German bank launches tool to help investors integrate Big Data into portfolio management
Deutsche Bank has launched α-Dig (Alpha-dig), a new interactive web tool that uses natural language processing to quantify the materiality of environmental, social and governance (ESG) issues and other company intangibles such as brand value, corporate culture, innovation and management quality.
Alpha-dig came about as a response to the growth in technology over the last few years, and also the growth around big data and artificial intelligence (AI), according to Spyros Mesomeris (pictured), global head of the quantitative strategy and co-head of data innovation group (DBDig) at Deutsche Bank. "We wanted to leverage big data and AI within the bank's research department, but also more broadly within the corporate and investment banking division," said Mesomeris. "A significant amount of alternative data sets and unstructured data may contain information that is relevant to share prices and would allow us better evaluate the risk profile of a company, as well as obtain an enhanced view of the macroeconomic environment and move away from traditional GDP growth indices."
The bank has built a team of data scientists and technology specialists, attracting people from backgrounds not confined to banking, who offer domain expertise in different industries and different parts of the economy and can interpret data patterns. "Alpha-dig will be an invaluable toolkit and data source for fundamental portfolio managers and analysts, ESG specialists, quant investors, and asset owners, who struggle to quantify the materiality of company intangible information using existing data sources," said Mesomeris.
To develop the tool, the team has also worked with other teams at Deutsche with a lot of the R&D behind the bank's thematic and systematic indices is done by the quantitative strategy team. "Alpha-Dig can help us to expand our offering and create a larger investable product breadth around the bank's index-linked offering," said Mesomeris. "One of the ways in which the tool and the data behind it can be leveraged would be via structured products, for example, via ESG thematic indices. This will also lead to creating bespoke solutions, such as indices and structured products for institutional clients based on their use of Alpha-dig. This can also be replicated in the retail market."
One of the bank's data sources is regulatory filings because, in the risk factors section of those filings, there tends to be information that companies discuss from time to time, and may refer to litigation or product issues and other soft information that is not incorporated in current prices, according to Mesomeris. "An analyst usually misses this type of information as it is typically buried deep into the disclosures and is hard to decipher," said Mesomeris. "We also wanted to capture what companies do around ESG, leveraging on information from news sources and we're seeking to partner with a reliable source of financial media news, which would allow us to do detailed backtesting analysis."
"Alpha-Dig is an innovative tool which enables investors to look far beyond accounting data by incorporating intangible information that the market is not fully pricing," said Mesomeris.
Andy Moniz (below), chief data scientist for DBDig said ESG has changed and is no longer just about exclusion or screening out of companies. "In today's market, there is a desire from asset owners to really integrate non-financial information within mainstream investment processes," said Moniz.
"That is exactly where data science can add value based on empirical evidence looking back more than 20 years. The goal is to integrate ESG into the mainstream."
Data is coming in two main forms, including structured data such as hard accounting numbers, analyst forecasts, and data that can be put on an excel spreadsheet to create a valuation model, according to Moniz. "In today's service-based economy, most of the value of a firm comes from its intangible assets, such as its brand value, management quality, innovation, employee satisfaction and of course sustainability issues too," he said. "This data is generally unstructured in nature and hard to process, rendering it difficult to quantify objectively and across many companies."
The bank's motivation was to come up with a tool that can quantify the intangible assets and liabilities of a company using data from a number of sources, and that can also measure their materiality or statistical impact on risk, return and valuation multiples, said Moniz. "A portfolio manager can use a number of different sources to get the accounting information she needs, but our product provides her with all the non-financial information required to have a more objective, balanced, and rounded view of a company and the whole portfolio," said Moniz.