Fraud is on the rise. Collectively, this global criminal enterprise is hitting financial services firms with a severe one-two punch.
The first punch involves cash. Lots of it. In 2011 alone, fraud losses on UK cards totalled £388 million in 2012, showing a 14 per cent increase from total fraud losses of £341m according to the UK Card Association( ). But the second part of the one-two punch might be even worse. That’s because fraud run amok can cause an immeasurable amount of harm to a bank’s reputation.
Bank fraudsters have gone digital, and keeping up with them has become a monumental task for those firms unwilling to invest in the right security tools. Smart global banks, however, are embracing the benefits of Big Data to stop criminals dead in their tracks. Banks are finding that the most effective tool to combat fraud is to develop algorithmic machine learning programs that out-fox even the most sophisticated digital criminals.
Benefits of Big Data
Machine learning begins with Big Data. True, it’s a term that means different things to different people. But at the core the term represents the notion that to leverage data – large, varying, and fast changing datasets – we need a new set of so-called Big Data technologies. Although these technologies are as varied as Hadoop, In Memory databases, and NoSQL, they collectively shun the idea that traditional relational databases are the gold standard for storing and querying data.
Big Data technologies enable us to extract insights either as visualisations for human consumption or as mathematical equations (what are known as predictive models) for consumption by computers. In the realm of fraud detection, Big Data technologies help us win what’s lately been a losing battle involving three very important data elements: quality, timeliness, and breadth.
Today’s cybercriminals have a leg up on all three of these vital data elements. That’s why it’s essential to develop an integrated fraud prevention plan based on a combination of real-time anomaly detection and machine learning models. Such programs can tap into massive amounts of data created inside and outside the bank, which is the key to successfully curbing fraud in today’s digit age.
Antiquated fraud detection
Fraud detection is a predictive analytics problem. Predictive analytics techniques work by extracting patterns from past datasets to predict the future. These techniques typically assume that the future should mimic the past. For these techniques to be effective, we require accurate, timely, and broad datasets. The incumbent approaches to fraud detection falter on all the three dimensions of data and make the efficacy of current approaches to fraud detection questionable at the very least. Let’s discuss the potential shortcomings of each set:
Quality: The quality of datasets that banks would use in fraud analysis is poor because they didn’t detect all fraud cases. What should have been identified as fraud got tagged as not-fraud. Doing so led to building sub-optimal models with poor predictive quality. A good fraud detection model is one that has high tolerance to outlier cases and can withstand false-negatives without deterioration of the model.
Timeliness: Unlike human consumption patterns that help predict the next product we are likely to buy, fraud patterns can change with time. Fraudsters adopt new tricks as old ones start failing. As a result, there is a strong need to be able to detect new fraud patterns shaping up on the field and then to deploy updated models. Traditional analytical approaches typically take three to six months to develop and deploy into fraud detection systems. This timeframe for banks is laughably slow for a criminal bent on fraud.
Breadth of Data: The effectiveness of fraud detection models increases if we have more data around various scenarios. Weaving a story of the people involved using varying datasets like blogs of Internet activity, mobile interactions, and the data stored in a bank’s system can help carve out a complete story. Models can then improve the accuracy of their predictions. Most fraud detections systems today don’t leverage unstructured data outside a company’s systems.
Analytics are not created equally
Sophisticated companies are machine learning powered by Big Data technologies to build state-of-the-art fraud models. Traditional statistical approaches and modern day machine learning techniques are based on the same mathematics. But the terminology, culture, and toolset used in the two disciplines are so different that it merits treating machine learning as a distinct discipline in itself.
Machine learning has origins in the Artificial Intelligence world. Companies like Google and Amazon utilise machine learning to build automated predictive models.
For fraud detection, machine learning powered by Big Data technologies has a unique advantage in relation to the timeliness issue. Machine learning is essentially a group of algorithms that show improvement of the predictive model when more data is fed into those algorithms. The algorithms learn from data and keep on improving over time (see graph). With Big Data feeding into machine learning algorithms, the efficacy of fraud models improves significantly over time. This is completely opposite of traditional approaches where the model deteriorates over time.
Machine learning s also related to neural networks. Decision trees and random forest methods have also shown better resilience to handling poor quality datasets inherent in fraud problems. For example, experts cite random forest as the most successful technique used by data scientists in winning predictive modeling competitions hosted on Kaggle.com
Data beats mathematics
There is only so much you can do by optimising the mathematics that goes into building predictive models. Ultimately, what really gets a lift in the accuracy of models is more data (size and breadth). Banks collect a lot of data from customers through an array of service preferences in order to know them better. They also have systems in place to monitor or gather data on daily transactions (deposits, withdrawals, etc.) of customers. Banks can also monitor data from blogs, chat archives, feedbacks, survey responses and other forms of structured and unstructured data from multiple channels.
Numerous research papers (e.g., Unreasonable Effectiveness of Data) and enterprise scenarios like Google search have proved that feeding more data (size and breadth) into algorithms leads to a greater lift in model performance then spending more time in optimising the models. Not surprisingly, therefore, we see a big difference by using Big Data technologies for fraud detection. The ability to run models on population rather than samples combined with the ability to tap into no-traditional data formats available from social networks and emails creates a capability for fraud detection that has not existed … until now.
Global corporations measure success a number of ways. Accountants, for instance, can demonstrate year-over-year financial gains on income statements. Then there are the intangible aspects of success – what an accountant might call goodwill. Elements like reputation and intellectual capital might take decades for a company to build up. Yet sophisticated fraudsters are damaging the reputations of once-respected banks by running circles around them in cyberspace. That’s why financial services firms need to utilise Big Data. By leveraging large, diverse, and fast-changing datasets, Big Data technologies take fraud detection leaps and bounds ahead of traditional approaches. By storing and analysing data in new ways, financial institutions can detect fraud in advance and beat criminals with a one-two punch of their own.
About the Authors:
Niraj Juneja is a Principal Consultant in the Infosys’s Management Consulting division. His focus is on using data science techniques to enable better decision making for Financial Services firms. As a practitioner of analytical techniques that use Big Data technologies, Niraj believes that the traditional approaches to decision making that rely heavily on recommendations from gurus and human intuition will undergo a major shift towards “data driven” decision making enabled by Big Data technologies.
Niraj has several years of experience consulting for Fortune 100 Financial services firms and has successfully executed large scale data driven business transformation programs.
Kiran Kalmadi is a Principal Consultant in the Financial Services and Insurance (FSI) business unit and leads the FSI Research team. He has around 13 years’ experience in bespoke research and analysis for strategy development, consulting, marketing and business development.
Kiran has worked extensively in the retail banking and payments domain and has been involved in developing research-based consultative insights and analysis for business pursuits and client engagement.He has a keen interest in Social Media, Payments, Analytics, Internet, and Mobile Banking and its adoption by financial institutions.
The importance of app-based commerce to hospitality in the new normal
By Jeremy Nicholds CEO, Judopay
As society adapts to the rapidly changing “new normal” of working and socialising, many businesses are working tirelessly to ensure that they have all the necessary safety precautions in place to keep trading. One such sector is hospitality, but the way it typically operates now looks very different to what we were used to seeing prior to the pandemic.
Many pubs, restaurants and other hospitality establishments have now been open for a few months since lockdown, providing much relief and enjoyment to many consumers, as well as getting many employees back into work. However, a core component for businesses to maintain trading in these times is to ensure the crucial safety of staff and customers.
Payments are playing an important role in this and we’re seeing payment technology being implemented in new and unique ways to help make the hospitality sector as safe as possible. One such technology is app-based commerce, which allows businesses to interact with customers in ways that minimises physical contact whilst crucially still enabling engagement.
With table service now mandatory and Test and Trace measures continuing, we’re likely to see this technology being increasingly adopted in the months and years ahead. So, let’s take a look at what its use means for the hospitality industry and beyond and how it lines up with the government’s latest advice for businesses within the sector.
Understanding government guidance
Guidance issued from the UK government expands upon advice already offered by the Prime Minister to the hospitality sector, at the point of reopening back in July. It has been stated that all indoor hospitality is limited to table-service, interaction between staff and customers should be minimised as much as possible, masks are being enforced for indoor hospitality staff and the rule around groups of 6 continues.
At the same time, businesses now have a clear duty to support NHS Test and Trace by collecting names and contact details from customers so they can be reached if a customer/worker tests positive. This is a recent mandatory move having previously been guidance.
What’s more, it’s recognised that payments are a practical tool to help companies adhere to these guidelines. Throughout the pandemic it has emphasised that contactless payments are useful for reducing human interaction and touch points – such as PIN pads.
Early on, we saw the payment industry increase the authentication limit for contactless spending limit from £30 to £45 to help reduce cash purchases, cash machines and PIN pad usage. The Government are strongly encouraging the use of contactless payments in the hospitality sector, however, there’s a big part of the solution that they may have overlooked that can help hospitality businesses meet these guidelines with even greater ease – app-based commerce.
Why use apps?
Apps provide a whole host of benefits and are the perfect tool for not only minimising contact, but also ensuring customers are contactable at a later date, if needs be.
While contactless payments eliminate the need for customers to pay using cash, or touch PIN pads, apps can remove physical human interaction at the point of sale altogether. This is because they enable customers to pay ahead or at the table, meaning they don’t need to leave their seats or regularly interact with staff. And done well they can even be a boost for business, enabling more convenient transactions and higher levels of repeat purchase.
When it comes to ensuring that customers are contactable, apps and e-wallets have a real advantage over traditional card-based transactions and anonymous cash payments. They allow companies to retain details about who has attended an establishment at a given time, enabling them to know whether a customer was present while a person known to be carrying the virus was in the vicinity. The communication advantages of apps also allow establishments to manage their footfall and customer flow.
The role of app-based commerce in the new normal
Apps will become more and more important for all types of businesses, as consumers shift their behaviour towards digital. They represent a new ‘real estate’ for retail and other businesses to manage – to present their brand in the right way, to engage customers and drive transactions.
Recently, we’ve seen Apple support this move towards app-based commerce with the launch of App Clips, further bolstering its use as we emerge from lockdown and encouraging safer and hygienic ways to pay.
App Clips are a great way for consumers to quickly access and experience what an app has to offer. They are fast and lightweight so a user can open them quickly and start and finish an experience from an app in seconds. And when they’re done, the business can offer the opportunity to download the full app from the App Store.
We are also seeing a number of hospitality businesses warming towards the use of app-based commerce and doing a great job of implementing it. The technology has already become central to the safe trading operations of big names in the industry such as Caffè Nero and The Young’s Pub, which are great examples of how to make apps work for your business.
As the industry steadily navigates its way through a new normal of operating, we expect that app-based commerce will skyrocket. In fact, we’ve already seen a great number of businesses throughout different industries expressing interest in the payment method, suggesting that it will play a pivotal role in moving forward. It certainly is a great way for businesses to keep staff and customers safe.
Why the FemTech sector might be the sustainability saviour we have been waiting for
By Kristy Chong, CEO & Founder Modibodi ®
Taking single use plastics out of circulation is no easy feat, but the answer might lie closer than we think
FemTech: The Beginnings
The term FemTech was initially coined to describe the powerful offering from tech start-ups as they ventured into developing revolutionary products centred around women’s health needs. Whilst the beginnings were humble, we have seen a whole host of innovations enter the market which have changed the game for women and business leaders around the globe.
Fast forward to 2020, FemTech is an industry predicted to be worth $50 billion by 2025 and a powerhouse that is not just tackling women’s health issues but also helping to solve major environmental and sustainability crisis that we face today.
The fearless female entrepreneurs have founded and grown businesses that are continuing to help women across the globe deal with issues such as fertility, periods, sexual wellness, pregnancy and many others. And the best is yet to come.
It is a Man’s World
Traditionally, both technology and medical sectors have been very slow in tackling women’s issues and notoriously lagged in developing products and tools that address issues predominantly affecting women. Whilst figures show that women spend 29% more on healthcare than men, only 4% of overall R&D funding goes towards developing products for the women’s sector therefore the market is ripe for disruption.
As a woman, a mother and entrepreneur I knew that like many others I had to take matters into my own hands.
Following an incident with incontinence whilst training for a marathon in 2011 after the birth of my second child, I recognised the need to innovate apparel that offered a dignified, supportive and sustainable solution for women to manage leaks from periods, incontinence and everything in between. After two years of product development and over 1000 scientific tests, I founded Modibodi in 2013 with a long term view of breaking taboos, opening minds and offering a reusable, sustainable option for sanitary products that’s not just for women – but for the benefit of all bodies on this planet and the environment too. Now, we’ve expanded on that notion to support all people, including men who suffer incontinence, sweating and chafing, providing them with a reusable, sustainable option with our Modibodi Men range.
As you can imagine, this was far from simple not just due to tech and business sectors being notoriously dominated by men, with figures showing that 98% of VC funding goes towards male founded products but also because we were not just selling a new brand of lipstick or gym-wear, we had created a whole new product category based on talking about things that made people and retailers uncomfortable.
As a social advocate for women’s health issues and rights I knew that I needed to persevere because the amalgamation between technology and feminism is a major force of social change and one that can have wide scale impact on our world.
The Sustainability Story
The sustainability agenda has really taken off in the last couple of years, especially in our war against single use plastic. But it occurred to me very early on that we are not doing enough and there are still areas that need urgent review.
Very early on in the development stage of Modibodi I knew that sustainable sanitary products could be a game changer in eliminating single use plastics from circulation and whilst the world and respective governments were focusing on plastic straws, I felt the change needed to come from numerous angles and streams of consumerism.
The proof of concept was starring us right in the face, the average woman uses an average of 11,000 disposable feminine hygiene products in her lifetime and these convenient products come with an inconvenient environmental cost. They take 500 to 800 years to biodegrade, which means the first ever tampon and pad is still in landfill. Even more alarmingly, 8% of all waste that enters water treatment works comes from period waste, including non-flushable items such as pantyliners.
This is why I believe that the revolutionary innovations that are born out of the FemTech sector have capabilities to be one of the key drivers of the sustainability agenda. There is something remarkably special about a group of purpose driven businesses that can connect with consumers through a collective set of values to drive change and be a force for good.
As most purpose driven business leaders will tell you, the fight never stops as the world evolves and continues to change. The sheer growth in the FemTech sector and the capabilities developed to date have changed millions of lives around the globe.
As an industry and a movement, we’ve also managed to play our part in driving the sustainability agenda and I will argue that actually the wide scale change and unity needed to continue making strides in eradicating single use plastic from our circulation will come from within the powerhouse that is FemTech.
The sheer capacity for change can be easily demonstrated if we look at the granular data and its potential for growth. If just 100,000 young girls use Modibodi alone from the start of their menstrual cycle, this would prevent 1.1 billion disposable hygiene products from ending up in landfill or 1.5 million garbage bags of waste. As of May 2020, our global base of 500,000 customers alone have prevented an estimated 2.5 million garbage bags of disposable hygiene waste from ending up in landfill or flushed into the ocean.
With the FemTech industry growing at a racing speed, I have no doubt that we are at the tipping point of pioneering wave of inventions that will take the agenda further and have the capacity and means to lead the movement. It is up to the trade organisations and world leaders to recognise the potential that such businesses and brands carry in order help to facilitate its growth trajectory.
Limitless possibilities: Delivering disruption with IoT
By Nick Earle, CEO of Eseye
In the past decade, digital companies like Amazon and Netflix have used data to reinvent products and services in ways no-one imagined possible. Shopping and films were not new concepts, but these companies and many others built hugely successful businesses by disrupting existing industries through connected, personalised, data-driven services.
We are on the brink of a similarly disruptive revolution, as the Internet of Things (IoT) starts doing the same for ‘physical’ businesses – from tennis rackets to coffee machines and industrial machinery – allowing them to offer connected, data-driven, differentiated experiences. This is sometimes referred to as the ‘next Internet’ and IDC predicts that in total there will be 41.6 billion connected IoT devices or “things” by 2025.
Access to this incredibly detailed data on every aspect of how the physical world works will create endless disruptive innovations – from both new and existing companies. This presents limitless opportunities, but also severe threats to companies that wait too long.
A decade ago, many predicted this revolution, but it has taken longer than expected. Despite pockets of innovation, many have struggled to deliver successful IoT projects. We have yet to see the IoT equivalent of Netflix.
There are some obvious reasons for this. Many companies with a long heritage in the physical world find digitisation hard to navigate. Moving from selling units via a capex model to managing a continuously connected, data-driven relationship via an opex model is a big shift – involving new technologies, business processes, skills and management metrics. Concerns about how to do this can cause management paralysis where the outcome is often ‘do nothing and wait’. Arguably a worse approach than trying and failing.
It’s also a culture issue. We don’t like change, it’s difficult and we only do it when we have to. The problem is that when you are the market leader your existing financial metrics often disguise the change that your competitors are implementing in the market. A large installed base of customers will keep generating revenue for a long time and it’s often hard, if not impossible, to recognise the new disruptive business models that are winning the next generation of customers. But as the old saying goes, you overtake on the corners not the straights, and the COVID-19 pandemic has accelerated many digital initiatives not slowed them down. Your business model is being disrupted whether you can see it or not and it’s almost certainly accelerated during 2020.
Another reason is much more basic. Due to the fragmented nature of the Mobile Network industry, where multiple players compete with each other with their proprietary SIMs, the holy grail of ubiquitous global cellular connectivity for each and every device via a single embedded eSIM has not been possible. The reality is no network SIM, even from the largest Tier 1 operators, can deliver more than 90% global coverage, even with extensive roaming arrangements. You don’t want a connected lawn mower which is invisible in 10% of cases, or a connected health monitoring device that misses 10% of emergencies. And to fill that connectivity gap you don’t want to have to use a different operator’s SIM – that just adds complexity, cost and kills the business case. If this connectivity barrier can be removed, then the savings in manufacturing and supply chain costs that can be delivered from moving to single global product SKUs will more than justify the investment in IoT pilots and new product rollouts. This is the problem that Eseye solves and we are currently doing it for more than 2,000 customers worldwide.
I’ve spoken exclusively to IoT industry leaders from Microsoft Azure, EY, Thales, Relayr, and The Chasm Group, to understand the opportunities that IoT offers for companies to create disruptive products and services, and the lessons they’ve learnt delivering digital transformation and disruption through connected devices.
Dr Miroslaw Ryba, Global IoT Leader at EY, explained that: “Disruptive IoT is about taking the sum of thousands of IoT sensors – say in a factory – and combining data to deliver transformational insights. And that the next, exciting phase, will be a new data economy.
“There is [already] an agreement that the user gives up their data in return for a service. Imagine what will happen once that data expands to real-world activities. It will allow the development of whole new classes of products and services aligned to customer needs.”
Tony Shakib, Global IoT Business Acceleration Leader, at Microsoft Azure believes that we’re at an inflection point where some companies are taking investment in IoT infrastructure seriously, allowing them to capture meaningful data, and integrate it into their workflow management systems. Here they can start delivering, and acting on, real-time insights.
He said: “Gradually we’re crossing from the experimental phase to mass adoption” he explains. “Once we get there, we’ll see real change. Once you start connecting devices and using data intelligently, the amount of innovation you can do becomes exponential.”
When moving from incremental advances to big disruptive IoT-driven transformation, Shakib believes the key is cultural change.
He explained: “Tech is not the bottleneck – devices, security, connectivity, and cloud platforms are all there if you know where to look. The problem is people struggling to understand the art of the possible.”
VP of IoT at Thales, Andreas Haegele, unpacks the points of consideration including, security, connectivity and process when trying to maximise the benefits of IoT.
“Most business models of the past – and many today – are ‘sell and forget’. IoT connects your products, which changes what you offer. It creates an ongoing connection between you and the customer allowing you to deliver ongoing services and collect data which provides valuable insights.
“However, there are other factors to consider, namely around process and security. Eseye, for example, offers out-of-the-box connectivity which you can embed in an IoT device and it just works, there is no need for setting up new networks, security protocols, certification with mobile network operators (MNOs), etc. IoT needs security to be embedded from the start as security is very hard to retrofit. There must be a unique identity for every device so they can be managed during their lifetime. And you need to make sure software updates can only be accepted by trusted sources.
“Also, built-in connectivity is central to IoT. Each device needs to consider the right type for them, but I expect most will use cellular eventually, since it removes many roadblocks to uptake. If devices over-complicated connectivity, that’s a major turn off for customers who expect seamless, convenient experiences.”
While Peter Van der Fluit, Principal at Chasm Group, said: “Any company that currently makes or operates a physical product needs to be thinking about IoT. If you don’t connect your product to create a differentiated offer, someone else will.
“To be successful in embracing IoT, or any disruptive technology, companies should divide their business into four ‘Zones’ – an approach established by Geoffrey Moore in his book Zone to Win. Two of these Zones focus on innovation, and two on the core business. Each needs a different leadership style, culture, financing and governance.”
With so much disruption and change thrust upon companies, business models are inevitably going to evolve. Josef Brunner, CEO at Relayr, explained to me how IoT is disrupting business models, forever.
Josef said: “IoT is creating whole new ways of thinking for those who manufacture products, enabling them to change how they sell in a way that works better for them and their customers. This is often talked about as moving from selling products to selling services. We’d go further and say that at its best, IoT is about selling outcomes. Rather than charging an hourly or monthly subscription, the manufacturer can sell the value that is delivered.”
But there are pitfalls to be avoided when switching to a model that sells outcomes. Josef explains: “The main mistake companies make is to think of IoT as a technology project, looking at what tech is available and working out where to deploy it. Instead, they should start with the business problem.
Start by looking at what assets you have, and how they could be used to deliver a better experience for customers. Put the customer need at the centre of that offer. Then look at how tech can enable it.”
The inventors of the internet could never have predicted Uber and Netflix. Likewise, we can only guess at what IoT entrepreneurs will come up with once they have access to data from trillions of devices capturing rich data on every aspect of our lives and businesses. But it’s likely to be an even bigger wave of innovation than the first version of the internet unleashed. There really are no limits.
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