In most countries, consumers have a legal right to return goods purchased on the internet. Many retailers now even offer free ‘try-before-you-buy’ returns, but the processes for managing those returns, known as reverse logistics, are far more fragile, costly, and susceptible to issues than the generally well-controlled forward logistics processes. Although return rates vary widely across different verticals, the average return rate has been calculated to be around 17 to 18%.

Brightpearl

Source: Brightpearl

Reverse logistics faces complex issues due to the ad hoc way in which consumers return items and vulnerabilities in the returns processes. Because reverse logistics is not seen as a revenue-generating process, it sometimes doesn’t get the attention it needs, but recently it’s been getting more widely recognized as having a key role in the company’s profitability. Having efficient processes for collecting, re-selling or recycling used items can bring in additional revenue and improve a company’s bottom line. There are other important reasons for giving more attention to reverse logistics.  Consumers are now judging companies on their green credentials, and consumers are aware that many electronic devices contain some highly toxic chemicals. Providing a channel through which old devices can be traded in and reliably recycled is a positive selling point. The efficiency of the returns process also has a significant impact on customers impression of a business.

Although the ‘returns revolution’ impacts all retail lines of business, high-value consumer electronics are especially prone to issues in the returns process.  Huge volumes of handsets, set-top boxes, routers, even TV’s and laptops, are now being returned through a multitude of channels for a variety of reasons. Warehouses may receive thousands of such goods per week. Most of those devices may still be working and able to be resold, but tracking such devices back from customers, assessing their viability for resale, refurbishing, repackaging, and then re-distributing them, is a substantial challenge.

The problems begin as soon as a customer says they want to return a device. Whether it is because the device is faulty, unfit, incorrect, unwanted, or because they’re terminating their contract, they must provide notification that the device is getting returned. Agents must correctly capture the details of why the device is getting returned and issue an RMA (Return Merchandise Authorisation). This will trigger a complex sequence of processes to terminate services in the network, calculate bill adjustments, prepare downstream systems for receipt of the returned devices, update inventories on receipt, manage the inspection, refurbishment, and resale of those devices, and potentially issue replacements for faulty devices. Depending on factors such as contract, warranty, device status, termination type or customer rating, customers may be liable for additional charges or eligible for compensation.
Reverse Logistics

Typical return channels would be to send a device by courier, return it to a shop, or a technician may return the goods.  Whatever the channel is, devices will often arrive without a clear indication of which customer account they relate to.  Returns to stores are particularly problematic with agents failing to scan in barcodes or register returns correctly. In-store systems may not be able to record IMEI, IMSI and/or serial numbers, and there is no motivation for staff to label returned devices accurately.

With so many moving parts it’s no surprise that many devices become stranded or lost along the way, and customers getting charged incorrectly. Operators have been known to write off more than $5+ million in lost devices per month.

One solution is to implement automated controls that provide monitoring across all systems in both forward and reverse logistics, thus assuring that devices can be monitored from the initial order in CRM, in and out of warehouses, with couriers, shipping, refurbishment partners, finance companies and activation status in network service provisioning.  With monitoring systems in place that can even detect the physical location where devices are installed, it’s possible to validate inventory, bill customers and partners accurately, prevent fraud, recover maximum value from returned devices and understand why devices are getting returned.

Subex provides ROC Device Assurance solutions to operators around the globe, helping to track down missing devices, reconcile and correct billing, CRM, provisioning, distribution and inventory systems with world leading discovery and reconciliation capabilities.

8 Simple Strategies for Telcos to counter Wangiri Fraud

Fraud Management

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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.

Account Takeover – Fraudster Intelligence

Fraud Management, General

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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

Fraud Management

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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

Fraud Management

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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.

GDPR – A New Road to Trust

Digital, Fraud Management, General, Regulations

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As the May 25th deadline for the European General Data Protection Regulation (GDPR) looms closer many organisations still haven’t made the internal changes required by the new law.  For those who haven’t yet faced up to the impact of GDPR, a good starting point is to understand how the 7 Principles of this new regulation affect their business.  The challenge many have found is that there is not ‘one size fits all’ when it comes to GDPR.  Every organisation will have different requirements.  That’s why it’s recommended that organisations urgently carry out a self-assessment to gauge their own level of compliance, which considers their own unique circumstances.  Here are some of the questions organisations should ask themselves:

  1. Has all the personal data being held, where it comes from, how it’s processed and who it has shared with been documented?
  2. Are lines of accountability clearly documented should there be a data breach?
  3. Has a lawful basis for the processing been identified and documented? If not then has consent been obtained from the data subjects?
  4. Is there a process to securely dispose of personal data that’s no longer required?
  5. Do staff receive data protection awareness training, and do they know what processes to follow to identify, report and resolve data breaches?
  6. Do we carry out internal audits to monitor our own compliance with data protection principles?
  7. Have appropriate technical and organisational measures to protect data during processing been implemented?
  8. Do key people in the organisation demonstrate support for data protection?
  9. Can we respond to a data subjects request to see the personal data we hold about them?

The ICO, the UK’s supervisory authority, are providing assistance by making a self-assessment tool available on their website.  This can help both data controllers and processors to identify compliance gaps and provides recommended actions.  After carrying out a self-assessment, organisations need to draw up a plan for tackling the compliance gaps identified.  As can be seen from the above questions, high on the list of priorities is documentation. Documentation needs to exist that details the processes and policies to be followed, and as evidence that those processes are being followed.   This is because, in the event of a data breach, auditors from the supervisory authority will be looking for documentary evidence that shows how organisation has tried to comply with GDPR.  Such evidence could significantly reduce the likely penalties.  The level of detail required will depend largely on the sensitivity of the personal data held, and likely risk of a breach.  For example, in the case of highly sensitive data, a full Data Protection impact assessment should be carried out to understand and mitigate the risks.  If companies are diligent in their efforts to protect personal data, and thereby protect the customers themselves, then Elizabeth Denham, head of the ICO, has some comforting words.

‘You will know by now that, while I am never afraid to use the stick in the cupboard, I prefer the carrot.

Education, engagement, encouragement, – they all come before enforcement.

I have said many times that we are a pragmatic regulator and that hefty fines will be reserved for those who wilfully or persistently flout the law.’

GDPR is challenging companies to put their data protection house in order, but the benefit of GDPR is that it forces companies to better understand their own processes and improve internal governance.  This can lead to greater efficiencies and transparency, which can ultimately help to restore trust in big corporations that has steadily been eroded by every new revelation about misconduct and abuse of power, not to mention poor customer service.  Organisations that are looking for ways to avoid GDPR should instead start embracing it as a way to restore customers trust.

Why SIM Box Fraud is Rampant in Africa?

Digital, Fraud Management

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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.

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