Our CPO, Janer Gorohhov, discusses Veriff’s Fraud Report 2020

When discussing identity fraud it’s easy to assume that its origins lie in the information age, when software first enabled fraudsters to commit digital theft – but that’s not the case. Identity theft dates way back to the pre-digital age and can be categorized as any record of someone stealing personal information with the aim of committing fraud. Take for example US election fraud during the 1800s, when the paper ballot system replaced voice votes and enabled cooping. 

Today, personal data is everywhere and the sheer volume of user-generated Internet data grows exponentially each day. Despite the enormous levels of risk at play, we use the Internet more than ever before; we do everything online, from taxes to investing to health care. Over the past two years alone, we’ve generated 90% of the world’s online data. As engagement climbs and digital footprints grow, the increasingly valuable concept of one’s digital identity, and the wealth of aforementioned precious information, become more and more available and prized to bad actors. 

Fraudsters use the identities of others to violate the law by stealing money, obtaining loans and trading data in a way that their typical victim doesn't notice until the damage is already done. Criminals can use various techniques to obtain personal data such as phishing, malware, social engineering and other tactics you can read about in our blog. 

Last year, 20.3% of all FTC complaints were reports of identity theft. Of the 3.2 million reports received by the Consumer Sentinel Network, 1.7 million were fraud related and over 650,000 were identity theft complaints with a reported loss of $1.9 billion––an increase of $293 million from 2018. Additionally,  according to Statista, the risk of identity theft has increased significantly since the coronavirus outbreak began and is expected to increase even more in the coming months. 

2020 was an unpredictable year, and equally as wild for our personal lives as it was for digital fraud rates and fintech adoption. For some companies, and even industries, identity verification went from a ‘nice to have’ to a ‘need to have’ in a matter of days. At Veriff we protect companies from a wide range of attacks using some of the most robust tech in the industry, and here are some unique insights we found in the three industries we work with the most: crypto, fintech and mobility. 

As a leader in eKYC and digital ID verification, Veriff analyzed millions of verification sessions and data points from across the globe to ascertain the most prominent trends of 2020. Fraud is on the rise – which isn’t surprising, considering that the majority of businesses have moved online due to the Coronavirus pandemic. Thus, it’s more crucial than ever to be sure your customers are who they’re claiming to be.

A global view: The United States has the highest fraud rate in the world, nearing 10% and followed by Vietnam (9.3%) and Nigeria (5.9%).

Pandemic-induced fraud: Due to increased online activities as a result of the pandemic, there was a >3x increase in overall fraud rates in the fintech and mobility sectors this year. The crypto sector remained high, but was more stable with no drastic spikes.

Most common document fraud: When looking at the document types that fraudsters use most often in attempts to steal, falsify or illegally verify an identity Veriff saw that over half use an ID card (51%) followed by a driver’s license (27.4%) and a passport (19.1%).

Industry differentiators: The mobility industry saw a 16% jump in fraud rates from H1 2020 to H2. Similarly, the fintech industry experienced a 7% increase and cryptocurrency saw an 11% jump.

Identity fraud rises: Identity fraud is the second most prevalent type of fraud in crypto (40%) and the most common type in fintech (70%). After comparing H1 2020 to H2, Veriff saw an 11% increase in fraud rates.

Online fraud is the use of web services to defraud people or otherwise take advantage of them. Some of the most common types of online fraud specifically include new account fraud and account takeover. In cases of new account fraud, many times bad actors will create “synthetic identities” (fake identities created using real information, like social security numbers) to start using online services. These identities can incorporate a mix of real and fake information, data stolen from honest people, falsified documents, modified real data and/or fully fraudulent identities purchased on the dark web. In cases of account takeover, criminals get access to people’s existing accounts and start doing online transactions on their behalf. 

A growing phenomena in online fraud is deepfakes: synthetic media whereby an image or video of a person is replaced with the likeness of someone else. Veriff encounters deepfakes on a daily basis as fraudsters try to fool the system and get through our verification flow while pretending to be someone they are not. Luckily the technology we use at Veriff is much more sophisticated and does not rely solely on biometrics; we combine many different data points when detecting fraud. 

The 2020 Coronavirus pandemic led to a huge rise in the adoption of digital solutions, changing the way that many industries operate – and the ensuing lockdowns led to a massive increase in online activity, with fraud rates following suit. Arkose Labs’ Q4 2020 Fraud and Abuse Report reveals that attack volumes doubled (as compared to H2 2019, leading to a 25% attack rate increase across all transactions). 

Veriff saw fintech fraud more than triple in spring ‘20 during the initial COVID outbreak, reaching over 5% at times as people moved their banking online (see Graph 1).  

Mobility fraud exhibited a sharp increase, starting in September (see Graph 2) as more mobility service providers launched and people began relying on safer alternatives to public transportation such as scooters, mopeds and cars. 

Crypto fraud rates are the highest of these three sectors numerically (see Graph 3), but Veriff did not witness any extraordinary jumps during the year such as with fintech and mobility. 

Veriff can verify identities from almost anywhere in the world, covering more than 190 countries and territories. When looking at where we see the most online identity fraud attempts globally, the United States (see Graph 4) is the leading country with close to a 10% fraud rate (meaning 10% of all verifications submitted were fraudulent). 

Graph 4 - Top 5 Most Fraudulent Countries in 2020

Here’s a real fraud story from the US that we came across at Veriff: 

“We noticed abnormal traffic associated with a car dealership located in the US. In addition to the store’s employees opening crypto accounts and verifying themselves at the spot in the shop, it seemed like shop’s customers were also asked to pose with their documents as a part of the ‘store procedure'. Some of the sessions were guided by what we think was an employee of the shop, some were carried out independently by customers sitting in cars. Unfortunately, this didn't lead anyone to getting a good discount at the car dealership, but a free crypto account was created on their behalf without their knowledge.”

People use different types of documents when verifying themselves and Veriff supports close to 9,000 different government issued IDs. When looking at the document types that fraudsters use most often in attempts to commit fraud, we see that over half of them opt for an ID card (see Graph 5).  

One reason for this trend is standardization. Passports, for example, exhibit similar quality and security standards globally whereas the appearance and nature of ID cards differs widely by region. In other words, creating a fake Estonian passport for online identity verification purposes would be around the same level of difficulty as creating a Venezuelan passport. However, when looking at ID cards, a Venezuelan ID card is much easier to fake than an Estonian ID card.

Globally, the documents that we decline most often due to suspected tampering are Vietnamese ID cards (13% fraud rate) followed by the U.K. drivers license with 8% (see Graph 6).

Graph 6 - Top 5 Documents Declined as Suspected of Fraud in 2020 

When analyzing American fraud trends, the most common document type presented by fraudsters is the US passport (see Graph 7). Thus it is also the most declined document type (due to suspected tampering). 

Graph 7 - Top 5 US Documents Used by Fraudsters in 2020 

In autumn, Veriff launched a barcode scanning feature that enables businesses  to extract document data automatically, leading to a higher rate of more accurate data extraction. PDF417 barcodes are a standard feature on the back side of all United States and Canadian driver's licenses, making Veriff’s scanner a secure and reliable way to catch instances of document tampering.

Identity Fraud Trends in Different Industries

The identity fraud that Veriff tackles on a daily basis can be divided into four types.

Fraud types vary dramatically by industry. Let's take a look at each of our core markets in more detail.

As mentioned in our Crypto Fraud Report, the cryptocurrency market exhibits the highest fraud rates when compared to the other industries that Veriff works with. In fact, this trend has remained stable since 2019 when we wrote our first fraud report.

 “The biggest value that Veriff brings us is the KYC and compliance, where we’re removing a lot of the bad actors and stolen IDs. With velocity abuse, where when someone has stolen loads of IDs and they’re trying to sign up, Veriff helps us detect where they’re coming from and recognizes the repeat use of a device. The benefits of the combination of these tools allows us to reduce the fraud rate and meet our compliance regulations as well.” – Chris Adjei-Ampofo, CIO, Uphold

This year, recurring fraud accounted for over 50% of fraud attempts in crypto – making it by far the most prevalent type. 

Recurring fraud breaks down into two types, one of which is basic ‘recurring’ fraud, where a fraudster has been successful and comes back to try again. The other is velocity abuse, where after getting approved once fraudsters try to abuse the system and get approved as many times as possible, normally verifying different real users without telling them what they’re being verified for. Fraudsters tend to go as far as creating synthetic identities, where they try to create a new identity by combining their real information in conjunction with fake data.  

Identity fraud is the second most prevalent type of fraud in crypto. This is more familiar to a wide audience, seeing attackers attempt to impersonate legitimate users with the assistance of fake data.

Here’s a true fraud story we came across from Italy. 

Forging a photo on the document is one thing, but forging the person presenting this document is a whole other story! A guy from Italy has printed out the document with a nicely crafted face on it, and in addition to it he designed a life-like mask matching the identity on the document he was showing. If only he knew we were able to see him ‘changing faces', he probably wouldn’t have gone this far. 

Compared to H12020, we’ve seen an 11% increase in fraud rates in H2 (see Graph 9). 

Graph 9 - Identity Fraud Rate in Crypto 2020

Since crypto technology is fast-moving and more and more businesses accept crypto payments, the increase in fraud rates is not surprising. Fraudsters look to leverage uncertainty and new procedures enabled by the pandemic, as many people are forced to move more of their lives online and some of them discover online services for the first time. For example, as many lost economic stability when the pandemic hit they are now more exposed to so-called 'investment scams' in which criminals convince people to invest into a 'new and developing' cryptocurrency by promising huge returns. There were also cases of scammers posing as trusted e-commerce sites and luring customers into buying COVID-19 treatments via crypto payments. People unknowingly exposed their identities, which fraudsters then re-used for illicit purposes.

As for the countries with the highest fraud rates in crypto, the US leads the way with over 10% followed closely by Vietnam and Nigeria (see Graph 10). 

Graph 10 - Top 5 Fraudulent Countries in Crypto in 2020

Fintech has become an essential part of everyday life for customers and institutions. As more and more services are digitized and clients don’t have to physically meet a financial representative to open accounts or perform transactions, fraudsters' appetites grow alongside demand.

"With the help of Veriff’s technology, TransferGo is able to verify a customer's identity fast but also in a most secure manner. We are able to prevent any attempts by fraudulent individuals looking to register or use our service. Our partnership with Veriff also supports Know Your Customer (KYC) and Anti-Money Laundering (AML) checks during the initial sign-up process." – Baran Ozkan, Director of Product at TransferGo

The most prevalent type of fraud in fintech is identity fraud (see Graph 11).

In order to detect whether a verification has been unlawfully initiated with someone else’s document, we compare the extracted faces from a selfie and a document photo. If the confidence of similarity is too low, we decline the session. If we’re not sure, we highlight the appropriate risks and leave the decision for a specialist. If they match, the session is algorithmically approved using our ML stack. If the same user submits a verification attempt in future, we can crosslink the incoming session with previous sessions through face embedding and present risk labels suggesting previous attempts of impersonation.

Compared to H1 2020 we’ve seen a 7% identity fraud rate increase in H2 (see Graph 12). 

Graph 12 - Identity Fraud Rate in Fintech 2020

The highest fraud rates in the fintech sector are seen in Europe. With close to 5%, Romania takes the lead (see Graph 13) followed by the United Kingdom and Spain. 

Graph 13 - Top 5 Fraudulent Countries in Fintech in 2020

Identity verification is critical to most businesses – but when talking about mobility, a high value asset is being handed over to a stranger. Knowing that person’s identity and predicting the behavior of bad actors is absolutely critical to a healthy, compliant and secure mobility company.

“On top of the strong time-saving automation component, we consider Veriff’s category extraction feature a game changer, as it fully enables the car-sharing use case. In particular, fraud and damages are an increasing concern in the mobility industry – so of course high cost assets such as a car, or a luxury car for that matter, need to be safeguarded: precise license identification strongly contributes to this.” – Nicholas Kirk, Head of Business Development, goUrban

In the mobility sector the most prevalent fraud types are identity fraud and recurring fraud, which are almost equally as common (see Graph 14). 

If fraudsters do manage to abuse the system, they will come back and try again; if they fail, they will still come back – and try twice as hard. Luckily, recurring fraud is where Veriff’s crosslinks shine the brightest. If we’re confident that the end-user has committed fraud before, we’ll automatically decline all the recurring attempts associated with the same person, device, or document.

If the same person, device, or document, have been found approved in the historically submitted sessions, all the recurring attempts will be declined with Velocity/Abuse – a feature that ensures that no end user abuses your service via multi-accounting.

Compared to H1 2020, in H2 we’ve seen a 16% increase in recurring fraud rates (See Graph 15), which pushed identity fraud down to the second most prevalent type of fraud in mobility.

Graph 15 - Recurring Fraud Rate in Mobility in 2020 

As the use of scooters skyrocketed in many cities because of the pandemic, the increase in fraud is expected. We’ve seen many cases of underage users attempting to get illegal access to vehicles with another person’s legal ID, or attempt to fool our system by showing images from their mobile device.

When it comes to regional mobility fraud rates, the Netherlands takes first place with a fraud rate of over 10% (See Graph 16). 

Graph 16 - Top 5 Fraudulent Countries in Mobility

We're proud to present our Identity Fraud Report 2020, free to download right now, no email required.

We're proud to present our Identity Fraud Report covering all of 2020, looking at the trends and changes we've observed throughout the last 12 months. We'll look at the effect of Covid-19, how the major industries we support were affected, and make our recommendations for 2021.

Read or download the Veriff Identity Fraud Report 2020, exploring trends in online identity fraud during the last 12 months.

Personal vehicle usage and public transport have transformed unimaginably in recent years, as innovative services like app-based cars, scooter or bike rentals, and ride-sharing have been introduced.

Such services led to the emergence of the concept of 'Mobility-as-a-service' (MaaS). In the “Technology in Society” journal the concept of MaaS is described simply as: 

“The bundling of different transport means, public and private, into one easy-to-use package for the customer. The service is provided to the customer on demand via mobile applications and payment is handled via a digital wallet.” 

In other words, MaaS brings all modes of transport together into one intuitive mobile app and makes any trip-planning easy and instant, putting the passenger at the forefront. It combines travel options with different vehicles from different carriers, providing everything from travel-planning to payment.

In addition to making travelling cheaper, easier and more accessible, the ‘MaaS’ concept also made it environmentally friendlier. The UK technology and innovation center for Intelligent Mobility has provided a theoretical example showing how a MaaS supporting user can reduce Single Occupancy Vehicle use in their report “Exploring the Opportunity for Mobility as a Service in the UK“.

And according to the research of ‘Mobility and the Sharing Economy: Potential to Overcome First- and Last-Mile Public Transit Connections’, one-way car sharing is able to reduce VMT and GHG emissions by 6%-16% and 4%-18% accordingly.

The concept of shared consumption has changed the landscape of the mobility industry. It is based on the idea that sometimes temporary access to a service is more convenient and beneficial than permanent access. The shared consumption model has been proposed with regard to personal vehicle use for several years. The bottom line is this: there are hundreds of different vehicles scattered around a city (usually economical or electric cars, scooters or bikes) which can be easily booked and accessed directly from an app on your phone. And when the ride is finished, you lock the vehicle using the app, get a receipt and no longer worry about where you parked your car, how much the monthly maintenance is for it, etc.  

When providing access to these services, you need to know your customer’s identity (and whether they’re allowed to use the relevant vehicle) before handing them the keys. This is where Veriff comes into play - helping you grant access to legitimate users with a high level of automation, accuracy, compliance and fraud prevention. And if you’re not convinced, check out what our partners, goUrban, said about us in our blog.

Mobility was one of the most affected industries during the COVID-19 pandemic. There are various factors at the heart of the negative consequences: lockdowns, closure of state borders, restrictions on movement, perceived health risk when using shared transportation etc. Different combinations of all of these factors affected every mobility service. According to recent McKinsey analysis “With the number of passenger-kilometers traveled declining 50-60% worldwide since the onset of the COVID-19 crisis, use of micromobility solutions has declined dramatically.” 

Today mobility companies are in a transitional stage full of uncertainty, with the potential need to introduce strict hygiene controls, such as compulsory face masks for drivers and passengers, health checks, protocols complying with distance and number of people allowed per space. The uncertainty concerns not only the timing of the return to pre-crisis indicators, but also the future image of the transport sector in the post-coronavirus world as a whole.

Veriff has an in-house built fraud prevention engine that is automating the decision making process and also assists specialists in case an automatic decision can’t be made (a hybrid approach). The engine can be broken into smaller pieces but all of them revolve around our proprietary device fingerprinting solution (see Graph 1).

Crosslinking allows Veriff to group together sessions that share similar data points. Based on previous knowledge, fraudsters don’t tend to limit themselves to one try - they’ll try to get verified today, tomorrow and in the upcoming months and they won’t stop as long as they have fake identities. All the information from crosslinks is taken into account by our automatic decision engine, and is forwarded to our clients. 

Velocity/Abuse ensures that no end-user abuses your service via multi-accounting. Taking into account all of the information we see through crosslinks, we can automatically shut down users if they, their document, or device have been approved before. We have three velocity checks that can be activated altogether or independently from each other:

Duplicated user - checks whether the person has been approved before

Duplicated document - checks whether the document has been approved before

Duplicated device - checks whether the same device has been approved before

Risk labels point out the signs of fraudulent behavior in sessions. These labels are used by our specialists in more detailed security review and are forwarded to clients to give insight about the final decision and help in post analysis.

What types of fraud are we discussing here?

We’re breaking mobility fraud down into 4 main types:

We’ll look at each in depth, what they are, the types we see most regularly, and the impact within the financial technology world.

This is often the type of identity fraud that leaps to mind first - tampered or entirely fake identity documents. These often exist in the form of fake IDs for a specific real world application - normally gaining access to something you’re underage for - but online there is normally more skill that goes into their creation, and they look to serve a monetary purpose, frequently some form of financial bonus on offer for inviting more users to a site.

In the case of mobility, we might consider a fake driver’s licence created to gain access to a vehicle when underage, or present when caught driving underage. Although both Veriff and police forces can catch these out with impressive speed.

There are various methods of tampering, but the end result always includes slight alterations made to a legitimate document in order to partially or entirely change the holder’s identity. Forgeries include but are not limited to:

Overwriting document data with a pen, pencil or other simple tools

Adding/removing specific document data or elements

Tampered documents are usually counterfeit originals, but fake documents try to imitate the appearance of a legitimate-looking document but are reproductions of the original. These come in the form of:

Alterated government-issued specimens that are public

Premade templates with fake photos and data

In the first 6 months of 2020, document fraud represented 7% of all fraud in the mobility market (see Graph 2).

Our in-house document database plays a key role in ensuring the accuracy of document fraud prevention. The database is updated regularly as we carry out extensive document related research (i.e. we find official specimens, information related to the issuing terms, etc) and cooperate with government authorities across the world.

In addition to our database, Veriff’s in-house fraud prevention engine plays a crucial role in document fraud detection and prevention. With the help of crosslinking we’re able to see if a user has previously submitted tampered documents or was involved in any suspicious activity.

This is exactly what you’d perhaps expect, fraud which involves a degree of technical skill which an average person wouldn’t possess. In this instance, we’re looking at streamed images and fraudulent access, two methods to take advantage of offers and make potential monetary gains.

Images and/or videos are streamed (or a slideshow)

This type of fraud happens when a verification includes media that’s coming from an emulated camera source. A fraudster might collect the portrait and document pictures belonging to different people in advance, edit them into a video and stream this inside Veriff’s flow to imitate the process being live.

Every time an end-user accesses the verification flow, we collect device and network information. Fraudulent accesses are defined as:

“Accesses associated with one verification session that has been accessed from different countries' networks and multiple devices.”

This is an indicator of the session link being fraudulently shared between different parties.

In the first 6 months of 2020, technical fraud represented 4% of all fraud in the mobility market (see Graph 3).

Our comprehensive profile of raw device and network data grants us full control over exactly which pieces of information we use and in what context. We can utilize specific elements of the device information, to spot whether camera emulation software was used at some point during the verification process. 

If we detect that an emulated camera source was used to submit the session, we note this, which helps in the final decision. We also perform checks on session images, to check if there is consistent natural movement between them.

To prevent possible fraudulent access in the session, we look to detect whether a session is being accessed from different countries' networks. If we detect a repetitive pattern indicating fraudulent access, we automatically block the user with the suspicion of the session link being compromised.

As we’re talking about technical fraud - did you know about the existence of romance scams? 

In romance scams fraudsters usually create fake online profiles with fictional identities, pictures and names with the help of which they lure their victims, where the main target group is usually senior women. After contact is established, they start expressing strong emotions for their victim, sharing ‘personal' information and digitally whispering sweet nothings. Once they’ve gained their victims’ trust, they request for money or other ‘favors’. These scams usually end up with big financial losses and a deep emotional feeling of betrayal.

We’ve unsurprisingly seen a similar ‘love story’ in Veriff. A woman was lured into opening an account for a service we assumed she would never use, most likely not understanding she’s the victim of a scam. Thanks to our fraudulent access detection and video feature, we caught the fraudster red-handed while he was asking the woman to take additional pictures and send authorization details via messenger.

Now we come to identity fraud. Not dissimilar to document fraud which we mentioned earlier, identity fraud is more about impersonation than actual document tampering. That’s one of the two examples we’ll look to highlight in fact, attempted impersonation, along with attempted deceit.

Attempted impersonation is the intentional use of someone else’s identity document with the aim of obtaining access to the service on someone else’s behalf. This type of fraud usually uses an illegally obtained physical document of the victim presented by a fraudster.

The end-user doesn’t show a real physical document, but shows it from a device screen or a printed-out paper as they’re using someone else's digital document or a digitally manipulated document of their own.

In the first 6 months of 2020, identity fraud made up 55% of all fraud in the mobility market making it by far the most prevalent type (see Graph 4).

Given the nature of the industry, every mobility company has to keep a balance between ensuring compliance with all the relevant regulations and offering a great customer experience. And this is where Veriff comes in, with our highly configurable flow and strong fraud prevention. 

In order to detect whether a verification process has been initiated with someone else’s physical document, we compare extracted faces from a selfie and a document photo. If our confidence in the similarity is too low we decline the session. If our automated engine is unsure it highlights appropriate risks and leaves the decision to a specialist.

For mobility, we’re predominantly verifying driver’s licenses, and this is why we also now offer driver’s license category extraction, as an additional feature geared towards mobility companies. You’ll not only be able to see the details of your user, but also what category of vehicle they’ve been approved to drive. 

By providing high-value assets to consumers, namely cars, every mobility service is subject to high business risks. Along with a potential vehicle’s theft there is the danger of identity theft by fraudsters who penetrate real users' devices or create fake identities to get access to the service.

“Identity theft is not a joke, Jim! Millions of families suffer every year!“ - Dwight Schrute 

Here in Veriff, we’ve seen different types of identity theft - from underage kids using their siblings' or parents' documents to rent a scooter to deepfakes trying to imitate someone else’s likeness by manipulating images and/or videos. The rising tide of AI and machine learning is constantly making it easier to steal someone’s face without undergoing a plastic surgery (like John Travolta did in the movie “Face/Off”), but our anti-spoofing controls and deepfake detection will make sure the right person is getting access to the service they require.

An example of deepfake technology: in a scene from Man of Steel, actress Amy Adams in the original (left) is modified to have the face of actor Nicolas Cage (right) - source https://en.wikipedia.org/wiki/Deepfake

Finally, we come to recurring fraud. This is also broken down into two examples, one of which is basic ‘recurring’ fraud, where a fraudster has been successful and come back to try again. The other is velocity abuse, which we’ll explain further below.

Recurring - Strong links to previous fraud

If fraudsters manage to abuse the system - they will come back and try again, if they fail to do so - they will come back and try twice as hard.

Velocity abuse works as follows - after getting approved once, fraudsters try to abuse the system and get approved as many times as possible, which usually involves verifying different real users without telling them what they’re being verified for. Fraudsters tend to go as far as creating synthetic identities, where they try to create a new identity by combining their real information in conjunction with fake data.

In the first 6 months of 2020, recurring fraud made up 34% of all fraud in the mobility market (see Graph 5).

Recurring fraud is where our crosslinks shine the brightest. If we’re confident that the end-user has committed fraud before, we’ll automatically decline all the recurring attempts associated with the same person, device or document. 

If the same person, document or device have been found approved in the historically submitted sessions, all the recurring attempts will be declined with Velocity/Abuse. 

In our third fraud report, we take a look at the impact of online and identity fraud on the world of mobility in 2020, and the most prevalent types of fraud seen by Veriff, with data gathered from our verification flows.

The Veriff Mobility Fraud Report - January to June 2020

The Financial Technology (Fintech) industry has been gaining momentum over the years by transforming the way financial businesses operate and providing a huge range of services to consumers. The industry has evolved rapidly and keeps on growing. According to the 'Fintech Global Market Opportunities and Strategies' report published in July 2020:

“The global Fintech market reached a value of nearly $111,240.50 million in 2019, having grown at a compound annual growth rate (CAGR) of 7.9% since 2015, and is expected to grow at a CAGR of 9.2% to nearly $158,014.3 million by 2023. Also the market is expected to grow to $191,840.2 million in 2025 at a CAGR of 10.2% and to $325,311.8 million in 2030 at a CAGR of 11.1%.”

Fintech transforms traditional financial institutions into faster, more secure and coherent businesses by implementing technologies like Blockchain and AI. It enabled the possibility of day-to-day banking operations, trading, investing, lending, international payments etc to users all around the world. Moreover, according to the World Bank Group report, digital financial services have the potential to help the poor increase their income and resilience by gaining access to basic financial services.

However we’ve seen the potential for fraud and financial abuse within the industry, with the recent Wirecard story acting as a stark reminder to up-and-coming players in the financial world of having risk management protocols in place. But this was fraud on a large scale - what about the everyday fraudsters, intentionally attempting to steal identities in an attempt to gain access to accounts or gain financial windfalls? This is what Veriff is fighting daily.

The COVID-19 pandemic hit most industries incredibly hard. It impacted the financial stability of business as well as individuals, sending millions to poverty. According to the Global Economic Prospects the crisis is expected to leave a 5.2% contraction on global economic activity in 2020.

At the same time the crisis brought an opportunity for Fintech companies to increase their demand in times of social distancing, quarantines and people adapting to a new reality powered by digitization. We’ve written on our blog about how the pandemic will impact the future of the financial industry and measures to combat illicit financing.  

As many businesses look to go digital, the demand for digital KYC processes also increases. And this is where Veriff comes in by helping granting access to services to legitimate users, and blocking the fraudsters.

We’re breaking Fintech fraud down into 4 main types:

In the first 6 months of 2020, document fraud represented 24% of all fraud in the fintech market (see Graph 2).

In addition to our database, Veriff’s in-house fraud prevention engine plays a crucial role in document fraud detection and prevention. With the help of crosslinking we’re able to see if a user has previously submitted tampered documents or was involved in any suspicious activity. 

Document fraud is the second most prevalent type of fraud in Fintech, so no matter which area you’re in, we’re ready to help you tackle this problem. And trust us, we’ve seen different types of document tampering, from very obvious one-time document manipulation to complex fraud schemes, like the following: 

”We noticed unusual traffic coming from an Eastern European country, associated with a financial institution. What raised suspicions even further was the fact that customers were submitting documents issued by a different country. At first glance one could think these were people travelling, as the documents seemed legitimate and people presenting them matched the identity on the document. But having all data points collected by our fraud engine and our highly trained specialists' expertise, it became evident that the presented documents were fake, and the end-users presenting them were up to something fishy. Our further investigation revealed that the group of fraudsters used disposable tools in order to emulate foreign traffic and create the illusion of “legitimacy”, and we had a reason to believe that the ultimate goal of this scheme was to set people up for migration to a more developed country (with fake documents in hand and a financial history). Unfortunately for these people, the trip was short lived.”

Every time an end-user accesses the verification flow, we collect device and network information. Fraudulent accesses are defined as:
“Accesses associated with one verification session that has been accessed from different countries' networks and multiple devices.”
This is an indicator of the session link being fraudulently shared between different parties.

In the first 6 months of 2020, technical fraud represented 1% of all fraud in the fintech market (see Graph 3).

Now we come to identity fraud. Not dissimilar to document fraud which we mentioned earlier, identity fraud is more about impersonation than actual document tampering. That’s among the examples we’ll look to highlight in fact, attempted impersonation. We’ll also look at third party guidance, which involves a more physical presence.

Third party guidance usually involves physical assistance of the end-user, sometimes without telling them what the verification is for. This behavior leads us to believe that the end-user being assisted will not be the one actually using the service they’re being signed up for.

In the first 6 months of 2020, identity fraud made up 67% of all fraud in the fintech market making it by far the most prevalent type (see Graph 4).

Given the nature of the industry, every Fintech company has to keep a balance between ensuring compliance with all the relevant regulations and offering a great customer experience. And this is where Veriff comes in, with our highly configurable flow and strong fraud prevention. 

In order to detect whether a verification process has been initiated with someone else’s physical document, we compare extracted faces from a selfie and a document photo. If our confidence in the similarity is too low we decline the session. If our automated engine is unsure it highlights appropriate risks and leaves the decision to a specialist. 

It’s no wonder identity fraud is the most prominent type of fraud in fintech. Malicious actors' appetite grows together with the industry, as more and more services are digitized and clients don’t have to physically meet a financial representative anymore to open accounts or perform any financial transactions. Here’s another first-hand story from inside Veriff:

“Forging a photo on a document is one thing, but forging the person presenting the document is a whole other story! The villain of this story must have watched the episode of “The Office” (the US version), where Dwight Schrute demonstrated his collection of wigs for every single person in the office with the words: “You never know when you're gonna need to bear a passing resemblance to someone”. Our perpetrator printed out a document with a nicely crafted face on it, and in addition, has designed a life-like mask matching the identity on the document he was showing. If only he knew we were able to see him ‘changing faces', he probably wouldn’t have gone this far.”

In the first 6 months of 2020, recurring fraud made up 8% of all fraud in the fintech market (see Graph 5).

Now that we’ve looked at the 4 different types of fraud that we’ve seen within the fintech industry, we can see the full breakdown below (see Graph 6):

In our second fraud report, we take a look at the impact of financial crime and fraud on the world of fintech in 2020, and the most prevalent types of fraud seen by Veriff, with data gathered from our verification flows.

The Veriff Fintech Fraud Report - January to June 2020

The cryptocurrency market is subjected to the highest fraud rate compared to other industries that Veriff works with right now. In fact this was still the case when we wrote our first fraud report, midway through last year, and this isn’t looking to change very fast.

The industry itself gains popularity day-by-day, by enabling faster and lower-cost international transactions, along with different promotional activities, which in turn lures criminals willing to cheat the system. And crypto itself is still seen in some quarters as a niche interest, but as the value of some of the more stable coins stays high, it’s worth understanding it all a little better.

To do that, we’d recommend our accompanying blogs - a Geek’s Guide to Crypto and Why Crypto is Ready for IDV to help you brush up before getting into the nitty gritty of this report.

As an illustration of the level of global financial crime within cryptocurrency alone, in 2019 cyber criminals were able to siphon away $4.26 billion from cryptocurrency users and exchanges. In the larger cases, this was down to sophisticated hacking of wallets and exchanges, but like all financial crime, there are larger and smaller scale examples.

One of the more public examples of fraudulent activity around crypto took place on Twitter recently, as a number of celebrities had their accounts hacked, and links were placed with the enticement to “send money here and you’ll get double back”. Unsurprisingly, those who sent crypto saw none in return and the scammers were quickly taken down, but not before damage had been done.

We wanted to take a deeper look into the ways in which criminals look to exploit cryptocurrencies through identity-related fraud, the trends we’ve observed, and how Veriff is designed to help crypto fight back.

Crosslinking allows Veriff to group together sessions that share similar data points. Based on previous knowledge, fraudsters don’t tend to limit themselves to one try - they’ll try to get verified today, tomorrow and in the upcoming months and they won’t stop as long as they have fake identities. All the information from crosslinks is taken into account by our automatic decision engine, and is forwarded to our clients.

When it comes to Crypto, we can break fraud down into 4 main types:

We’ll look at each in depth, what they are, the types we see most regularly, and the impact within the crypto industry.

While tampered documents are usually counterfeited original documents, fake documents include manipulations that try to imitate the appearance of a legitimate-looking document but in reality are reproductions of the original. Such forgeries might come in the form of:

Alterations of government-issued document specimens that are publicly available

Premade templates with inserted fake photos and document data

In the first 6 months of 2020, document fraud represented 4% of all fraud in the crypto market (see Graph 2)

Our internal specimen database plays a key role in ensuring the accuracy of document fraud prevention. The database is updated on a daily basis as we carry out extensive document-related research (i.e. we find official specimens, information related to the issuing terms, etc) and cooperate with government authorities across the world.

In addition to our database, Veriff’s fraud prevention engine plays a crucial role in document fraud detection and prevention. When it comes to crypto, fraudsters usually tamper with documents in bulk. This means they often have various amounts of documents but also mobile devices to ensure some kind of anonymity. Luckily, with Veriff’s crosslinking we’re able to see data points that fraudsters are able to change. 

Every time an end-user accesses the verification flow, we collect device and network information. Fraudulent accesses are defined as:
“Accesses associated with one verification session that has been accessed from different countries' networks and multiple devices.”
This is an indicator of the session link being fraudulently shared between different parties. 

In the crypto realm, link-sharing scams are initiated to get victims to sign up with legitimate documents, and then reap the benefits of an account takeover. Usually a fraudster will create an account on a crypto site, entering all the victim’s information that has been scraped from the web, and when the time comes for verification, they send a link to the specific individual - saying ‘verification is required’ for some other purpose. This could range from getting a free box of chocolates, to some kind of exclusive discount, to anything really. We’ve seen a lot of examples!

In the first 6 months of 2020, technical fraud represented 2% of all fraud in the crypto market (see Graph 3).

Thanks to a comprehensive profile of device and network data, we have full control over exactly which pieces of information we use and in what context. We can utilize specific elements of device information, to spot whether camera emulation software was used at any point during the verification process. 

We also perform checks on verification session images, and if there is little-to-no natural movement between them, we raise a risk label to flag this. 

To prevent possible fraudulent access within sessions, we’ve developed a specific risk label that is triggered if we detect the session being accessed from different countries' networks. 

Also added to the mix is crosslinking - if our fraud engine detects previous fraudulent accesses submitted by the same user, all their further verification attempts are automatically blocked as we consider it hard fraud.

Now we come to the two biggest types of fraud in the crypto market, the first of these being identity fraud. Not dissimilar to document fraud which we mentioned earlier, identity fraud is more about impersonation than actual document tampering. And that’s one of the two examples we’ll look to highlight - attempted impersonation and attempted deceit using fake images.

Here’s a real life example from the Veriff team:

“Fraudsters put a fake job ad on a popular social media site claiming to represent a large company. Users applied for the job, and after that the scammers collected the applicants CVs and opened crypto accounts on their behalf. When identity verification for the crypto wallet was required, fraudsters sent verification links to ‘job applicants’ as part of a hiring process. Fortunately the “scammed people” contacted the company for whom they allegedly applied for a job and had done the verification for. Naturally they found out that online identity verification was not part of the company’s hiring process."

In the first 6 months of 2020, identity fraud made up 34% of all fraud in the crypto market (see Graph 4).

In order to detect whether a verification has been initiated with someone else’s physical document, we compare the faces from the selfie and document photo. If our confidence in the  similarity is too low we decline the verification. If we’re not sure, we highlight the appropriate risks and leave the decision for a specialist. 

If the same user tries to submit a different verification attempt in future, we can crosslink the incoming session with the previously declined sessions. 

Finally, we come to recurring fraud - and if you’ve been doing the addition through this report, you’ll know it makes up the lion’s share of fraud in the crypto market. This is also broken down into two examples, one of which is basic ‘recurring’ fraud, where a fraudster has been successful and come back to try again. The other is velocity abuse, which we’ll explain further below.

Here’s another story from the Veriff team:
“We noticed abnormal traffic associated with a car dealership located in the US. In addition to the store’s employees opening crypto accounts and verifying themselves at the spot in the shop, it seemed like shop’s customers were also asked to pose with their documents as a part of the ‘store procedure'. Some of the sessions were guided by what we think was an employee of the shop, some were carried out independently by customers sitting in cars. Unfortunately, this didn't lead anyone to getting a good discount at the car dealership, but a free crypto account was created on their behalf without their knowledge.”

Crypto market experiences the highest rates of multi-accounting due to different promotions involving free money. After getting approved once, fraudsters try to abuse the system and get approved as many times as possible, which usually involves verifying different real users without telling them what they are being verified for. Fraudsters tend to go as far as creating synthetic identities, where they try to create a new identity by combining their real information in conjunction with fake data.

In the first 6 months of 2020, recurring fraud made up 60% of all fraud in the crypto market (see Graph 5).

Recurring fraud is where crosslinks shine the brightest. If we’re confident that the end-user has committed fraud before, we’ll automatically decline all the recurring attempts associated with the same person, device or document. 

Now that we’ve looked at the 4 different types of fraud that we’ve seen within the crypto industry, we can see the full breakdown below (see Graph 6):

Of course in all of the above instances, Veriff is well-placed as a verification provider to fight back against online fraud in all forms. We continue to observe trends across the crypto industry so we can stay ahead of developments, and prevent losses for our crypto partners.

Look out for our next report coming in the near future all about fraud in Fintech.

Get a free trial of Veriff for 30 days with 100 free verifications to get a real look at our fraud prevention capabilities in action. Don't make identity verification a difficult hurdle for your potential customers.

We looked at the impact of financial crime and fraud on crypto in 2020, and the most prevalent types of fraud seen by Veriff, with data gathered from our verification flows.

The Veriff Crypto Fraud Report - January to June 2020

Starting with an overview of the current state of fraud in a growing digital economy, the following report will shed light on the causes and forms of online identity fraud today, and close with industry-specific recommendations on how to put a stop to it.

You can’t sweep identity fraud under the rug in 2019

Since the birth of the World Wide Web 30 years ago, it has become an inseparable aspect of day to day life. Within only a year, the number of users on the Internet increased by 9.1%, compared to a relatively small 1.1% increase in the total population.

Whether it is the sheer increase in the volume of online users, or that fraudsters are innovating at a faster rate than corporate security teams and anti-fraud technology, trust online is increasingly difficult to uphold. If you find this tough to swallow, take a look at the cost of identity fraud for people and businesses.

The consumer and business cost of online identity fraud

In 2018, a staggering $1.48 billion in losses resulting from online fraud complaints reported to the Internet Crime Complaint Center. That’s a 28% increase compared to their 2017 numbers. Businesses aren’t safe either. A 2018 survey published by EY revealed that 33% of surveyed business leaders saw fraud and corruption as one of their greatest risks.

Fintech companies and banks usually come to mind when you think about fraud, but other industries are just susceptible albeit in different ways. According to a study by ThreatMatrix, the fraudulent new-account trend makes global e-commerce transactions ten times riskier than they used to be. 

Adding to that, our data gathered from millions of verifications a year detect that as much as 5% of all attempted verifications are fraudulent, with some industries like cryptocurrency and blocktech seeing rates as high 24.6%. 

Reports
Back to all articles

The Veriff Identity Fraud Report 2020

The Veriff Mobility Fraud Report - January to June 2020

The Veriff Fintech Fraud Report - January to June 2020

The Veriff Crypto Fraud Report - January to June 2020

The Veriff Identity Fraud Report 2019

Stay up to date on Veriff news, product updates, and more

ReportsBack to all articles

The Veriff Identity Fraud Report 2020

The Veriff Mobility Fraud Report - January to June 2020

The Veriff Fintech Fraud Report - January to June 2020

The Veriff Crypto Fraud Report - January to June 2020

The Veriff Identity Fraud Report 2019

Stay up to date on Veriff news, product updates, and more

Reports
Back to all articles