Financial Services

Thinknum Sees Financial Analysis In A New Light

thinknumpixThinknum is a startup with the mission: disrupting financial analysis.

In his work as a quantitative strategist at Goldman Sachs, Thinknum co-founder Gregory Ugwi saw firsthand the trials and tribulations financial analysts went through to digest companies’ financial reports and then build their own research reports about their expectations for future performance based on past numbers. The U.S. SEC’s mandate that companies disclose their financial data using XBRL (eXtensible Business Reporting Language) was supposed to help them, as well as investors of all stripes and sizes that want to better understand what’s going on at the companies they’re interested in.

“The SEC has mandated that all companies have to release their numbers in a machine-readable format, and that’s XBRL (eXtensible Business Reporting Language),” says Ugwi. The positive side of that is that anyone can now get the stats on companies from Google to Wal-Mart, but the downside is that by and large, they can’t do it in a user-friendly way.

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The Office of Financial Research To Look Hard At FIBO For Financial Instrument Reference Database

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Image Courtesy: Flickr/ .reid

Ontologies are getting a thumbs up to serve as the basis for the Office of Financial Research’s Instruments database. Last week, the Data & Technology Subcommittee of the OFR Financial Research Advisory Committee (FRAC) recommended that the OFR “adopt the goal of developing and validating a comprehensive ontology for financial instruments as part of its overall effort to meet its statutory requirement to ‘prepare and publish’ a financial instrument reference database.”

The Instruments database will define the official meaning of financial instruments for the financial system — derivatives, securities, and so on. The recommendation by the subcommittee is that the OFR conduct its own evaluation of private sector initiatives in this area, including the Financial Industry Business Ontology (FIBO), to assess whether and how ontology can support transparency and financial stability analysis.

FIBO, which The Semantic Web Blog discussed in detail most recently here, is designed to improve visibility to the financial industry and the regulatory community by standardizing the language used to precisely define the terms, conditions, and characteristics of financial instruments; the legal and relationship structure of business entities; the content and time dimensions of market data; and more. The effort is spearheaded by the Object Management Group and the Enterprise Data Management (EDM) Council.

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Text Analytics Can Cut A Broad Swath in Capital Markets

tgroupWhat’s next for the capital markets arena when it comes to unstructured content? According to research and consulting firm TABB Group, which specializes in the stock, bond and money markets, it’s time to turn text analytics to internally generated and disseminated unstructured data, which holds a high value for customized intelligence.

In new research,  “Inner Voices: Harvesting Text Analytics from Proprietary Data,” research analyst Valerie Bogard and senior analyst Paul Rowady discuss that there are more use cases than initially undertaken for text analytics tools. “Although ultra-low latency trading strategies were an early use case in this space, text analytics is no longer limited to just that,” Bogard said in an email to The Semantic Web Blog. “The use of machine readable news has been widely adopted and all major market data providers incorporate market moving news content into their feeds.”

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Interest Grows In Riding The Semantic Wave

Image Courtesy: Flickr/ Peter Kaminski

Image Courtesy: Flickr/ Peter Kaminski

Industry leaders in sectors including banking and financial services look to have high hopes for semantic technology. They’re thinking about FIBO (Financial Industry Business Ontology) and leveraging semantic technology for more traditional types of data integration and analytics projects. At Cognizant, Thomas Kelly, a director in its Enterprise Information Management practice – and the author of this white paper on How Semantic Technology Drives Agile Business – sees the positive development that clients in the Fortune 500 space like these “are maturing in their use of semantic technology, from a project focus to more enterprise initiatives.”

The interest in FIBO, he says, is representative of an overall interest across in industries in leveraging industry ontologies as mechanisms to help companies better standardize, align and learn from the output of industry-wide efforts. The attention that industry analysts, including Gartner, have put on the semantic web in the last year – not to mention regulators beginning to consider its use in sharing information on a regulatory basis – have helped increase interest by commercial organizations, Kelly notes. That’s also evident in the life sciences sector, as another example, with the efforts of the FDA/PhUSE  Semantic Technology Working Group Project to include a draft set of existing CDISC standards in RDF.

The pickup in attention to many things semantic ties to the different perspectives that organizations need to manage about their data, which include “how they currently think of their data, how it is currently perceived in managing business operations; and where they are looking to go in the future that makes it more inclusive of what’s going on in the world outside their walls – that is, how the rest of the industry looks at this data and uses it to support their business processes,” he says.

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QuantDesk Event Analyzer Module For Bloomberg App Portal Delivers Market — And Machine Learning — Magic

rsz_ucenapixLucena Research is the company behind the machine-learning based investment technology QuantDesk (see our original story here). Its five modules are designed to give non-quants in family investment offices, hedge funds, endowments and other registered investment advisors a scientific approach to investment decision- making to augment their own strategies with the tools to figure out market trends and patterns.

But CEO Erez Katz says there’s another market its technology now is ready to address: Those who’d like to have the research done for them. To that end, it’s deploying a new module on the Bloomberg App Portal, dubbed the QuantDesk Event Analyzer, that provides subscribers with professionally researched market & equity trends,  and equity price forecasts based on machine learning pattern analysis.

The company already has three modules on the portal, and the latest provides a collection of studied and researched events-based decision support strategies. “We do the research, form the strategy, and deploy our findings in the form of entry/exit signals on their dashboard on the Bloomberg App Portal,” says Katz, whereas previously its products deployed only toolsets and technology for users to deploy their own strategy. “This new edition takes the research of our internal quants and exposes the output and exclusivity of these unique strategies to our premium client base – that is, buy and sell signals not available to the rest of the world.”

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Following Up on FIBO At SemTechBiz

SemTechBizThe Financial Industry Business Ontology (FIBO) was a main topic of interest at last week’s Semantic Technology & Business Conference – which took place in New York City, the capital of the financial services industry. FIBO, as The Semantic Web Blog has previously discussed, is both a business conceptual ontology and an operational ontology delivered together, designed to be useful both to the financial industry and the regulatory community in understanding the complex patterns and relationships of information characteristic of the sector, with the goal of driving greater transparency. The FIBO initiative is a joint effort underway by the Object Management Group and the Enterprise Data Management (EDM) Council.  But many other different standards will be useful to solve the industry’s issues, as well.

At the presentation, Semantics in Finance, Thematix Partners’ principal Elisa Kendall – self-described standards wonk and member of the OMG Architecture Board and co-chair, Ontology Definition Metamodel (ODM) Revision Task Force – pointed out that the amount of regulation in the financial services sector has increased over 400 percent in the last two to three years. She argued for a little more sympathy for the financial services industry, too, which hasn’t been on the receiving end of a lot of that since about 2008 – even though some of these players stepped up to buy companies that were knocked flat by the mortgage market meltdown.

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New Session Added to SemTechBiz NYC Line-up: Semantics in Finance

A new presentation has been added to the already bustling agenda for the Semantic Technology and Business Conference in New York next month. The conference, which takes place October 2-3 at the New Yorker, will now include Semantics in Finance: Addressing Looming Train Wreck in Risk Management, Regulatory Compliance and Reporting,  a presentation by Elisa Kendall, a partner at Thematix Partners. Read more

Digital Reasoning’s Synthesys Puts The Focus On Compliance Via RealTime Email Analytics

Synthesys, Digital Reasoning’s machine learning platform that ferrets out meaning in unstructured data at scale, is bringing its smarts to compliance use cases for organizations, such as financial institutions. (See this article for more insight into the technology behind the company’s software.)

This week, the vendor delivered Version 3.7 of the Synthesys software, which brings with it the capability to monitor and analyze all email communications in near real-time. That matters to many compliance program use cases, among them insider trading, money laundering and reputation management. “They all go back to finding information inside of communications, like who are the people and organizations mentioned in email, and what is being discussed about them,” says Tim Estes, chairman and CEO. “Synthesys can take essentially millions of emails and winnow them to maybe a hundred that are problems.”

That means fewer things are falsely flagged as issues, there’s less privacy treading into innocent emails, and there’s more return on time for the people charged with protecting customers and enforcing compliance requirements.

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Sentiment Analytics Tech Helps Gauge TRust In Financial Services Sector

How do you feel about the financial institutions you deal with? A report earlier this week of a survey of Wall Street financial services industry professionals, conducted by Labaton Sucharow LLP, might have you a bit leery.

The report notes, for example, that 23 percent of those polled said they’d observed or had firsthand knowledge of wrongdoing in the workplace. Twenty-nine percent believe that financial services professionals may need to engage in unethical or illegal activity in order to be successful. More than one-quarter think the compensation plans or bonus structures at their companies incentivize employees to compromise ethical standards or violate the law, and 24 percent would engage in insider trading if they could make $10 million and get away with it. Twenty-eight percent say the financial services industry does not put the interests of clients first.

Says the report, “We see a powerful and frightening pattern that threatens an already fragile marketplace.” Yikes. Now, on the heels of that, comes Thomson Reuters’ Q2 TRust Index that aims to gauge trust in the top 50 global financials. It leverages technology including its own news and social media sentiment analytics solution, Thomson Reuters News Analytics (TRNA), and its MarketPsych Indices, which provides real-time psychological analysis of news and social media.

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Global Corporate Networks Exposed through New Online Platform

World-wide interests of US banks first to be identified

Visualization of Goldman Sachs Corporate Network[Press Release] A new online platform launched today is set to provide free and open access to global corporate networks.

The platform, developed by OpenCorporates, collects, extracts and makes usable global corporate data, in an open and granular way. Large data sets, many of which were not available as open data before, have been imported by the London-based company, and used to develop corporate network visualisations which show the global corporate networks of businesses. Examples include IBM, Starbucks and Barclays.

In addition to the corporate network visualisations, the new technology has produced maps which show the world-wide interests of four US banks – Bank of America, Citigroup, Goldman Sachs and Morgan Stanley. They reveal complex and deep networks, as well as the central position that the Cayman Islands have within them.

Chief Executive of OpenCorporate, Chris Taggart said:

Photo of Chris Taggart“This platform is an incredibly powerful and innovative piece of technology. Prior to its development, many of the datasets we are using were only available as web pages or PDFs. Now we are bringing this data together into a useable format which will change the way people are able to access and view corporate networks.”

“The emphasis we place on detailed provenance and confidence scores with this platform is substantially better than existing efforts to identify corporate networks, which are essentially ‘black boxes’. These hide the underlying data used to derive the relationship links, give no indication of how likely the information is to be correct, or the date the information related to. We believe that in a world which is increasingly dependent on corporate data, this is critical – whether you are an investigative journalist, or calculating credit risk.”

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