Emil Eifrem of Neo Technology explains why traditional relational database technologies aren’t financial services organisations best tools for stopping sophisticated scams
While no fraud prevention measure can ever be 100% bullet-proof, a lot of help can be provided to risk managers by a new approach to working with banking data; one that focuses on relationships and uncovers the hidden patterns of suspicious activity, in order to head off the fraudsters.
But when we say ‘relationships,’ isn’t that what our existing, relational database management systems are doing? The answer is yes, but there’s a subtle yet critical difference. SQL based databases are great, but essentially you have to tell them what to look for – while the technique we’re discussing goes from points of data to all the connections between them.
And looking at data relationships doesn’t necessarily mean gathering new or more data. The key to it is to look at data in a way that helps make explicit underlying connections.
This is achieved by a powerful, well-proven approach, graph databases, that is gaining increasing attention. And a growing number of enterprises, banks and financial institutions are using them to solve a variety of data problems, in particular to identify advance fraud scenarios – and in real-time, too.
A case in point: PayPal uses graph techniques to perform sophisticated fraud detection on eBay and StubHub transactions for just this purpose. Market-watchers IDC estimate that this has already saved it more than $700 million and also enables the company to perform predictive fraud analysis.
If they act the same as a proper customer – how to spot the electronic burglar?
Let’s explore in more detail how relationship-spotting can help in anti-fraud activities and risk management. As we know, there are various types of fraud: first-party bank fraud, insurance fraud, and e-commerce fraud, to name some of the most troublesome. First-party fraud involves criminals who apply for credit cards, loans, overdrafts and unsecured banking credit lines, but who have no intention of paying the money back, something that’s a serious problem for banking institutions; it’s estimated that as much as 10 to 20% of unsecured bad debt at leading US and European banks is drawn from this form of deceit.
The surprisingly large size of these losses is due to first-party fraud being hard to pick up as fraudsters behave in the same way as your legitimate customer until the day they cash in their inflated accounts and abscond with the money. At the same time, there is the relationship between the number of participants to the value of their illegal gains, where a small number of perpetrators can translate in to a distressingly high numbers of illegitimate transactions. In a fraud ring of just two individuals, sharing only phone number and address, this ring can create 22= 4 synthetic identities with fake names and with 4-5 accounts for each synthetic identity, a total of 18 accounts. Assuming an average of £4,000 in credit exposure per account, the bank’s loss could be a whopping £72,000 as a result – perhaps a lot more.
Catching fraud rings and stopping them before they cause damage is what we all want to be able to do. One reason for that still being a rarity is that traditional methods of fraud detection are not geared to look for the right thing – in this case, the fraud rings that are created by shared identifiers.
What they all have in common in terms of criminal practices is layers of indirection to hide the crime that can only be uncovered via connected analysis. The good news is that while these exponential relationships are what make these schemes so damaging for banks, it’s also the characteristic that makes them open to graph techniques. Thus standard stats-based tools, e.g. deviations from normal purchasing patterns, use discrete data, not the connections we’ve been discussing. Discrete methods are useful for catching fraudsters acting on their own, but fall short when it comes to collectives who may work cross-border, even cross-continent. Furthermore, such methods are prone to the notorious ‘false positive,’ which creates undesired side-effects in annoyed customers and lost revenue opportunity.
Doable in SQL, yes – but not easily or cheaply
By contrast, uncovering fraud rings with traditional relational database technologies requires modelling the data as a set of tables and columns then carrying out a series of complex joins and self-joins. Queries like that work, but are complex to build, and expensive to run. Scaling them in a way that supports real-time access also poses significant technical challenges, with performance becoming exponentially worse not only as the size of the ring increases, but as the size of total data set grows.
Augmenting existing fraud detection infrastructure to support ring detection can be easily done by running appropriate entity link analysis queries using a graph database, augmented by running checks during key stages in the customer and account lifecycle, such as once a credit balance threshold is hit, when a cheque bounces and so on.
Real-time graph traversals tied to the right kinds of events can help banks identify probable fraud rings: during or even before the bust-out occurs.
Widening access to a powerful anti-fraud tech
Another use case is bogus car insurance activity. In the UK, insurers estimate that bogus ‘whiplash’ accident claims add £144 per year to every driver’s policy. In a typical hard fraud scenario, rings of fraudsters work together to stage fake accidents complete with fake drivers, fake passengers, fake pedestrians and even fake witnesses.
Once again, graph databases can be a powerful tool in combatting this kind of multi-party fraud. As in the bank fraud example, identifying that a ring is in operation would require joining a number of tables in a complex schema (accidents, vehicles, owners, drivers, passengers, pedestrians, witnesses, providers) and joining these together multiple times – once per potential role – in order to uncover the full picture is not an easy task in SQL, easier using a graph approach. Graph databases’ ability to draw relationship connections, again, provides an exciting answer here.
Clearly, graph databases are emerging as the ideal solution to finding hidden patterns, and at scale. Interestingly, they have been powering the social web for some time – but while early graph database converts like PayPal and Facebook had to build their own in-house graph data stores from scratch, off-the-shelf graph databases are now available for any size of business. Forrester Research estimates that more than one in four enterprises will be using such technology by 2017 – and no wonder given the efficacy of what they do.
To sum up, traditional database technologies, while still suitable and necessary for certain types of prevention, are not designed to detect the most elaborate fraud operations. In contrast, graph databases provide a unique ability to uncover a variety of important fraud patterns, in real time, either in groups or on an individual basis – and so are a powerful addition to any financial services firm’s security arsenal.
And with their growing availability, there’s no excuse for ignoring their potential any more.
The author is co-founder and CEO of Neo Technology, the company behind Neo4j, the world’s leading graph database (http://neo4j.com/)
Lockdown 2.0 – Here’s how to be the best-looking person in the virtual room
suggests “the product you’re creating is not the camera, the lens or a webcam’s clever industrial design. It’s the subject, you, which is just on e part of the entire image they see. You want that image to convey quality, not convenience.”
Technology experts at Reincubate saw an opportunity in the rise of remote-working video calls and developed the app, Camo, to improve the video quality of our webcam calls. As part of this, they consulted the digital photography expert and author, Jeff Carlson, to reveal how we can look our best online.
It’s clear by now that COVID-19 has normalised remote working, but as part of this the importance of video calls has risen exponentially. While we’re all used to seeing the more casual sides of our colleagues (t-shirt and shorts, anyone?), poor webcam quality is slightly less forgivable.
But how can we improve how we look on video? We consulted Jeff Carlson for some top tips– here is what he had to say.
- Improve the picture quality of your call
The better your camera, the higher quality your webcam calls will be. Most webcams (as well as currently being hard to get hold of and expensive), are subpar. A DSLR setup will give you the best picture, but will cost $1,500+. You can also use your iPhone’s amazing camera as a webcam, using the new app from Reincubate, Camo.
Jeff’s comments “The iPhone’s camera system features dedicated coprocessors for evaluating and adjusting the image in real time. Apple has put a tremendous amount of work into its imaging software as a way to compensate for the necessarily small camera sensors. Although it all works in service of creating stills and video, you get the same benefits when using the iPhone as a webcam.”
Aidan Fitzpatrick, CEO of Reincubate explains why the team created Camo, “Earlier this year our team moved to working remotely, and in video calls everyone looked pretty bad, irrespective of whether they were on built-in Mac webcams or third-party ones. Thus began my journey to build Camo: an iPhone has one of the world’s best cameras in it, so could we make it work as a webcam? Category-leading webcams are noticeably worse than an iPhone 7. This makes sense: six weeks of Apple’s R&D spend tops Logitech’s annual gross revenue.”
- Place your camera at eye level
A video call will never quite be the same as a face-to-face conversation, but bringing your camera up to eye level is a good place to start. That can involve putting your laptop on a stand or pile of books, mounting a webcam to the top of your display screen, or even using a tripod to get the perfect position.
Jeff points out, “If the camera is looking down on you, you’ll appear minimized in the frame; if it’s looking up, you’re inviting people to focus on your chin, neck, or nostrils. Most important, positioning the camera off your eye level is a distraction. Look them in the eye, even if they’re miles or continents away.”
Low camera placement from a MacBook
- Make the most of natural lighting
Be aware of the lighting in the room and move yourself to face natural lighting if you can. Positioning the camera so any natural light is behind you takes the light away from your face, which can make it harder to see and read expressions on a call.
Jeff Carlson’s top tip: “If the light from outside is too harsh, diffuse it and create softer shadows by tacking up a white sheet or a stand-alone diffuser over the window.”
Backlit against a window Facing natural light
- Use supplementary lighting like ring lights
The downside to natural lighting is that you’re at the mercy of the elements: if it’s too bright you’ll have the sun in your eyes, if it’s too dark you won’t be well lit.
Jeff recommends adding supplementary lighting if you’re looking to really enhance your video calls. After all, it looks like remote working will be carrying on for quite some time.
“The light can be just as easy as a household or inexpensive work light. Angle the light so it’s bouncing off a wall or the ceiling, depending on your work area, which, again, diffuses the light and makes it more flattering.
Or, for a little money, use a softbox or a shoot-through umbrella with daylight bulbs (5500K temperature), or if space is tight, LED panels. Larger lights are better for distributing illumination– don’t be afraid to get them in close to you. Placement depends on the look you’re going after; start by positioning one at a 45-degree angle in front and to the side of you, which lights most of your face while retaining nice shadow detail.”
In some cases, a ring light may work best. LEDs are arranged in a circle, with space in the middle to put the camera’s lens and get direct illumination from the direction of the camera.
- Centre yourself in the frame
Make sure you’re getting the right angle and that you’re using the frame effectively.
“You should aim for people to see your head and part of your torso, not all the space between your hair and the ceiling. Leave a little space above your head so it’s not cut off, but not enough that someone’s eyes are going to drift there.”
- Be mindful of your backdrop
It’s not always easy to get the quiet space needed for video calls when working from home, but try as best you can to remove anything too distracting from your background.
“Get rid of clutter or anything that’s distracting or unprofessional, because you can bet that will be the second thing the viewers notice after they see you. (The Twitter account @RateMySkypeRoom is an amusing ongoing commentary on the environments people on television are connecting from.)”
A busy background as seen by a webcam
- Make the most of virtual backgrounds
If you’re really struggling with finding a background that looks professional, try using a virtual background.
Jeff suggests: “Some apps can identify your presence in the scene and create a live mask that enables you to use an entirely different image to cover the background. While it’s a fun feature, the quality of the masking is still rudimentary, even with a green screen background that makes this sort of keying more accurate.”
- Be aware of your audio settings
Our laptop webcams, cameras, and mobile phones all include microphones, but if it’s at all possible, use a separate microphone instead.
“That can be an inexpensive lavalier mic, a USB microphone, or a set of iPhone earbuds. You can also get wireless lavalier models if you’re moving around during a call, such as presenting at a whiteboard in the camera’s field of view.
The idea is to get the microphone closer to your mouth so it’s recording what you say, not other sounds or echoes in the room. If you type during meetings, mount the mic on an arm instead of resting it on the same surface as your keyboard.”
- Be wary of video app add-ons
Video apps like Zoom include a ‘Touch up your appearance’ option in the Video settings. This applies a skin-smoothing filter to your face, but more often than not, the end result looks artificially blurry instead of smooth.
“Zoom also includes settings for suppressing persistent and intermittent background noise, and echo cancellation. They’re all set to Auto by default, but you can choose how aggressive or not the feature is.”
- Be the best looking person in the virtual room
What’s important to remember about video calls at this point in time is that most people are new to what is, really, personal broadcasting. That means you can easily get an edge, just by adopting a few suggestions in this article. When your video and audio quality improves, people will take notice.
Bringing finance into the 21st Century – How COVID and collaboration are catalysing digital transformation
By Keith Phillips, CEO of TISATech
If just six or seven months ago someone had told you that in a matter of weeks people around the world would be locked down in their homes, trying to navigate modern work systems from a prehistoric laptop, bickering with family over who’s hogging the Wi-Fi, migrating online to manage all financial services digitally, all while washing their hands every five minutes in fear of a global pandemic… You’d think they had lost their mind. But this very quickly became the reality for huge swathes of the world and we’re about to go through that all over again as the UK government has asked that those who can work from home should.
Unsurprisingly, statistics show that lockdown restrictions introduced by the UK government in March, led to a sharp increase in people adopting digital services. Banks encouraged its customers to log onto online banking, as they limited (and eventually halted) services at branches. This forced many customers online as their primary means of managing personal finances for the first time.
If anyone had doubts before, the Covid-19 pandemic proved to us the importance of well-functioning, effective digital financial services platforms, for both financial institutions and the people using them.
But with this sudden mass online migration, it’s become clear that traditional banks have struggled to keep up with servicing clients virtually. Legacy banking systems have always stilted the digitisation of financial services, but the pandemic thrust this issue into the limelight. Fintech firms, which focus intently on digital and mobile services, knew it was only a matter of time before financial institutions’ reliance was to increase at an unprecedented rate.
For years, fintechs have been called upon by traditional players to find solutions to problems borne from those clunky legacy systems, like manual completion of account changes and money transfers. Now it is the demand for these services to be online coupled with the need for financial services firms to cut costs, since Covid-19 hit the economy.
Covid-19 has catalysed the urgent need to bring digital transformation to a wider pool of financial services businesses. Customers now have even higher expectations of larger institutions, demanding that they keep up with what the younger and more nimble challengers have to offer. Industry leaders realise that they must transform their businesses as soon as possible, by streamlining and digitising operations to compete and, ultimately, improve services for their customers.
The race for digital acceleration began far before the recent pandemic – in fact, following the 2008 financial crisis is likely more accurate. Since the credit crunch, there has been a wave of new fintech firms, full of young, bright techies looking to be the next big thing. Fintechs have marketed themselves hard at big conferences and expos or by hosting ‘hackathons’, trying to prove themselves as the fastest, most innovative or the most vital to the future of the industry.
However, even during this period where accelerating innovation in online financial services and legacy systems is crucial, the conditions brought about by the pandemic have not been conducive to this much-needed transformation.
The second issue, which again was clear far before the pandemic, is that fact that no matter how nimble or clever the fintechs’ solutions are, it is still hard to implement the solutions seamlessly, as the sector is highly fragmented with banks using extremely outdated systems populated with vast amounts of data.
With the significance of the pandemic becoming more and more clear, and the need for better digital products and services becoming more crucial to financial services firms and consumers by the day, the industry has finally come together to provide a solution.
The TISAtech project was launched last month by The Investing and Saving Alliance (TISA), a membership organisation in the UK with more than 200 leading financial institutions as members. TISA asked The Disruption House, a specialist benchmarking and data analytics business, to create a clearing house platform for the industry to help it more effectively integrate new financial technology. The project aims to enhance products and services while reducing friction and ultimately lowering costs which are passed on to the customers.
With nearly 4,000 fintechs from around the world participating, it will be the world’s largest marketplace dedicated to Open Finance, Savings, and Investment.
Not only will it provide a ‘matchmaking’ service between financial institutions an fintechs, it will also host a sandbox environment. Financial institutions can pose real problems with real data and the fintechs are given the space to race to the bottom – to find the most constructive, cost-effective solution.
Yes, there are other marketplaces, but they all seem to struggle to achieve a return on investment. There is a genuine need for the ‘Trivago’ of financial technology – a one stop shop, run by an independent body, which can do more than just matchmaking. It needs to go above and beyond to encompass the sandboxing, assessments, profiling of fintechs to separate the wheat from the chaff, and provide a space for true collaboration.
The pandemic has taught us that we are more effective if we work together. We need mass support and collaboration to find solutions to problems. Businesses and industries are no different. If fintechs and financial institutions can work together, there is a real chance that we can start to lessen the economic hit for many businesses and consumers by lowering costs and streamlining better services and products. And even if it is just making it that little bit easier to manage personal finances from home when fighting with your children for the Wi-Fi, we are making a difference.
What to Know Before You Expand Across Borders
By Sean King, Director of International Tax at McGuire Sponsel
The American retail giant, Target Corporation, has a market cap of $64 billion and access to seemingly limitless resources and advisors. So, when the company engaged in its first global expansion, how could anything possibly go wrong?
Less than two years after opening its first Canadian store in 2013, Target shut down all133 Canadian locations and terminated more than 17,000 Canadian employees.
Expansion of an operation to another country can create unique challenges that may impact the financial viability of the entire enterprise. If Target Corporation can colossally fail in its expansion to Canada, how might Mom ‘N’ Pop LLC fare when expanding into Switzerland, Singapore, or Australia?
Successful global expansion requires an understanding of multilayered taxes, regulatory hurdles, employment laws, and cultural nuances. Fortunately, with the right guidance, global expansion can be both possible and profitable for businesses of any size.
Any company with global ambitions must first consider whether the company’s expansion outside of the U.S. will give rise to a taxable presence in the local country. In the cross-border context, a “permanent establishment” can be created in a local country when the enterprise reaches a certain level of activity, which is problematic because it exposes the U.S. multinational to taxation in the foreign country.
Foreign entity incorporation
To avoid permanent establishment risk, many U.S. multinationals choose to operate overseas through a formal corporate subsidiary, which reduces the company’s foreign income tax exposure, though it may result in an additional level of foreign income tax on the subsidiary’s earnings. In most jurisdictions, multinationals can operate their business in the foreign country as a branch, a pass through (e.g., partnership,) or a corporation.
As a branch, the U.S. multinational does not create a subsidiary in the foreign country. It holds assets, employees, and bank accounts under its own name. With a pass through, the U.S. multinational creates a separate entity in the foreign country that is treated as a partnership under the tax law of the foreign country but not necessarily as a partnership under U.S. tax law.
U.S. multinationals can also create corporate subsidiaries in the foreign country treated as corporations under the tax law of both the foreign country and the U.S., with possibly two levels of income taxation in the foreign country plus U.S. income taxation of earnings repatriated to the U.S. as dividends.
Under U.S. entity classification rules, certain types of entities can “check the box” to elect their classification to be taxed as a corporation with two levels of tax, a partnership with pass-through taxation, or even be disregarded for U.S. federal income tax purposes. The check the box election allows U.S. multinationals to engage in more effective global tax planning.
Toll charges, transfer pricing and treaties
When establishing a foreign corporate subsidiary, the U.S. multinational will likely need to transfer certain assets to the new entity to make it fully operational. However, in many cases, the U.S. multinational cannot perform the transfer without recognizing taxable income. In the international context, the IRS imposes certain outbound “toll charges” on the transfer of appreciated property to a foreign entity, which are usually provided for in IRC Section 367 and subject to various exceptions and nuances.
Instead, the U.S. multinational may prefer to license intellectual property to the foreign subsidiary for a fee rather than transfer the property outright. However, licensing requires the company and foreign subsidiary to adhere to transfer pricing rules, as dictated by IRC Section 482. The U.S. multinational and the foreign subsidiary must interact in an arms-length manner regarding pricing and economic terms. Furthermore, any such arrangement may attract withholding taxes when royalties are paid across a border.
Are you GILTI?
Certain U.S. multinationals opt to focus on deferring the income recognition at the U.S. level. In doing so, they simply leave overseas profits overseas and delay repatriating any of the earnings to the U.S.
Despite the general merits of this form of planning, U.S. multinationals will be subject to certain IRS anti-deferral mechanisms, commonly known as “Subpart F” and GILTI. Essentially, U.S. shareholders of certain foreign corporations are forced to recognize their pro rata share of certain types of income generated by these foreign entities at the time the income is earned instead of waiting until the foreign entity formally repatriates the income to the U.S.
The end goal
Essentially, all effective international tax planning boils down to treasury management. Effective and early tax planning can properly allow a company to better achieve its initial goal: profitability.
If global expansion is on the horizon for your company, consult a licensed professional for advice concerning your specific situation.
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