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MONETISING BIG DATA IN RETAIL BANKS STARTS WITH A BETTER CUSTOMER EXPERIENCE

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Davy Nys, Vice President of EMEA & APAC, Pentaho

Retail banks are starting to view big data as a promising asset class that can provide new revenue streams. However as the government’s recent pause on the NHS Care.data scheme proves, even when organisations intend to use data to benefit society and it’s anonymised, consumers are still wary. Retail banks, which have been wracked by scandals relating to PPI fraud, LIBOR rigging, unpopular bonus schemes and IT failures, need to think beyond upselling and cross-selling and consider how big data analytics can repair trust and improve the whole customer experience.

Davy Nys, Vice President Of EMEA & APAC, Pentaho

Davy Nys, Vice President Of EMEA & APAC, Pentaho

Retail banks are indeed under more pressure than ever to use their valuable data to come up with more competitive customer offerings. With UK household disposable incomes at their lowest point since 1987 (ONS figures as of Q1 2013) more consumers are using resources like switching websites and tuning into programmes like Moneybox to take a more active role in managing their finances. Although consumers are still slow to change their current accounts, when it comes to other financial products and loans, this is changing thanks to initiatives like The Payment Council’s recently launched Current Account Switch Service. Some are evaluating new players like peer-to-peer lending services Zopa and RateSetter and using personal finance management software like Intuit’s Mint.

So with competition and awareness heating up, how can retail banks monetise their customer data to gain marketshare without jeopardising already fragile customer trust? The best way to start is to use data to give customers something they genuinely want! Fortunately there’s one glaring thing that falls into that category: integrating financial product and service portfolios into a ‘360 degree view’ so that they are easier for customers to manage. Every banking customer has a story about when they called their online bank manager to enquire about, say, their buildings and contents insurance, and was swiftly transferred to another department (or automated voicemail system). This, despite having been sold on the promise that they would get a seamless, integrated customer experience.

To varying degrees, banks have started to integrate their core retail products like current, savings and mortgage accounts into single views. However customers increasingly expect to be able to see, for example, insurance policy details and renewal dates so they have the visibility to compare products, negotiate fees and read the latest terms and conditions. Some banks already fearing for their reputations, have been afraid to carry out further integration for fear that data will leak out of legacy IT silos and threaten data privacy and security. Other banks feel threatened by greater transparency and the giving customers more information to help them ‘shop around’.

These are valid fears, however given all the high-profile security failures and breaches that have happened recently, these no longer support inaction. The reality is that many banks run on ancient IT infrastructures riddled with risks and costs, both of which get passed on to customers. Furthermore, as it dawns on customers that their financial products aren’t truly integrated but merely ‘white-labelled,’ they no longer see the point in paying any kind of premium to buy services from a single provider and are much more likely to shop around.

A bigger picture

I want to be very clear that monetising big data is not just about making it easier to upsell insurance to a mortgage customer. It’s about offering the kind of exceptional personal service and experience that ultimately leads to the ‘Valhalla’ of customer value pricing (CVP), or maximising the total value of a customer to a bank throughout all interactions and transactions.

CVP is a relatively simple idea and will be familiar to most readers: by working out what different customers need and integrating that knowledge throughout all its interactions, a bank should be able to improve customer service and loyalty as well as increase its own profitability by optimising pricing for customer value. Simple though it may sound, this has eluded retail banks for years because they have set pricing using assumptions that are too generic and crucially, focused more on growing revenue than adding customer value. Big data analytics offers an important technological solution to help resolve this dilemma.

How big data integration and analytics supports CVP

Unlike other industries that offer multiple services to customers such as broadband providers, retail banks uniquely possess very concrete data about exactly what their customers have purchased, when and how often. This means retail banks are have the best data available for building detailed customer profiles and tailoring product and service offerings accordingly. So how do modern big data integration and analytics tools support this? Here are just a few ways:

Supporting a two-way, 360-view

The most fundamental service that benefits the retail bank and its customers is the ability to offer that integrated 360-degree view of each customer’s entire portfolio I described earlier. This view also needs to run both ways! Yes, banks should have that holistic view of its customers, but similarly customers increasingly expect that same visibility of their products and services. This includes being able to use a single password to sign in and view everything through a clear and simple dashboard. Customers who prefer to deal in person or over the phone should get a similarly integrated experience and not have to be transferred to people in other departments using completely non-integrated IT systems. This 360-view is the prerequisite to being able to monetise data more profitably in the future.

As mentioned before, many banks still fear that data will leak out of their ‘secure’ silos if they attempt to integrate it into new applications that improve the experience for customers or their bank managers. However sophisticated new data integration tools make it possible for banks to blend data ‘at the source’ without having to first move it into a different ‘staging area’. These same tools also make it possible for banks to set up smart rules to ensure that data is handled according to local and European data governance rules, virtually eliminating the risk of compliance and security breaches.

Lower costs

Retail banks are harshly criticised for passing on high operating costs to customers by stealth, whether it be through hidden transaction fees or selling products customers don’t need. New players in the market can offer customers better value, in part because they use modern, cost-effective IT infrastructures. Data storage is one of the most expensive and escalating components of IT spend so consider this: according to a report (October 2013) by Cloudera and Syncsort, to store one Terabyte of data in a mainframe costs anywhere from $20,000-100,000. That same data costs roughly $15,000-80,000 to store in a data warehouse. However, it only costs $250-$2500 to store it in a Hadoop cluster. That’s anywhere from six to 400 times cheaper than the alternatives! Big data infrastructure and tools, which are based on open standards, generally cost much less than their legacy, proprietary alternatives.

Smarter offers

To demonstrate how far banks are from being able to make smart offers today, in a recent US Gallup poll of 9000 people, it transpired that customers were being so poorly targeted that 53 percent of those surveyed reported already owning the products that were being marketed to them! Clearly, with all the data banks have available, they can do much better. For instance if a bank can see from a credit card statement that one of its customers has just purchased an expensive bicycle or rare painting, that customer’s manager could recommend a more comprehensive buildings and insurance policy to make sure those items were covered. Similarly if a credit card statement indicated that a customer regularly goes snowboarding in the Alps, the customer’s manager could suggest a travel insurance policy that covers winter sports. Even if banks aren’t ready to switch to modern IT architectures today or prefer to migrate over time, new tools are available that enable safe, cost-effective and easy data blending, without needing to move data out their existing systems.

Customer-friendly fraud detection

For the past five years I have been travelling to Orlando in February for our company’s kick-off meeting and every year, without fail, my credit card provider flags my card as potentially being used for fraudulent transactions. Surely, it can see a pattern here by now! Getting smarter about using data for fraud detection is a simple way banks can improve the customer experience by giving the impression that they care just as much about the customer experience as they do its own risk.

Measuring customer sentiment

According to a recent survey by Bain and Company, the rewards of securing greater customer loyalty can be substantial, around $10,000 more in net present value over the lifetime of an affluent ‘promoter’ customer versus one that is a ‘detractor’ (note: US data). But most banks go about measuring customer satisfaction in a haphazard, outdated way. Retail banks are crazy for surveys, with some banks’ customers being invited to complete a survey after every transaction. I personally find these annoying and either ignore them or complete them so quickly that they are probably not very useful. A much more revealing and less intrusive way to establish customer sentiment is to combine less frequent, more detailed surveys with social and online content that customers voluntarily publish. Big data analytics tools can help mash up these different data sources to help banks continually design better services.

Beyond Valhalla

Retail banks have considerable work to do to build the infrastructures and transform their cultures so that they can deliver the integrated, 360 customer views that will serve as the foundation for the ‘Valhalla’ that is CVP. I firmly believe it’s worth the effort because beyond that the rewards are even greater. For example, when customers trust their banks enough to allow them to share data with their favourite retailers, data could have a very high monetary value indeed. Furthermore as the trend in omni-channel banking grows to include things like ‘smart ATMs,’ touch screen walls, mobile applications and kiosks the opportunity to create sophisticated service experiences driven by high quality, integrated data are practically limitless.

But remember, majestic structures like Valhalla can only be built upon strong foundations. Retail banks need to figure out how to monetise their own data, before they can even think about commercialising it externally. Fortunately the right tools are available in the market today to embark on this journey.

big data in retail banking

big data in retail banking

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Deloitte: Middle East organizations need to rethink their workforce in the wake of COVID-19

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Deloitte: Middle East organizations need to rethink their workforce in the wake of COVID-19 1

Organizations in the Middle East have had to take immediate actions in reaction to the COVID-19 pandemic, such as shifting to remote and virtual work, implementing new ways of working and redirecting the workforce on critical activities. According to Deloitte’s 10th annual 2020 Middle East Human Capital Trends report, “The social enterprise at work: Paradox as a path forward,” organizations now need to think about how to sustain these actions by embedding them into their organizational culture.

“COVID-19 has created a clarifying moment for work and the workforce. Organizations that expand their focus on worker well-being, from programs adjacent to work to designing well-being into the work itself, will help their workers not only feel their best but perform at their best. Doing so will strengthen the tie between well-being and organizational outcomes, drive meaningful work, and foster a greater sense of belonging overall,” said Ghassan Turqieh, Consulting Partner, Human Capital, Deloitte Middle East.

According to the Deloitte report, many organizations in the Middle East made quick arrangements to engage with employees in the wake of the pandemic through frequent communications, multiple webinars where senior leaders addressed employee concerns, virtual employee events, manager check-ins, periodic calls and other targeted interactions with the workforce.

The report also discussed how UAE and KSA governments have reexamined work policies and practices, amended regulations and introduced COVID-19 initiatives to support companies and the workforce in the public and private sectors. Flexible and remote working, team-building and engagement activities, well-ness programs, recognition awards and modern workspaces are among the many things that are now adding to the employee experience.

Key findings from the Deloitte global report include:

  • Only 17% of respondents are making significant investments in reskilling to support their AI strategy with only 12% using AI primarily to replace workers;
  • 27% of respondents have clear policies and practices to manage the ethical challenges resulting from the future of work despite 85% of respondents saying the future of work raises ethical challenges;
  • Three-quarters of leaders are expecting to source new skills and capabilities through reskilling, but only 45% are rewarding workers for the development of new skills; and
  • Only 45% of respondents are prepared or very prepared to take advantage of the alternative workforce to access key capabilities despite gig workers being likely to comprise 43% of the U.S. workforce this year according to the Bureau of Labor Statistics.

“Worker well-being is a top priority today, and similarly to the rest of the world, companies in the Middle East are focusing their efforts to redesign work around well-being by understanding workforce well-being needs,” said Rania Abu Shukur, Director, Human Capital, Consulting, Deloitte Middle East.

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One in five insurance customers saw an improvement in customer service over lockdown, research shows

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SAS research reveals that insurers improved their customer experience during lockdown

One in five insurance customers noted an improvement in their customer experience over lockdown, according to research conducted by SAS, the leader in analytics. This far outweighed the 11% of customers who felt it had deteriorated over the same period.

This is positive news for insurers during such challenging times, with 59% of customers also saying that they would pay more to buy or use products and services from any company that provided them with a good customer experience over lockdown.

The improvement in customer experience also coincides with a rise in the number of digital customers. Since the pandemic started, the number of insurance customers using a digital service or app has grown by 10%. Three-fifths (60%) of new users plan to continue using these digital services moving forward.

However, while the number of digital users grew over lockdown, half of the insurance customer base has not yet chosen to move to digital insurance apps or services.

Paul Ridge, Head of Insurance at SAS UK & Ireland, said:

“It’s impressive that there was a net improvement in customer experience during lockdown, despite the challenges the industry was facing with a transition to remote working and increased claims for things like cancelled holidays. While many were forced to wait on customer help lines for long periods, part of the improvement may be explained by even a small (10%) increase in the number of digital users.

“However, it’s clear that a huge number of customers are still yet to make the move online. It’s vital that insurers provide the most accurate, timely and relevant offerings to customers, and this is best achieved by having additional insight into online customer journeys so they can understand them better. Using analytics and AI, insurers can seize this opportunity to digitalise their customer experience and offer a more personalised approach.”

Meanwhile, for insurers that fail to offer a consistently satisfactory customer experience, the price could be severe. A third (33%) of customers claimed that they would ditch a company after just one poor experience. This number jumps to 90% for between one and five poor examples of customer service.

For more insight into how other industries across EMEA performed during lockdown, download the full report: Experience 2030: Has COVID-19 created a new kind of customer? 

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The power of superstar firms amid the pandemic: should regulators intervene?

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The power of superstar firms amid the pandemic: should regulators intervene? 3

By Professor Anton Korinek, Darden School of Business and Research Associate at the Oxford Future of Humanity Institute. Gosia Glinska, associate director of research impact, Batten Institute for Entrepreneurship and Innovation, Darden School of Business

Recent news that Apple hit a market cap of USD2 trillion highlights an extraordinary success story: A once struggling computer-maker on the verge of bankruptcy innovates its way to becoming the most valuable publicly traded company in the United States.

Apple’s 13-figure valuation is indicative of a larger trend that is not entirely benign — the rise of a handful of superstar firms that dominate the economy. Over the past three decades, advances in information technology, mainly the Internet, have supercharged the superstar phenomenon, allowing a small number of entrepreneurs and firms to serve a large market and reap outsize rewards. And COVID-19 has greatly accelerated the phenomenon by pushing us all into a more virtual world.

Apple — along with Amazon, Facebook, Google, Microsoft and Netflix — is a case in point. The combined market value of those six companies exceeds USD7 trillion, which accounts for more than a quarter of the entire S&P 500 index. Even amid the pandemic’s economic wreckage, these megacompanies continue to prosper. The combined share price for Apple and its five peers was up more than 43 percent this year, while the rest of the companies in the S&P 500 collectively lost about 4 percent.[1]

Superstar firms can be found in almost every sector of the economy, including tech, management, finance, sports and the music industry. They command increasing market power, which has consequences for technological, social and economic progress. It is, therefore, critical to understand how their advantages arose in the first place.

THE FORCES BEHIND THE SUPERSTAR PHENOMENON

The “economics of superstars” was first studied by the late University of Chicago economist Sherwin Rosen. Forty years ago, Rosen argued that certain new technologies would significantly enhance the productivity of talented workers, enabling superstars in any industry to greatly expand the scope of their market, while reducing market opportunities for everyone else.[2] Digital innovations, including advances in the collection, processing and transmission of information, is what Rosen envisioned would lead to the superstar phenomenon.

Digital technologies are information goods, which are different from the traditional, physical goods in the economy. What it means is that fundamentally different economic considerations apply. Unlike physical goods — a loaf of bread or a car — information goods have two key properties: They are non-rival and excludable. Non-rival means that something can be used without being used up. Excludability means that an owner of digital innovation can prevent others from using it, by protecting it with patents, for example. These two fundamental properties of information goods are what give rise to the superstar phenomenon.

In a working paper I co-authored with Professor Ding Xuan Ng at Johns Hopkins University[3], we described superstars as arising from digital innovations that require upfront fixed costs that allow firms to reduce the marginal costs of serving additional customers.[4] For example, once an online travel agency has programmed its website at a fixed cost, it can easily displace thousands of traditional travel agents without much additional effort, scaling at near-zero cost.

Because a firm can exclude others from using its digital innovation, it automatically gains market power. The innovator then uses that power to charge a mark-up and earn a monopoly rent — basically, a price superstars charge in excess of what it costs them to provide the good — which we call the ‘superstar profit share’.

THE POLICYMAKER’S DILEMMA

In a vibrant free market economy, businesses compete for customers by innovating and improving their offerings while keeping prices low; otherwise, they are displaced by more innovative rivals entering the market. Unfortunately, the increasing monopolization of the economy by technology superstars is weakening the competitive environment around the world.

Monopoly power is the main inefficiency from the emergence of superstar firms, because superstars can exclude others from using the innovation that they have developed.

So, what policy measures can be employed to mitigate the inefficiencies arising from the superstar phenomenon?

We do have antitrust policies designed to promote competition and hence economic efficiency. Authorities could take a drastic measure and break up monopolies. Or they could tax all those excess profits megacompanies make.

Another policy to consider involves giving consumers control rights over their data. Right now, only companies have that data, and they are selling it. If you free it up and don’t allow them to sell it anymore, it reduces their monopoly profits. And if you give consumers more freedom over their data, they could, for example, share it with the latest start-up and create a more competitive landscape.

However, such policy remedies can be a double-edged sword. On the one hand, they reduce monopoly rents. On the other hand, they can also reduce innovation.

Innovation requires investments in R&D, which represent a significant sunk cost that only large firms can afford. Government regulations can easily backfire, discouraging large firms from making long-term R&D investments.

What, then, is the best policy intervention? Professor Ding Xuan Ng and I believe that basic research should be public. Digital innovations should be financed by public investments and should be provided as free public goods to all. This would make the superstar phenomenon disappear, and the effects of digital innovation would simply show up as productivity increases.[5]

We live in a brave new world that is increasingly based on information. Because the information economy is different from the traditional economy, antitrust policy should be revamped to reflect that. Instead of worrying about the economy being eaten up by these gigantic monopolies, policymakers need to focus on the question ‘What specific actions can we pursue to make the economy more competitive and efficient?’

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