Suburbia is the first Dutch startup ever to be selected for Fintech Business Camp Tokyo, an accelerator program for young fintechs. The two-month program, which will kick off in October, is run by the office of the mayor of Tokyo with Accenture Japan.
“We feel really proud and honored to be the first and only Dutch startup picked for this program,” said Hamza Khan, CEO and founder of Suburbia. “Standing out in a crowded field only proves that our technology is truly innovative and highly scalable – what we’ve built in Europe can work just as well in Asia-Pacific or the Americas… or anywhere!”
Suburbia was selected by the Tokyo Metropolitan Government (TMG) from a pool of over 120 applicants located in 29 countries, alongside 11 other startups. They were reviewed and chosen based on their innovative technologies and business models “which do not yet have a presence in Japan”.
The initiative, first launched in 2017, is part of the Japanese government’s four-year campaign to revitalize Tokyo’s financial sector and cement the city’s status as a global financial hub. TMG considers fintech a key element in achieving its goals. The program aims to provide startups with access to some of the nation’s leading companies and support them with their entry into the market.
Startups that have been accepted into the program are provided with support in localization, mentoring from top Japanese banks, and networking and business matchmaking opportunities. Three of the 19 foreign companies that have participated in the program in the past two years now have a footprint in Japan.
As part of the program, Suburbia will be going to Japan to meet with local companies and investors. This will culminate with a pitch in November where the company will present a business plan developed during the course of the program.
For over the last decade, some of the most successful companies on earth have made their riches by mining user data and selling it to advertisers. The big question is whether this will continue to be a sustainable business model with the ever-mounting scrutiny on data privacy and if not – what’s the alternative?
Many say the Cambridge Analytica scandal sparked a great data awakening by bringing to light the ways in which some companies were amassing and monetizing personal data about their users. As a result, Facebook was recently slapped with a record $5 billion fine and new privacy checks.
This isn’t a problem that is exclusive to the giants of Silicon Valley. In Europe, hefty fines have also recently been meted out to British Airways and Marriott for data breaches. As data protection complaints have doubled year-on-year, regulators will be getting tougher on companies to ensure their compliance with GDPR (General Data Protection Regulation).
Meanwhile, GDPR has driven a global movement as governments outside the EU, from Australia to Brazil, are set to introduce similar data protection regulations.
In addition, GDPR has helped to create greater awareness about data protection among the general public. The European Commission’s March 2019 Eurobarometer survey showed that about 67% of European citizens surveyed know what GDPR is.
The convergence of a compliance culture within organizations, stricter data privacy regulations globally, and consumers becoming more aware of their rights will continue to have a huge impact on businesses that profit from personal data, and even any business which collects it.
The situation demands urgency as the stakes have never been higher. According to a report by Gartner, by 2020, personal data will represent the largest area of privacy risk for 70% of organizations, up from 10% in 2018.
But better privacy for individuals doesn’t mean it’s bad for business. On the contrary, companies can use this opportunity to establish trust with customers while becoming more thoughtful and innovative about their approach to data monetization. For many firms, data monetization has been inextricably linked with the personal data of their customers. However, they could be collecting, generating or archiving other types of non-personal data that could be valuable to certain end users. That is, the alternative data that may even be overlooked by the business generating it.
This data might be structured or unstructured, but new tools and technologies have made it easier to mine and process such data into insights. These insights could serve as timely intelligence to those in other sectors, like economists, analysts or investors looking to identify patterns and trends.
In fact, there are many use cases for such alternative data in the world of investing when every bit of timely information helps to gain an edge. This is where anonymized and aggregated data matters most and personally identifiable information has zero value. What economists and asset managers most want to know is how many soft drinks Coca Cola is selling across Europe this quarter, not whether John Doe bought a Coke.
The growing focus on privacy doesn’t mean data monetization has been taken off the table. Data will always be an important and valuable asset for any organization, but it needs to be harnessed with the full respect of individual rights to privacy.
PSD2: the latest tightening of data regulations will require strategic, operational and infrastructural changes for banks and financial institutions.
Is it an opportunity or a threat though? Judging from current opinion, it appears the financial industry hasn’t quite made up its mind. If there’s anything worse for the sector than a clear and present threat, it’s uncertainty.
In a recent survey conducted by open banking platform Tink, one thing is clear, financial institutions dislike regulation. They named it as the biggest threat to their current business models. With the final PSD2 deadline looming on the horizon, there is little time for firms to get wrapped up in an existential crisis though. Most are soldiering on, despite their doubts, to ensure they can comply with the new directive. They are investing in digitization, greater security and privacy.
However, it’s clear that they need to do more than the bare minimum in order to not only survive, but thrive, in this new ecosystem. For banks, payment service providers (PSPs) and other players, PSD2 unearths an opportunity for them to innovate and compete.
Data should increasingly be viewed as a natural resource like oil. Yes, data is the new oil is a somewhat tiresome cliché, but sitting on an oilfield is not much use unless you have the right tools, infrastructure and capabilities to make something out of it. In that sense, firms need to grapple with how they can turn what is essentially a commodity, into a competitive advantage.
To benefit from the opportunities that will arise from PSD2, there are two key approaches any financial or payments services firms can take in the new landscape:
1. Monetize their data – Increasingly, no one party will have a monopoly on data. This means firms will need to start thinking about how to leverage their distinctive data sets as part of a data monetization strategy – without compromising sensitive personal information.
When it comes to monetizing data, many are enticed by the opportunity, but they may view it as a challenge. They may raise questions over data ownership and privacy.
However, there is great value in anonymized, aggregated information that is used for business or investment insights. In finance, the interest is in identifying broad trends and patterns – the focus is never on the who but the what and how much. That means it’s possible to extract value from this data while preserving privacy.
Outside finance, there are other examples of how sensitive data can be used in a way that benefits the public. For instance, Uber shares anonymized data aggregated from billions of trips taken by its users in order to help urban planning around the world.
Transparent and responsible use of this data can open the door to new revenue streams. Data might not be the core business for many of these firms, but revenue from this can quickly become meaningful as the quantity and quality of data grow over time.
The value of their data can also increase when combined with multiple sources for consumption by third parties.
It can sound counterintuitive to deal with the threat posed by open data by sharing it even more widely. But this allows firms to strengthen existing data and play a more important role in the transactional ecosystem. Payments providers are well-positioned because they have unique insights into both merchants and consumers.
2) Get better customer insights – The changes that will be brought on by PSD2 will show that no incumbent can afford to rest on their laurels. The classic mindset of getting all your financial services from one provider is going to change. Many payment experiences will change and become more seamless.
One hot topic is instant payments. While consumers are the biggest benefactors of this trend, merchants can also benefit from it in a number of ways. Instant payments are data-rich so they can leverage real-time data like never before.
What does this mean for firms in this industry both big and small? Well, it will become more important than ever to convert data to actionable insights. They can use such insights to improve the customer experience, drive loyalty and even introduce better offerings.
This can help incumbents become much more data-driven and customer-centric in their approach, leading to better decision-making. Meanwhile, smaller players that can nimbly respond to these insights can outmaneuver bigger competitors and eat away at their market share.
Ultimately, firms need to tackle PSD2 from a strategic perspective and not just from a compliance perspective. The ones that proactively capitalize on these opportunities can future-proof their business and disrupt, rather than be disrupted.
From early-stage payments fintechs to giant acquirers, every company is asking themselves the same question: “How can we turn our data into dollars?”
After all, most companies these days are to some extent data companies, whether they are aware of it or not. Many businesses try to leverage certain types of data they capture, but there’s also a lot of valuable ‘data exhaust’ they could use without ever sharing any personal or sensitive information. This is known as alternative data and it is being rapidly monetized and shared in the US and Europe.
What is data exhaust?
No, it doesn’t refer to the exhausting nature of big data. (Though there is something to be said about that too!)
Data exhaust refers to the excess data that is generated as a byproduct of a company’s operations. Simply put, it’s all the data the firm might not know what to do with, or might not think is relevant to its core business. This amount is much bigger than you think – Forrester reported that on average, between 60% to 73% of all data within an enterprise goes unused.
However, with advances in IoT, machine learning and artificial intelligence, this rapidly growing volume of exhaust could hold much untapped potential. In fact, this data exhaust could end up being converted into valuable fuel, whether for better decision-making or new ancillary revenue.
Why is data monetization so hard?
Firstly, many firms struggle with what data monetization actually means. Some paths to data monetization are more obvious than others. We’re living in an era when exploiting data for advertising or marketing purposes has become a huge concern. Even when there is no threat to personal privacy, organizations still have to navigate reputational risks if there is even a whiff of data misuse.
Secondly, trying to glean insights from all this raw and unstructured data can be like finding a needle in the haystack. It’s a significant challenge in terms of resources and infrastructure, requiring data expertise that is usually not found in-house.
So what can companies do to tackle this?
Two routes to monetization
These are the two primary paths to data monetization that companies can choose to take, though they are not mutually exclusive. In fact, both paths can intersect and one can lead you down the other:
1) Getting new business insights – This is an internally focused path that may not directly lead to money on the table. But it’s about leveraging data to improve operations or the customer experience. In turn, this could lead to higher profitability or greater efficiencies that result in reduced costs.
Alternative data can yield insights that we may have otherwise not considered. But it’s easier said than done because, as Forbes reports, 87% of executives are still not confident they’re able to leverage all customer data.
But first, every organization needs to take stock of its data assets and figure out which types of data potentially hold value. Then they need to assess whether they have the data management infrastructure, tools and resources to be able to extract value from it.
2) “Externally” monetize data – These days, the mere mention of “selling data” conjures negative reactions. But there are ways of monetizing non-personal data that is aggregated and anonymized. This can be valuable to people you may not be thinking of in ways you might not have imagined.
Opportunities may exist in markets that are new and unfamiliar to the data owner. For instance, firms can open up new revenue streams by selling their data to economists, analysts, investors and any other parties that are seeking to gain new and unique insights.
Raw data by itself can be one-dimensional. It is when data from different companies and sectors is combined and enriched with complementary data sets that real value is created. For instance, a company working with vendors across the country might have data on national beverage sales. It could track these sales and provide additional insights back to the vendors to help them improve sales and promotions. The company could also share this data with beverage brands so they can finetune and optimize marketing by city.
Think about it this way: Doing nothing with your data is the equivalent of keeping all your savings under the mattress. It seems like a safe bet, but it’s outdated and you get zero returns. Data monetization is a smarter investment – it seems daunting at first but if you can find a safe, meaningful use case, your company’s data becomes a revenue driver rather than a sleeping asset.
An industry dominated by a small number of old players, an audience longing for better and the upstarts who broke through big.
Yes, this describes 2018 in data, where traditional heavyweights Thomson Reuters and Bloomberg saw an increasing field of disruptors, but it also reflects, and offers a lot of lessons from, the music industry in 1991.
An industry dominated by a small number of old players, an audience longing for better and the upstarts who broke through big.
For a quick and opinionated history, the friendly vibes of disco and psych-folk in the 70’s were eroded by the W shaped recession, stagflation and an international oil crisis, paving the way for a bleaker, heavier turn in both society and music.
Metallica released their first studio record,Kill ’em All in 1983, but became cultural mastheads with the thrash metal darkness of Master of Puppets in 1986, with the two albums selling a combined 9 million copies in the US alone. This heaviness was supplemented by the second wave of hair metal bands, notably Guns N’ Roses, whose Appetite for Destruction, released in ’87, sold 18 million copies domestically. The rock incumbents were established.
The next few years saw greater bombast, and bigger sales (Metallica’s self titled 1991 record remains their best selling, with almost 17m copies sold in the US), but a waning connection with listeners. Given the choice between heavy metal and hair metal, younger rock fans began to feel the apathy which would define Generation X. Then came KC.
Alternative Rock Conquers the World
Little known label Sub Pop Records in Seattle released Nirvana’s first record, Bleach, in 1989 to middling success. But it was the band’s 1991 release Nevermind on David Geffen’s DGC records which changed the face of 90’s rock, ushering in a raw sound stripped of pretense and even of meaning. Gone were the costumes, the makeup and the arena theatrics, in their place an urgent, hazy sound, inviting the listener to define their own meaning. This was alternative rock.
What is Alternative data? Alternative data is defined as data collected from new sources such as satellites or sensors, or used in new ways
And readers can now probably see the parallels. Alternative data, defined as data collected from new sources such as satellites or sensors, or used in new ways, has been around for a long time, picking up pace in the middle of the last decade. But 2018 was its major label moment, as NASDAQ purchased alternative data pioneer Quandl and almost 400 alternative data providers competed in the space.
Indeed, Quandl’s Alternative Data Conference in February 2019, which Suburbia will be attending, is titled “The race to be first is over”. The question is what comes next, and I believe the music industry has three important lessons for everyone.
1. Expect the Majors to Muscle in
Seattle post-Nirvana saw a flood of attention from major record labels, giving greater attention to bands like Alice in Chains or Pearl Jam. Others were met with less commercial success, like Nirvana precursors the Melvins or Tad. Similarly, Quandl was not the only alternative data provider to be purchased, with 7Park being bought by Vista Equity Partners in December.
In theory this influx of capital benefits everyone, by giving smaller players more resources, the bigger players more market control, and end users easier access to new platforms.
In reality, I see upsides and downsides. The influx of capital has only just begun, and by 2020 expect smart investments to bring today’s alternative data startups to the next level of success. On the downside, there will be major players who overpay to establish presence in a crowded market.
But don’t worry, the incumbents have the money to lose and are not going anywhere – Guns N’ Roses still sell out stadiums, and Bloomberg and Thomson Reuters’ Eikon will remain Wall Street fixtures. They just won’t have the field to themselves anymore.
2. New players will be distributed globally
The Pacific Northwest is considered the birthplace of grunge but by no means its only home. New York’s Gumball came from the opposite coast, The Smashing Pumpkins hailed from Illinois, Bush from across the Atlantic in London and Silverchair across the Pacfic flew the grunge flag in Australia.
Alternative data has similarly been an East Coast play, with Toronoto’s Quandl focusing on the hedge fund crowd in Connecticut and the banks in New York. But there is a growing field internationally, with Eagle Alpha, one of the industry’s earliest and most influential players, based in Ireland and Suburbia headquartered in Amsterdam.
Asia remains under-served, with some firms including IHS Markit having a presence, but the heavy hand of government-linked corporations creates headwinds for independent measurements and verification. Regardless, it is a matter of time before alternative data users and suppliers are truly global.
3. Nothing will be the same
Grunge as a genre began to fade by the mid-90’s, with Nirvana’s last album In Utero released in 1993 and the band dissolving the next year. Mother Love Bone’s tenure was even shorter, breaking apart before their first album was released. Even bands who stayed together changed their sound, with Pearl Jam’s 1996 album No Code turning towards ballads and garage rock.
But the mark of grunge was inedible in music, either directly as Nirvana drummer Dave Grohl’s next band Foo Fighters owned radio rock airways in the mid-90’s, indirectly with Marilyn Manson, getting input on his 1998 record Mechanical Animals from Billy Corgan of the Smashing Pumpkins, and passively in trending pop acts like Halsey, photographed in Nirvana t-shirts and whose 2018 track New Americana mentions Nirvana directly.
Outside of music, filmmaker Gus Van Sant’s mumbling cast were the outsiders raised on grunge, most clearly in his semi-biopic Last Days. In fashion and art, the band’s iconic designs from the yellow smiley face to the swimming baby have been emulated from high fashion brand Lad Musician in Japan to TV’s The Simpsons, and broadly the dividing line between the mainstream and the underground has been blurred.
This last point is crucial when it comes to data. Much like David Geffen’s major label DGC traded with tiny Sub Pop records, traditional releases like government reports or company earnings will become enriched with alternative data, and alternative data suppliers will find themselves collaborating with traditional sources.
Data driven decisions will no longer be the enclave of hedge funds who can afford multiple Bloomberg terminals, or large financial institutions purchasing reports from consultancies.
In a few years the influence of new data will be pervasive across mediums, roles and industries, leading to more accurate measurements and better decisions for everyone. Add that to the enduring legacy of Nirvana.
Thomas Egner, the Secretary General of the Euro Banking Association recently referred to data as the ‘new superpower of the financial services world.’
Despite the huge appetite for data across the industry, its disruption has been muted. Research from PwC highlights how little data most financial services firms use when understanding and engaging with customers – with estimates that businesses are only using 0.5% of available data. At the same time, according to Deloitte (2017) 44% of companies say that there are no clear accountabilities for data management or defined data processes and procedures.
This poor use of data is partly cultural. Quarterly earnings reports and whitepapers, for example, have been the staple of banking executives when making decisions and analysing the marketplace. However, these papers are often slow and infrequent and as these sources are readily available they tend to offer limited intelligence or insight.
For those institutions that are using data, there has been a growing understanding that simply having mountains of data is not enough. The conversation has moved from having big data to having fast and relevant data, with a growing demand for alternative data to provide intelligent, accurate and actionable information. Companies are beginning to see the value in purchasing alternative data as a way of gaining a competitive information advantage that is so vital in the banking and finance marketplace.
Alternative data consists of data obtained from hard to access or non-traditional sources such as satellites, point of sale transactions and the Internet of Things, and can be used to better predict market movements and trends. By harnessing alternative data, corporations, economists and investors are able to access the very latest data to inform the best decisions.
Alternative Data: an information advantage
Alternative data presents an information advantage, especially prominent in the field of investment management, with hedge funds among the pioneers in the alternative data field. A 2017 report from JP Morgan suggested that asset managers were spending up to $3 billion on alternative data per year, with the number of alternative data analysts quadrupling in the last five years.
Recent research from the University of Toronto highlighted the potential, with researchers analysing nearly 1 million tweets that mentioned nearly 3,600 companies to perform textual analysis on them. This analysis was then fed into a machine learning algorithm that was able to accurately predict whether each company would meet their quarterly earnings target or not. Indeed, the approach was even able to accurately predict how the share price of each firm would respond to that event.
In addition, work undertaken by the School of Business and Economics at Friedrich-Alexander-Universitat Erlangen-Nurnberg, which saw a deep learning algorithm trained on 180 million data points about members of the S&P 500 over a 22 year period from 1992 in order to generate better quality stock picks. When compared to existing methods, the algorithm was capable of achieving double digit returns, with an especially strong performance during turbulent financial periods.
Such outcomes are not confined to the stock market, with researchers at the University of Plymouth showcasing how commodity prices can be predicted with similar accuracy. Their work saw algorithms trained on vast quantities of data to accurately predict movements in the price of oil.
Capitalizing on the opportunity of alternative data
Despite the tremendous promise presented by data, its collection is not devoid of risk. Traditional data gathering is a big threat to an organisation’s security and reputation. Methods involving mining, scraping and analysing vast amounts of personal data from day-to-day business operations – to inform marketing and advertising campaigns -are putting companies at risk.
Data breaches such as those experienced by Equifax and Capital One highlight the disadvantages of depending on personal data and traditional data collection. At the same time, there needs to more robust cyber security measures for existing data sets on customers and stakeholders.
By using alternative data there can be significant reductions made to the security risks associated with relying on highly personal data – because any data that is being collected will be anonymised and aggregated.
Once companies have successfully adopted alternative data as part of their business strategy, we’ll see an evolving risk landscape. The real threat to banks and financial institutions won’t be data breaches but will relate to businesses that aren’t capitalising on the opportunity to stay better informed.
Firms that fail to update their investment processes to incorporate a wide range of alternative data sources run a considerable strategic risk, and are likely to be outflanked by rival firms that are able to incorporate such data sources into their valuation and trading processes.
Alternative data is set to transform banking and finance in the coming years, so missing out is a risk you really can’t afford to take.
When companies make their tentative first steps on the road to direct data monetization (that is, selling non-personal data they own), they have to start by understanding the value of their data. They need to assess what types of data they are collecting or generating in the course of business, and whether these could potentially be a new driver of revenue.
It’s often said that data is an important and valuable asset in any organization, but there’s a reason why it never appears on a balance sheet. Data valuation is a complex and challenging exercise. But knowing what their data is worth can help companies explore monetization, allocate resources and properly structure their technology infrastructure.
In addition, they have to understand the market’s perception of value. Some firms might be overestimating the monetary value of their data, while others are unaware that their data is valuable, often to people in sectors and industries they may not have even thought of. A Forbes contributor compared the latter to the instance when companies realize they’re sitting on patents they don’t really need, but actually have value to someone else.
So what are the fundamental characteristics of high-quality data that organizations need to consider when trying to measure its value? Or more simply put – what makes data valuable and how much is your data worth?
1.Does it tell a story?
Does the data tell you something about the economy or market trends? Does it track which brands are growing or which products are in high demand? The better your data reflects real world behavior, the higher its value.
2. Is it unique?
Generally, the more exclusive the dataset, the more lucrative it is. Do you have data that nobody else has, or is it already widely available from other sources?
3. Is it anonymized and compliant?
If you are planning to share raw data, it needs to be stripped of all personally identifiable information (PII) to protect the privacy of individual customers. This is critical in order to monetize data responsibly, as data privacy is not optional but essential.
4. Is it timely?
Is your dataset updated on a weekly, monthly or a near real-time basis? The latter is most desired, especially for economists and institutional investors that are looking for faster insights to stay ahead of the market.
5. Is it specific?
The more granular and detailed the data, the more valuable it is. (Though to reiterate, personal details should definitely be excluded!) For example, data showing a million smartphones were sold last week is valuable. But its value grows significantly if it also indicates how many of those smartphones were iPhone X or Samsung Galaxy, etc.
6. Is it complete?
Do you have data for every day, without any gaps? Missing data could be as bad as inaccurate data, as it provides only a partial view of the real trends.
7. Is it reliable and consistent?
If there are multiple servers where data is collected or stored, do they all add up properly? Or do they contradict with one another? Are there potential duplicates or other data errors?
8. Do you have archives of historical data?
The further back your data goes, the better. Historical information is used in all kinds of analytics. In most use cases, two or more years of data are important to see how trends are changing over time.
The media often makes it sound like a choice has to be made between monetizing business data and maintaining privacy. But it’s not an either/or situation, it’s possible to do both at the same time.
Since the EU rolled out sweeping data protection directives through the General Data Protection Regulation (GDPR) in 2018, firms have been questioning how to leverage their data while being compliant.
Indeed, the Business Application Research Center (BARC) found the issue of data security is one of the major stumbling blocks for organizations in monetizing their data. If they fail to find a way past these barriers, they are not only missing out on a valuable opportunity, but they could also end up eating the dust of more agile competitors.
In its report, BARC stated that, “for many the risk of using data for internal and external monetization seems to outweigh the potential benefits.”
Maybe it is because businesses have been so unnerved by negative headlines regarding data privacy scandals that they fail to truly grasp what is possible under these regulations.
Let’s focus on external monetization, which is basically about leveraging your internal operational data to create a new revenue stream. But today, the mere mention of “selling data” creates a fear of reputational risk.
Ensuring data privacy should rightly be a chief concern for every company that is dealing with highly sensitive customer data. It’s not important just from a compliance perspective, but essential for building customer trust and loyalty.
However, there are ways of monetizing non-personal data and this is often an opportunity that is overlooked. Companies may ask, “How can my data be valuable if it’s missing certain pieces of the puzzle?” That is because they assume the personal details form the critical components. But in fact, even an aggregated, anonymized form of the data could still form a complete picture for others. These could be people in different markets and industries, like economists, analysts or investors looking to identify patterns and trends.
In addition, new tools and technologies have made it easier and faster to extract, refine, enrich and anonymize this data. It is this process, enabled by technology, that helps to wring the maximum value out of a company’s data.
The early adopters in the use of alternative data, institutional investors, are rapidly increasing spending to acquire information that helps them make better decisions. Unlike advertisers, they have absolutely zero interest in personally identifiable information (PII). What they want is empirical, anonymized data that tells them how companies and markets are performing. How many beers are being sold by Heineken across Europe this quarter? Is Deliveroo seeing more orders than UberEats? Economists and analysts have strict compliance procedures and actually demand that the data they buy are stripped of consumer-level data.
Service providers are well-positioned to capitalize on the rapidly growing opportunities to leverage their data in the digital economy. But there shouldn’t be a tug-of-war between monetization and privacy. Forward-thinking firms will understand how they can turn their data into profit while having the utmost respect for privacy.