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Thinking Big! What can cognitive computing do for sustainable investment?



We live in an interconnected world, most of us own a smartphone, a tablet or a laptop (or all three!), and thanks to widespread internet penetration and advances in 4G data, we are now at a stage where most of us have access to the sum of human knowledge in the palm of our hands, at any time we choose.  Hendrik Bartel, CEO and Co-Founder of Insight 360 writes.

The way in which we use these devices to access information itself generates data – every digital process, web search and social media post can be stored and potentially analysed.  In 2013, 2.5 quintillion bytes of data was generated everyday, enough to fill enough to fill 57.5 billion i-pads!  We now generate data at such pace it is estimated that over 90% of all the data in the world was generated within the last two years!

Information moves markets, so it is no surprise that the previously inaccessible information big data makes available could transform the investment management industry.

Finding the needle in the haystack

One of the challenges of big data is that the datasets generated are too large and too complex for humans or traditional computing methods to be able to meaningfully understand, and much of the information generated is little more than noise.

However, those who persist in extracting the value from within this noise are already reaping the rewards, and sustainable investment professionals should take inspiration from other industries. For example, by analysing web searches and social media posts, Google has been able to determine flu outbreaks with a similar accuracy to the Centre for Disease Control – and in real-time.

Swamped with ESG data? Help is at hand!

Investors are increasingly swamped by a huge volume and variety of environmental, social and governance (ESG) data. For example, CDP requests greenhouse gas emission and other environmental data from over 11,000 companies in 60 countries, and over 8,000 organisations have reports published on the Global Reporting Initiative (GRI) database.

ESG data includes diverse sets of variables, such as disclosure on climate change, water management, labour standards, executive remuneration and board diversity. As more and more information on these indicators becomes available it is becoming harder for investors to extract the really useful information and thoroughly understand its material implications.

However, technological advances are making it possible for investors to easily and efficiently extract the pieces of data that really matter and use it to improve their investment analysis and decision making processes.

TruValues, a San Francisco based fintech startup, has developed technology specifically to address this problem. The “Insight360” platform which uses cognitive computing systems (systems that learn through experience and mimic human thought processes) with algorithms that can adapt and learn, to analyse huge amounts of ESG data in real-time.

This means that investors can undertake portfolio due-diligence in real time, rather than relying on quarterly or annual reports to understand the ESG profile of a particular company and also that the ESG characteristics of companies can be constantly monitored so that issues for action (such as shareholder engagements) are identified early.

How does this work in practise?

Restaurant company Chipotle faced some serious ESG related accusations earlier this year, when it was sued over claims that its menu was “GMO free”. The Insight 360 platform showed this dip in sustainability performance, but also assimilated more positive news from the company, such as an increase in the availability of pork products from a new supplier, and an announcement to hire 4,000 workers. Overall, this meant that Chipotle’s sustainability trend was only marginally affected. Investors using the platform were able to immediately feed this integrated information into their portfolio management processes.

What are the downsides to big data?

Like any strategy, big data analytics carries risk. Some might argue that we are developing an overreliance on data sets at the expense of company meetings and on-site visits. The biggest risk however relates to data security. Data is a growing area of crime and attacks are getting bigger and more damaging.  Ashley Madison, JP Morgan Chase and eBay have all suffered damaging data theft in recent years. The bigger the data, the bigger the target, and many companies now employ a specialist Chief Information Security Officer in order to manage the risk.

However, we are only just beginning to see implications and extent of what cognitive computing and big data analytics will be able to accomplish.  When used in conjunction with, and to complement, traditional investment processes, the potential benefits that arise from smart machines and big data far outweighs the risks.

It is an exciting time for technology and for sustainable investment.