Suburbia launches luxury cosmetics dataset for investment insights

29 October 2019, Amsterdam – Suburbia, a technology company specializing in alternative data solutions, has introduced its second offering that leverages millions of anonymized transactions to predict the performance of luxury brands in the beauty and personal care space.

Suburbia has partnered with companies in the payments ecosystem to collect receipt line-level data from multiple sources. This unique dataset tracks sales of luxury cosmetics and fragrances in France, the largest market for this segment in Europe and the fourth largest in the world, with a total value of three billion euros. 

“France is not just a large market for the world’s biggest luxury companies and beauty brands, it is also a trendsetter and tastemaker,” said Hamza Khan, CEO of Suburbia. “By collecting accurate sales across the country, our product is a powerhouse for what is popular in France, and a strong indicator of what will be popular globally.”

The new dataset delivers daily signals on publicly listed and private companies, including key players in the industry such as L’Óréal Luxe, Coty Inc., Estée Lauder Companies and LVMH. It tracks over 100 brands including Dior, Chanel, Hermès, Hugo Boss, Kenzo, Lancôme and YSL. The data product has been built specifically for investors who want granular insights into how these companies’ main revenue drivers are performing, whether by brand, category or product.

According to a recent report, among all luxury goods sectors, cosmetics and fragrances have witnessed the highest sales growth.* The market is expected to grow annually by 3.3% (CAGR 2019-2023).**

Suburbia’s proprietary technology is capable of processing millions of consumer purchases. No personal information is ever used or shared in the process. This data is updated on a daily basis with a one-day lag, so investors can get up-to-date insights for making decisions faster.

Other highlights of this product include:

  • Ticker mapping to easily see performance of publicly traded companies over time
  • Granularity such as EAN, brand name, item pricing, product category, basket composition, geography and time of transaction. Anonymized merchant ID is provided in order to compare same-store or like-for-like sales.
  • Historical coverage, with over three years of data available for backtesting

*  Deloitte, Global Powers of Luxury Goods, April 2019
** Statista, 2019

Suburbia launches European consumer transaction data solution for investment community

19 September 2019, Amsterdam – Suburbia, a technology company specializing in alternative data solutions, today launched its first-ever offering that leverages millions of anonymized transactions across Europe to provide predictive insights into consumer goods companies.

A multi-source platform with granular insights into brand performance, it delivers daily signals on over a hundred publicly listed and large private companies. This data product has been built specifically for hedge funds, asset managers and other institutional investors to generate alpha and manage risk.

“Investors have long been tapping into transactional data to anticipate trends and consumer behavior,” said Hamza Khan, CEO, Suburbia. “But we realized most of the existing data out there is generated by a panel of users which could lead to an opt-in bias and less accuracy. In addition, this data is much harder to come by in Europe because it’s such a diverse and fragmented landscape – every country has its preferred payment methods. We believe our unique approach has resulted in the industry’s most actionable dataset.”

Suburbia’s proprietary technology is capable of processing millions of consumer purchases from thousands of hospitality and retail channels across Europe, with a strong focus on Germany and the Benelux. No personal information is ever used or shared in the process. This data is updated on a daily basis so investors can get up-to-date insights for making decisions faster.

Other highlights of this product include:

  • Ticker mapping to easily see performance of publicly traded consumer packaged goods (CPG) companies over time
  • Granularity such as product details, item pricing, basket composition, geography and time of transaction
  • Historical coverage, with over two years of data available for backtesting

Suburbia first and only Dutch startup selected for Tokyo accelerator program

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.

The opportunity of alternative data for the banking and finance industry

(First published on Financial IT)

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.