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Fraud Attacks Often Come From Unexpected Places – Can Predictive Analytics Help?

Jerome Pugnet

Looking at companies’ experiences, of various sizes and across all industries, I think we would all agree that fraud attacks often don’t come from where one would expect! Companies still rely too much on guesswork and empiric methods while investigating potentially fraudulent transactions.

And to make things worse, fraud patterns evolve quickly and constantly. Thus, as companies put in place measures to prevent fraud, perpetrators quickly adapt and find ways to circumvent them. There’s clearly a need for better processes and tools to enhance their fraud detection and investigation.

Investigators’ experience isn’t sufficient anymore

To analyse and understand how and where fraud happens, one can’t just rely on the experience and intuitions of even the best investigators, or the analysis of standard fraud reports and basic metrics. Also, the more common analytical tools appear ineffective to scan very high and fast-growing volumes of data – where critical information to understand fraud patterns and hidden paths is buried.

Moreover, the range of data to examine to properly identify fraud trends is increasingly diverse – structured and unstructured. More than ever, fraud detection is a Big Data problem!

Fast-developing predictive technologies offer great potential for improvement

On the other hand, predictive analysis technologies are fast developing, becoming more widely available and easier to use, yet more powerful. They can help companies get deep insights into how and where fraudulent transactions originate, and analyze changing fraud patterns, in order to enhance their fraud detection strategies and adapt faster to new types of attacks.

So the combination of traditional fraud management solutions complemented by predictive analytics not only enhances capabilities to detect fraud, but also contributes to better prevention of potential future fraud. It enables a deeper, more forensic approach against fraud, helping users to improve the effectiveness of their investigations by better focusing on new types of fraud risks, and continuously updating and refining their fraud detection strategies using the data from predictive analyses.

Today’s best fraud management and predictive analytics solutions have many benefits. They:

  • Identify fraud patterns and trends more precisely: where fraud comes from, how it happens, who is involved, what areas of the business it impacts, and so on.
  • Enable going after the less known and more complex patterns and networks, and detecting earlier to minimize the damage of cleverly hidden suspicious transactions.
  • Provide the needed capabilities to analyze a wide variety and very high volume of data very fast, leveraging in-memory computing technology.
  • Help fraud investigators by reducing false alerts resulting from inadequate fraud detection mechanisms— a critical issue today for many fraud investigators as they’re faced with an excessive workload of potential alerts to analyse, and wasted efforts as many turn out to be false positives.

Can predictive analytics benefit a wider audience?

The innovation brought by predictive analytics touches many other areas of the business, and in areas such as governance, risk and compliance (GRC), its use will develop to enable better predictability of risk, increased insight in areas of control weakness, support for internal audit programs, and so on.

These multiple applications create a high demand for experts such as data analysts and specialized business analysts, but the scarcity and high cost of these resources pushes for better usability of the tools. In the area of fraud in particular, invaluable expertise resides within fraud investigation teams who don’t have these skills as their primary asset.

For them, and others, it’s important that new predictive technologies become approachable for the non-experts, and more readily consumable by their most interested audience—which is just what the latest generations of predictive technologies enable.

For more on security strategies, see Cybersecurity: Is It Time To Change Our Mindset?

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Jerome Pugnet

About Jerome Pugnet

Jérôme Pugnet is a senior director of GRC Product Marketing at SAP SE, based in London, and has over 12 years of experience in risk and compliance management, business process control, IT governance, fraud and audit management domains, in particular in the financial services industry. He has over 16 years of previous experience on financial software and ERP, in implementation engagements and pre-sales advisory roles.

Canada's BC Hydro Shows How Complex Supply Chain Is Done

John Graham

With 56,000 GWh of electricity produced per year, close to 300 substations, 18,500km of transmission lines, 60,000km of overhead and underground distribution lines, 300km of underground and submarine transmission cables, you’d probably say BC Hydro sounds like a big operation, right?

Well, if you’re generating, purchasing, and delivering electricity to 95% of British Columbia’s 4 million people spread across the vast expanse of some of the world’s most unforgiving terrain, “big” tends to be the only option.

BC Hydro, a provincial Crown corporation that reports to the BC Ministry of Energy and Mines, has a workforce of close to 6,000 people across offices in more than 100 communities throughout the province.

With such a huge operation to manage, any opportunities to improve reliability and efficiency are valuable. That’s why BC Hydro’s electric transmission system is connected to the transmission systems of neighbouring province Alberta to the east and the U.S. state of Washington to the south.

This is great for trade, which allows BC Hydro to run an overall tighter ship, but it adds to what is already a great challenge in managing a sprawling and complex supply chain. The organization spends more than $2 billion per year. Whom it buys from, how it buys it, and even when it buys it, all have an impact on costs and ultimately the prices it can offer customers.

The sheer scope of BC Hydro’s supply chain means it’s always been a challenge to manage supplier relationships – making sure they’re paid on time and having solid policies and controls that cover the entire supply chain.

BC Hydro’s Supplier eCommerce manager Hanif Dhrolia was well aware of this problem – one faced and handled with varying degrees of success by most large organizations – and set out to find a way to solve it.

A few years ago, BC Hydro kicked off a pilot program on the Ariba Network, a cloud-based B2B marketplace where buyers and suppliers can do business within a single, networked platform. Initially, a small selection of key suppliers was brought on board to test the waters, and gradually more were added as the approach proved successful.

“Early on there was some reluctance from both suppliers and internal stakeholders to move supplier transactions to a cloud network. Some didn’t want to mess with the way their invoicing was done, and others saw it as extra work,” said Hanif.

While change is often met with resistance, Hanif maintained a firm belief that everyone would eventually appreciate the long-term benefits. His instincts were right; all involved have seen how the platform’s invoice compliance – i.e. getting it right the first time – saves effort and money in the end.

It turns out that managing orders and invoicing over a business network in the cloud has exceeded Hanif’s expectations. His target was to have at least 93% of invoices paid on time; he reached 95%. BC Hydro is saving $1 million a year in accounts payable costs and is also finding opportunities to cut spending through dynamic discounting over the network.

For Hanif, success is not only about saving money, but also about improving supplier relationships. “The benefits to our suppliers of an e-commerce platform are the increased speed and frequency of on-time payments, the ability to track invoices and orders online in one place, fewer invoice exceptions, and paperless, environmentally friendly trade.”

It all adds up to a happier and healthier supply chain for BC Hydro, and has cemented Hanif’s place as a digital supply chain pioneer in Canada.

Natural resources are dwindling, but digitizing the supply chain helps companies preserve resources and see huge savings. Get more insight in the white paper Live Business: Creating Digital Supply Networks.

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John Graham

About John Graham

John Graham is president of SAP Canada. Driving growth across SAP’s industry-leading cloud, mobile, and database solutions, he is helping more than 9,500 Canadian customers in 25 industries become best-run businesses.

Consumer-Driven Digital Enterprise: The Digital Future Of Consumer Products

Jim Cook

Across industries, there’s a lot of talk about how digital is rewriting the rules of engagement.

We are shown examples of how digital disruption is impacting almost every aspect of businesses – from reinventing business models to transforming business processes. Re-imagining a business platform is almost a requirement in today’s consumer-led and data-driven economy. (You know the businesses that are quoted in every article on digital.)

A key question here, though, is: whether the consumer products industry is indeed facing digital disruption, or does it really need deeper digital innovation? Disruption turns an industry on its head by offering consumers something that previously did not exist, while innovation enhances an existing value proposition – making it better, faster, or cheaper.

It is important to distinguish between the two, because hype often causes businesses to overlook the true value of digital transformation. Companies may presume such radical changes have nothing to do with them, especially if they are already in a dominant market position. So while digital is dramatically changing industries such as retail and healthcare, the disruption in the consumer product industry may not be as severe – not yet anyway. Instead, what consumer products businesses should focus on is how they can transform digitally to gain the capacity to build and grow “live brands.” This is preparation and not protectionism.

Create direct customer experiences: Secure the dominant market position

The digital age has fundamentally shifted customer and consumer expectations. Consumers increasingly value outcomes over products. To build ongoing engagement and loyalty, consumer products companies need to sense and engage consumers and customers in the moment, i.e. build “live brands” by seamlessly delivering highly personalized experiences – anytime, anywhere.

This ability to create direct customer experiences helps consumer products companies create a sharper competitive edge to secure dominant market positions. Leading consumer products companies know this well.

Red Bull sets a fine example in creating direct customer experiences to protect and strengthen its brand. Today, it has moved beyond a beverage company into a content media company spanning web, social, film, print, music, and TV – creating brand experiences of exhilaration and adventure. Red Bull collects data from every touch point that it has with the consumer, building an enhanced profile of every individual so that it can respond with products that consumers desire – whenever and how they want them.

Procter & Gamble recently launched an online, direct-to-consumer subscription business for its Tide Pods (its highest-priced laundry detergent). The service (currently only available in Atlanta), branded Tide On Demand, offers free shipping of Tide Pods at regular intervals. P&G has also been testing its delivery laundry service – Tide Spin – in Chicago. While the direct-to-consumer services may not form a bulk of its revenue, they allow P&G to quickly build a live understanding of its customers, their preferences and habits, and then hone in on these insights to create new offerings that customers want.

Build a real-time supply chain: Support lasting customer loyalty

As consumer products companies move towards sensing and engaging customers in the moment, they also need to ensure a fast and profitable response to dynamic demand.

This necessitates connecting customer insights that brand owners have collated and analyzed with supply chain insights to accelerate time to market. Ultimately, it is about transforming previously linear supply chains into customer-centric demand networks – where demand information is captured through new signals from various sources (such as retailers, wholesalers, sites like Amazon, directly from customers, or the Internet of Things) and fulfilled through the orchestration of a network of internal and external partners.

With that, consumer product companies can start getting answers to questions such as:

  • What are my short-, mid-, and long-term views of expected demand across channels?
  • How can I combine supply chain planning with strategic, financial, sales, and operational goals?
  • How can I extend planning by collaborating with customers, partners, and suppliers?
  • How can the company translate the plan into actionable targets for fulfillment systems?

All these should go full circle to help make manufacturing more responsive, optimizing capacity to help ensure availability of finished goods produced just-in-time to meet demand, thereby also lowering inventory costs.

Consumer products companies need to consider how they can create the digital future today. We invite you to learn more about digital transformation for the consumer products industry, where you will get access to valuable resources including whitepapers and customer case studies.

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Jim Cook

About Jim Cook

Jim Cook is the Industry Advisor for consumer industries in South East Asia, with over 20 years’ experience of IT and business consulting. He has held various roles from solution architect, project and program management, business development as well as managing an SAP partner organisation. Jim is passionate about transformation within consumer driven organisations. Jim is particular interested in customer engagement solutions and the value that can be achieved from end to end SAP deployments.

How Emotionally Aware Computing Can Bring Happiness to Your Organization

Christopher Koch


Do you feel me?

Just as once-novel voice recognition technology is now a ubiquitous part of human–machine relationships, so too could mood recognition technology (aka “affective computing”) soon pervade digital interactions.

Through the application of machine learning, Big Data inputs, image recognition, sensors, and in some cases robotics, artificially intelligent systems hunt for affective clues: widened eyes, quickened speech, and crossed arms, as well as heart rate or skin changes.




Emotions are big business

The global affective computing market is estimated to grow from just over US$9.3 billion a year in 2015 to more than $42.5 billion by 2020.

Source: “Affective Computing Market 2015 – Technology, Software, Hardware, Vertical, & Regional Forecasts to 2020 for the $42 Billion Industry” (Research and Markets, 2015)

Customer experience is the sweet spot

Forrester found that emotion was the number-one factor in determining customer loyalty in 17 out of the 18 industries it surveyed – far more important than the ease or effectiveness of customers’ interactions with a company.


Source: “You Can’t Afford to Overlook Your Customers’ Emotional Experience” (Forrester, 2015)


Humana gets an emotional clue

Source: “Artificial Intelligence Helps Humana Avoid Call Center Meltdowns” (The Wall Street Journal, October 27, 2016)

Insurer Humana uses artificial intelligence software that can detect conversational cues to guide call-center workers through difficult customer calls. The system recognizes that a steady rise in the pitch of a customer’s voice or instances of agent and customer talking over one another are causes for concern.

The system has led to hard results: Humana says it has seen an 28% improvement in customer satisfaction, a 63% improvement in agent engagement, and a 6% improvement in first-contact resolution.


Spread happiness across the organization

Source: “Happiness and Productivity” (University of Warwick, February 10, 2014)

Employers could monitor employee moods to make organizational adjustments that increase productivity, effectiveness, and satisfaction. Happy employees are around 12% more productive.




Walking on emotional eggshells

Whether customers and employees will be comfortable having their emotions logged and broadcast by companies is an open question. Customers may find some uses of affective computing creepy or, worse, predatory. Be sure to get their permission.


Other limiting factors

The availability of the data required to infer a person’s emotional state is still limited. Further, it can be difficult to capture all the physical cues that may be relevant to an interaction, such as facial expression, tone of voice, or posture.



Get a head start


Discover the data

Companies should determine what inferences about mental states they want the system to make and how accurately those inferences can be made using the inputs available.


Work with IT

Involve IT and engineering groups to figure out the challenges of integrating with existing systems for collecting, assimilating, and analyzing large volumes of emotional data.


Consider the complexity

Some emotions may be more difficult to discern or respond to. Context is also key. An emotionally aware machine would need to respond differently to frustration in a user in an educational setting than to frustration in a user in a vehicle.

 


 

download arrowTo learn more about how affective computing can help your organization, read the feature story Empathy: The Killer App for Artificial Intelligence.


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Christopher Koch

About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

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What Will The Internet Of Things Look Like In 2027? 7 Predictions

Tom Raftery

Recently I was asked: Where do you see the Internet of Things in 10 years?

It is an interesting question to ponder. To frame it properly, it helps to think back to what the world was like 10 years ago and how far we have come since then.
iPhone launch 2007

Ten years ago, in 2007 Apple launched the iPhone. This was the first real smartphone, and it changed completely how we interact with information.

And if you think back to that first iPhone—with its 2.5G connectivity, lack of front-facing camera, and 3.5-inch diagonal 163ppi screen—and compare it to today’s iPhones, that is the level of change we are talking about in 10 years.

In 2027 the term Internet of Things will be redundant. Just as we no longer say Internet-connected smartphone or interactive website because the connectedness and interactivity are now a given, in 10 years all the things will be connected and the term Internet of Things will be superfluous.

While the term may become meaningless, however, that is only because the technologies will be pervasive—and that will change everything.

With significant progress in low-cost connectivity, sensors, cloud-based services, and analytics, in 10 years we will see the following trends and developments:

  • Connected agriculture will move to vertical and in-vitro food production. This will enable higher yields from crops, lower inputs required to produce them, including a significantly reduced land footprint, and the return of unused farmland to increase biodiversity and carbon sequestration in forests
  • Connected transportation will enable tremendous efficiencies and safety improvements as we transition to predictive maintenance of transportation fleets, vehicles become autonomous and vehicle-to-vehicle communication protocols become the norm, and insurance premiums start to favor autonomous driving modes (Tesla cars have 40% fewer crashes when in autopilot mode, according to the NHTSA)
  • Connected healthcare will move from reactive to predictive, with sensors alerting patients and providers of irregularities before significant incidents occur, and the ability to schedule and 3D-print “spare parts”
  • Connected manufacturing will transition to manufacturing as a service, with distributed manufacturing (3D printing) enabling mass customization, with batch sizes of one very much the norm
  • Connected energy, with the sources of demand able to “listen” to supply signals from generators, will move to a system in which demand more closely matches supply (with cheaper storage, low carbon generation, and end-to-end connectivity). This will stabilise the the grid and eliminate the fluctuations introduced by increasing the percentage of variable generators (such as solar and wind) in the system, thereby reducing electricity generation’s carbon footprint
  • Human-computer interfaces will migrate from today’s text- and touch-based systems toward augmented and mixed reality (AR and MR) systems, with voice- and gesture-enabled UIs
  • Finally, we will see the rise of vast business networks. These networks will act like automated B2B marketplaces, facilitating information-sharing among partners, empowering workers with greater contextual knowledge, and augmenting business processes with enhanced information

IoT advancements will also improve and enhance many other areas of our lives and businesses—logistics with complete tracking and traceability all the way through the supply chain is another example of many.

We are only starting our IoT journey. The dramatic advances we’ve seen since the introduction of the smartphone—such as Apple’s open-sourced ResearchKit being used to monitor the health of pregnant women—foretell innovations and advancements that we can only start to imagine. The increasing pace of innovation, falling component prices, and powerful networking capabilities reinforce this bright future, even if we no longer use the term Internet of Things.

For a shorter-term view of the IoT, see 20 Technology Predictions To Keep Your Eye On In 2017.

Photo: Garry Knight on Flickr

Originally posted on my TomRaftery.com blog

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Tom Raftery

About Tom Raftery

Tom Raftery is VP and Global Internet of Things Evangelist for SAP. Previously Tom worked as an independent analyst focussing on the Internet of Things, Energy and CleanTech. Tom has a very strong background in social media, is the former co-founder of a software firm and is co-founder and director of hyper energy-efficient data center Cork Internet eXchange. More recently, Tom worked as an Industry Analyst for RedMonk, leading their GreenMonk practice for 7 years.