Analytics Summit 2013
35
A Data Cocktail Dirty, with a Compliance Twist
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Financial Services firms are using big data to build better intelligence about their employees and customers, this presentation describes "how" and "why" data scientists play an important role in that process.
Transcript of Analytics Summit 2013
A Data CocktailDirty, with a Compliance Twist
Stock your bar with data & tools.Get awesome bartenders.Demand great cocktails.
Mix it up based on context.
How to effectively leverage analytics in your organization?
90% of the world’s data
was generated over the last
2 years…
That changes everything:how we collect, store, manage, analyze
and visualize data.
Data > Information > Knowledge > Wisdom
Past | Present | Future
the path of the enterprise
next disruption?
Cloud
Algorithms
Mobile
Big Data
Social
Dion Hinchcliffe. Dachis Group.
Big Data is so 2012
Algorithms
• Machine learning – Predictions– Clustering
• Statistical models working at scale– Counting– Comparing– Ranking– Filtering
* *
Geeky is the new ‘sexy’
Geeky? Yup …
• Java, R, Python• SQL, RDBMS, DW, OLAP• NoSQL, Hbase, Cassandra• Hadoop, HDFS, MapReduce & Yarn• Pig, Hive, Impala, Shark• ETL, Webscrapers, Sqoop, Flume• Knime, Weka, RapidMiner• SPSS, SAS, OBIEE• D3.js, Gephi, Tableau, Flare, Shiny• Microsoft Excel
Data scientists enablethe creation of data products.
A data product is …
• Curated and crafted from raw data• Meshed together from disparate sources, some with
structured and some with unstructured data• A result of exploration and iterations• Answers known unknowns, or unknown unknowns• Triggers immediate business value• A probabilistic window of future events or behavior
Financial services is the world’s most heavily regulated industry.
Risk is uncertainty about a future outcome.
Key Risk Indicator (KRI) is a management measure used to detect an adverse impact or
prevent the possibility of future adverse impact.
Expressed as a data product.
Compliance risk is the current and prospective risk to earnings or capital arising from violations of, or nonconformance with, laws, rules, regulations, prescribed practices, internal policies, and procedures, or ethical standards. This risk exposes the institution to diminished reputation, fines, civil money penalties, payment of damages, and the voiding of contracts.
DIGITAL REASONING | CONFIDENTIAL16
In early September 2011, the Swiss bank UBS announced that it had lost over 2 billion dollars, as a result of unauthorized trading performed by Kweku Adoboli, a director of the bank's Global Synthetic Equities Trading team in London.In April and May 2012 large trading losses occurred at JPMorgan's Chief Investment Office, based on transactions booked through its London branch. Trader Bruno Iksil, nicknamed the London Whale, accumulated unauthorized outsized CDS positions in the market. The original estimated trading loss of $2 billion was announced, with the final actual loss expected to be substantially larger.HSBC Holdings Plc agreed to pay a record $1.92 billion in fines to U.S. authorities for allowing itself to be used to launder a river of drug money flowing out of Mexico and other banking lapses.In January 2008, the bank Société Générale lost approximately €4.9 billion closing out positions over three days of trading beginning January 21, 2008, The bank states these positions were fraudulent transactions created by Jérôme Kerviel, a trader with the company.
After analyzing post-loss & causal factors, they all had a good chance of being prevented or detected if Key Risk Indicators (KRIs) had provided
information that could be aggregated, analyzed, and escalated.
is the world’s most heavily regulated industry
Example: UBS Rogue Trading 2012
Example: UBS Rogue Trading 2012
Many KRIs defined to monitor trading risk
With access to the right data product – We can build an “Holistic view” of a Trader’s risk profile
Human risks are hard to predict:Even the best designed risk controls are subject to the failings of people’s experience, attitude,
mindset and values.
Traders are people.People communicate with people.
People communicate using human language.
Human language is a rich data source that enables data scientists to study people’s past
behavior or predict future behavior.
Human language is dirty data.Different languages.
Full of ambiguity.Large amounts of it, and very noisy.
Difficult to count things.
"You shall know a word by the company it keeps."
- J. R. Firth, English linguist
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*09/26/2013
*09/26/2013
*Social Interaction
Making human language tractable:Resolving entities, facts & relationships In time and space
*Social Interaction
Transforming data into knowledge
Hans Gruber
Kurt Dyson
UBS
+44-20-7567-8000
1 Finsbury AvenueLondon, UK EC2M 2PP
kdyson@richardson
Tom Watson
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(*Verizon?)
26Sept
Social Interaction
28 28
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Combining data from multiple sources– Social media
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Combining data from multiple sources– Financial system
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On September 29, UBS trader Hans Gruber executes a short on 100K shares of AAPL shares for Kurt Dyson, a high profile buy side client of the firm.On Oct. 7, Apple announces disappointing iPhone6 sales resulting in a 10% share price drop and a windfall profit for Kurt Dyson based on the Gruber’s short order.
Soci
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Combining data from multiple sources – Trade Surveillance
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e-M
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Exch
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Expe
nse
Repo
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100K
AAP
L
App
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disa
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ne6
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s
Hans Gruber
Kurt Dyson
UBS
+44-20-7567-8000
kdyson@richardson
Tom Watson
VZ(*Verizon?)
Verizon
1 Finsbury AvenueLondon, UK EC2M 2PP
Social Interaction
26Sept
Soci
alIn
tera
ctio
n?
Data Cocktail – Holistic View of Hans Gruber
Analyzing Enron’s public email data.
Bill DiPietro & Jascha SwisherDigital Reasoning.
Example: KRI for Human Language
“Legal Entity” on restricted trading list occurring in electronic communications
+Legal Entity occurring in the context of “deal related” language
+Communication “outside” company firewall
Digital Reasoning
Locations:
NashvilleWashington
New York(London)
Investors:In-Q-Tel
Silver Lake (individuals) Partnership for NYC Invest. Fund
Team:70 employees
20 Masters or PhDs40+ TS clearances
5 patents
• Synthesys® is our machine-learning platform that understands human communication
• Amplifies human intelligence by automatically aggregating knowledge from large data sets across multiple languages and sources into a private knowledge graph
• Knowledge is explored and discovered by people solving problems and making decisions in national security and enterprise risk & compliance
• Focus on US Public sector, moving into financial services in US and Europe
• Cloud offering running on AWS will be available in a few weeks, looking to engage with data scientists
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