Barry Roche of the Irish Times recently wrote, “Taoiseach [the Irish term for ‘Prime Minister’] Enda Kenny will today launch a €5 million technology centre in Cork designed to create new business opportunities for Irish financial services and technology companies through addressing governance and compliance issues. The Governance, Risk and Compliance Technology Centre (GRCTC) is the latest addition to the network of 15 Technology centres in Ireland and will carry out R&D on semantic technologies which encode meanings separately from data and content files.” Read more
Next week in the U. K. members of the financial industry will be coming together at The Universal Strategy: Knowledge-Driven Finance Event, hosted by semantic technology vendor Ontotext. The event, says independent consultant in semantics and event organizer Jarred McGinnis, is aimed at giving participants “a snout to tail view of semantics in finance.”
The use cases, he says, are there, and to that end the panel will include presentations by Financial Times CTO John O’Donovan, who will discuss issues including how the publisher’s semantic approach is driving smarter topic pages. (The event actually takes place at The Financial Times site.) Also scheduled to be present is Mike Bennett, director at Hypercube and Semantics Lead at The EDM Council, which is a cross-industry group developing the Financial Industry Business Ontology (FIBO), and John Schlesinger, Chief Enterprise Architect at Temenos, which develops software for retail banking companies, including solutions that will leverage triple stores.
In a preview of his talk, Bennett spoke to The Semantic Web Blog that about the current state of FIBO affairs.
Oluwabusayo Sotunde of Ventures Africa reports, “Africa’s most innovative bank, Standard Bank Plc has reached an agreement with leading IT services provider, IBM to implement the latter’s new Watson technology. IBM’s Watson technology breaks traditional barriers in computing by embracing artificial intelligence, natural language processing and dynamic learning when assisting customers and businesses with the interpretation of data. Head of Innovation and Channel Design at Standard Bank, Vuyo Mpako explained that the bank partnered with IBM so it could consolidate the technology into its operating system. This would enable Standard Chartered efficiently interpret and maximise its data.” Read more
Suzanne Kattau of Silicon Angle reports, “IBM and the United Services Automobile Association (USAA), a financial services provider for the military community, today announced they have teamed up to offer IBM’s Watson Engagement Advisor in a pilot program to assist USAA members. USAA provides insurance, banking, investments, retirement products and advice to 10.4 million current and former members of the U.S. military and their families. Named after IBM founder Thomas J. Watson, IBM Watson uses natural language processing and analytics, and can process information similar to the way people think. This helps organizations to quickly analyze, understand and respond to vast amounts of Big Data. IBM’s Watson Engagement Advisor analyzed USAA’s business data and now understands more than 3,000 documents on topics exclusive to military transitions.” Read more
Digital Reasoning’s Synthesys machine learning platform (which The Semantic Web Blog initially covered here) this summer should see its Version 3.9 release. The update will build on the 3.8 release, which delivered with its Glance user interface the discovery and investigative capabilities that help information analysts in finance, intelligence and other compliance- and security-sensitive sectors react to findings in user profiles of interest and their associated relationships, activities and risks. Version 3.9 takes on the proactive part of the equation — early risk detection — via its Scout user interface.
Last year, the company honed in on compliance use cases ranging from insider trading to money laundering with Version 3.7 of Synthesys (covered here). There, the technology for discovering the meaning in unstructured data at scale, highlighting important entities in context, was applied to email communications for organizations such as financial institutions that have to be on the lookout for conversations that cross compliance boundaries.
AlphaSense’s Advanced Linguistics Search Engine Could Buy Back Time For Financial Analysts To Do More In-Depth Research
When Raj Neervannan, CTO and co-founder of financial search engine company AlphaSense, thinks about search, he thinks about it “as a killer app that is only growing…..People want answers, not noise. They want to ask more intelligent questions and get to the next level of computer-aided intelligence.”
For AlphaSense’s customers – analysts at large investment firms and banks or any other industry, as well as one-person shops – that means search needs to get them out of ferreting through piles of research docs for the nuggets of information they really need. Neervannan knows the pain of trying to interpret a CEO’s commentary to understand what he or she was really saying when making the point that numbers were going down when referring to inventory turns. (Jack Kokko, former analyst at Morgan Stanley, is AlphaSense’s other co-founder.)
“You are essentially digging through sets of documents [using keyword search], finding locations of terms, pulling them in piece by piece and constructing a case as to what the company’s inventory turn was really like – what other companies’ similar information was, how that matches up. You have to do quantitative analysis and benchmarks, and it can take weeks,” he says.
Marty Loughlin of Wall Street & Technology recently noted that in this era of “massive business and IT transformation,” organizations in the financial industry “will need to change how they track, manage, and consume data. For many organizations, this data is not easily accessible — it is distributed across the organization, often trapped in local business units, applications, data warehouses, spreadsheets, and documents. Traditional technologies are struggling to address this challenge and many believe a new approach is required. Some of the new big-data solutions do help. They are good at liberating and colocating data. However, they often struggle to make it usable. Creating a ‘data lake’ where rigid structure is not required can result in yet another silo of unusable data where context, meaning, and sources are lost. Many organizations are turning to semantic technology for the answer.” Read more
A new report from the Securities Technology Analysis Center (STAC), Big Data Cases in Banking and Securities, looks to understand big data challenges specific to banking by studying 16 projects at 10 of the top global investment and retail banks.
According to the report, about half the cases involved e petabyte or more or data. That includes both natural language text and highly structured formats that themselves presented a great deal of variety (such as different departments using the same field for a different purpose or for the same purpose but using a different vocabulary) and therefore a challenge for integration in some cases. The analytic complexity of the workloads studied, the Intel-sponsored report notes, covered everything from basic transformations at the low end to machine learning at the high-end.
Larry Hardesty of the MIT News Office reports, “By now, most people feel comfortable conducting financial transactions on the Web. The cryptographic schemes that protect online banking and credit card purchases have proven their reliability over decades. As more of our data moves online, a more pressing concern may be its inadvertent misuse by people authorized to access it. Every month seems to bring another story of private information accidentally leaked by governmental agencies or vendors of digital products or services. At the same time, tighter restrictions on access could undermine the whole point of sharing data. Coordination across agencies and providers could be the key to quality medical care; you may want your family to be able to share the pictures you post on a social-networking site.” Read more
The Aite Group, which provides research and consulting services to the international financial services market, spends its fair share of time exploring the data and analytics challenges the industry faces. Senior analyst Virginie O’Shea commented on many of them during a webinar this week sponsored by enterprise NoSQL vendor MarkLogic.
Dealing with multiple data feeds from a variety of systems; feeding information to hundreds of end users with different priorities about what they need to see and how they need to see it; a lack of a common internal taxonomy across the organization that would enable a single identifier for particular data items; the toll ETL, cleansing, and reconciliation can take on agile data delivery; the limitations in cross-referencing and linking instruments and data to other data that exact a price on data governance and quality – they all factor into the picture she sketched out.
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