As lawmakers in Brasilia debated a controversial pension overhaul for months, a robot more than 5,000 miles away in London kept a close eye on all 513 of them. The algorithm, designed by technology startup Arkera Inc., tracked their comments in Brazilian newspapers and government web pages each day to predict the likelihood the bill would pass.<\/p>\n
Weeks before the legislation cleared its biggest obstacle in July, the machine\u2019s data crunching allowed Arkera analysts to predict the result almost to the letter, giving hedge fund clients in New York and London the insight to buy the Brazilian real near eight-month lows in May. It\u2019s since rallied more than 8%.<\/p>\n
This is the kind of edge that a new generation of researchers are betting will upend the research marketplace. For Arkera\u2019s clients on Wall Street and in the City of London, that means getting robots to filter through the noise in faraway lands.<\/p>\n
\u201cThere\u2019s too many people to follow on Twitter, too many websites, too many articles,\u201d said Nav Gupta, the 48-year-old co-founder of Arkera, which says its software can process as much information as 1,000 human analysts.\u00a0\u201cThat\u2019s a very expensive problem and everybody faces it.\u201d<\/p>\n
The company raised 4 million pounds ($4.9 million) last year from investors including Alan Howard of hedge fund Brevan Howard Asset Management LLP.<\/p>\n
Using so-called artificial intelligence to automate swathes of the research process is quickly gaining traction because cost-conscious\u00a0investment banks are downsizing. In the U.K. alone, there was a 30% drop in research budgets last year, Financial Conduct Authority data show. At the 12 biggest banks, there\u2019s been a 7% drop since 2015 in the number of front-office staff covering currencies, such as\u00a0traders and researchers,\u00a0according to London-based research analytics consultancy Coalition Development Ltd.<\/p>\n
That means it\u2019s even harder than it used to be to afford\u00a0analysts on the ground in developing nations, about the only places in the world where investors can get yield right now.<\/p>\n
Data-science companies like Arkera and New York-based Sigmoidal say they can solve this problem using machines that learn as they go to dredge through tens of thousands of news articles, government statements and social media accounts in languages as varied as Spanish, Arabic and Chinese.<\/p>\n
After an initial investment of up to $100,000, banks can save $1 million over seven years using such systems because they don\u2019t need to hire as many data analysts, said Marek Bardonski, who was chief executive officer of Sigmoidal when he spoke with Bloomberg in July.\u00a0He has since left the company. Previously, Bardonski, 27, was a computer scientist at graphics chipmaker Nvidia.<\/p>\n
Take this year\u2019s protests\u00a0in Hong Kong. Bardonski said Sigmoidal\u2019s software was able to track developments in the Cantonese-language press and even identify the non-verified Twitter feeds of protest leaders to monitor the risk of further unrest. The technology is useful for far-away countries wracked by political turmoil, places where investors are keen to put money but don\u2019t have easy access to information.<\/p>\n
\u201cThe system can give an edge over traditional analysts working for financial institutions,\u201d said Bardonski, who said typical reports will include charts on sentiment, key word statistics and short written summaries. \u201cInstead of getting 100,000 news articles, clients can get all the insights on one page.\u201d<\/p>\n
Neither Sigmoidal nor Arkera would let Bloomberg see an example of an automated report to see how readable it is compared with one produced by a human, citing rules against sharing proprietary data.<\/p>\n
In Europe, the way investors consume research has evolved fast since new rules last year forced investors for the first time to pay separately for the analysis they receive. The so-called MiFID II legislation stopped a widespread practice of having the cost of research built into the fees that the likes of Goldman Sachs Group Inc. or Morgan Stanley got paid to execute trades.<\/p>\n
The irony is that a year and a half since the rules came into force, many investment banks still offer research for free because clients aren\u2019t willing to pay for it, according to Sarah Jane Mahmud, a senior Bloomberg Intelligence analyst who specializes in regulation. They get around the rules by\u00a0publishing research on their websites for public consumption.<\/p>\n
But the quality has gone downhill because mid-level analysts have left or been pushed out, leaving\u00a0junior analysts to do the work so their more senior colleagues can go to\u00a0client meetings. This is giving investors even more impetus to seek out bespoke research, like paying cash to speak with\u00a0experts in the field\u00a0or investing in automated research to support their senior fund managers and strategists.<\/p>\n
\u201cAsset managers now need to assess the value of every single research service to assess it it’s worth paying for, how much they should pay for it, and trying to filter the good from the bad,\u201d\u00a0Mahmud said.<\/p>\n
Under MiFID II, asset managers\u00a0must be prepared to demonstrate they\u2019ve done due diligence on all investments they make for their clients, something that\u2019s always been tricky in developing countries.<\/p>\n
It was that very problem that inspired Gupta and his business partner Vinit Sahni,\u00a0whose careers spanned firms including Citadel LP, DE Shaw & Co. and Goldman Sachs, to set up Arkera in 2015. During their 20-year careers in investment banking, trying to find information to substantiate something felt \u201clike pulling teeth,\u201d Sahni, 50, said.<\/p>\n
So the pair set up a team of data scientists and engineers to design a search engine that investors can use to give them an edge in places like Turkey, Mexico and Egypt. It works kind of like Google, only it\u2019s programmed to choose the most relevant sources from tens of thousands of articles, social media feeds and government releases.<\/p>\n
As good as robots are getting at deciphering market jargon,\u00a0even their developers admit they’ll never fully replace humans. In the next decade, Sahni\u00a0said\u00a0smart machines will significantly enhance the capabilities of human analysts.<\/p>\n
\u201cWe will see advancements in cognitive abilities, communication and the physical potential of humans as we collaborate closely with machines and algorithms,\u201d\u00a0he said.<\/p>\n
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