Who’s winning the deep forensic analysis ‘arms race’ for compliance? Real-time trade surveillance in global financial markets has created a data tsunami. With greater volumes of data comes greater compliance risk. CNBC reports U.S. Banks have been fined over $200B since the financial crisis. How are compliance teams fighting back to make more of the data and stay out of regulatory hot water? Rapid response to suspect trades means compliance teams need to access and visualize trade patterns, real time and historic data, to navigate the data in depth and flag possible violations. Join Hortonworks and Arcadia for this live webinar: we’ll cover the use case at a top 50 Global Bank who now has deep forensic analysis of trade activity. The result: interactive, ad hoc data visualization and access across multiple platforms – without limits on historic data – to detect irregularities as they happen. In-depth expert presentations by: Shailesh Ambike, Executive Co-Chair of Compliance & Legal Section (CLS) Education Sub-Committee of the Investment Industry Regulatory Organization of Canada (IIROC) Vamsi K Chemitiganti, GM – Financial Services at Hortonworks

1. Winning the Deep Forensic Analysis
Arms Race for Compliance

3. Role Of Big Data In Financial Services & Capital Markets
Customer Use Case: Real-time Trade Surveillance
Introduction To Arcadia Data + Hortonworks Solution
Capital Markets Background:
Behavior, Risk, And The New Reality

5. • IIROC has put “Universal Market Integrity Rule (UMIR) in place to govern
Broker/ Dealer and Marketplace activity since 2001
• UMIR has expanded Broker/Dealer surveillance requirements over the past 10
years with increased regulatory scrutiny with respect to:
• Market Manipulation – Spoofing, Artificial Pricing, Quote Stuffing, Non Bonafide
intra day order activity, Insider trading
• Recent cases include: ITG (fine), Knight Capital,
E*Trade (G1 Execution Services – G1X)

6. • Regulators are concerned about high velocity “low touch” trade flow which
could interfere with market integrity
• Large number of orders (Retail and Institutional) across multiple marketplaces
presents significant challenges for surveillance
• Electronic Communications (“E Comm”) adds to this challenge with respect to
overlaying communications (Public Side, Private Side, Client Side)
• Challenge for Surveillance staff is to differentiate the abusive nature of the
market conduct from the means through which the activity is conducted.

7. • DEA and Foreign Broker/Dealer flow is a significant portion
of participant’s order flow subject to increased surveillance
for market conduct – potential manipulation
• The result is an increased need to conduct surveillance for
this order activity
• The primary requirement to conduct this level of
surveillance is an ability to link orders, executions, trades to
: News, Insider Trading, E Communications, MNPI, pump
and dump schemes

8. • Broker Dealers require enhanced data platforms to extract
historical order and trade data.
• Inter relation between asset classes (equity / options) as well as regional
trading (Long in North America/ Short in EU) has increased the need for
scalable and reliable and efficient data platforms.
• Global Direct Electronic Access and Routing Arrangements increase the
need to analyze trading patterns and overlay with surveillance alerts.

10. 10 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Big Data - Key focus areas within the financial services industry
Common Focus AreasSegments of Banking
Risk Mgmt
Cyber Security
Fraud Detection
Predictive Analytics
Data
Compliance
Digital Banking
360 degree
view
Customer
Service
Capital Markets
Corporate Banking and
Lending
Credit Cards &
Payment Networks
Retail Banking
Wealth & Asset
Management
Stock Exchanges &
Hedge Funds
+

11. 11 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Demand drivers for Big Data in Capital markets
Source: Celent
Catalyst Definition Example
Larger data sets Larger data sets allow analysts to query and conduct
experiments with fewer iterations
Omnichannel data, Tickers, price, volume and longer
time horizons. Social media/ third party data
New types of data New data types that need to be synthesized for traditional
relational databases
Business process data, Social Data, Sensor & device
data. OTC contracts and public filings.
Analytics and
visualization
More powerful analytics and visualization tools to explain
and explore patterns – Fraud, Compliance & Segmentation
Complex Event Processing (CEP), predictive analytics.
Portfolio and risk management dashboards
Tools and lower-cost
computing
Open source software tools. Lower server and enterprise
storage costs
Hadoop, NoSQL. Commodity hardware. Elastic
compute capacity.

12. 12 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Capital
Markets
Trade & Market
Surveillance
Market integrity & investor
protection
Trade Lifecycle
Trade strategy development,
backtesting across asset
classes; looking for
correlations etc.
Sentiment Analytics
Leverage Social Media and
other data feeds to drive
trading strategies and
portfolio rebalancing
decisions
Single View of
Customer
Single View of Customer
Activity & Risk across
multiple trading desks
Data Products
Analytic tools (statistical
modeling, functional grouping,
time series analysis) to clients
around trade data;
Capital Markets

14. Founding engineering team from
Teradata, HP, IBM DB2
Venture Funded
Production enterprise customers
in the Global 2000
Customers analyzing > 100 Billion data items
High concurrency and Strong SLA
– OUR FOUNDING VISION –
High performance and scalable visualization for Big Data
with absolutely zero data movement

15. • Data summarization
• Big data fidelity loss
• No collaboration
• Higher security risk
• Management and
operational complexity
Data
Traps
Order Book Market Data
Electronic
Communications
Trader Data OATS
Operational Data Sources

17. Distributed BI &
Analytics Engine runs
on each HDP node
Visualize Historical &
Real-time data in a
single platform
Closed-loop navigation
through to granular
data, rather than just
visualizing summaries
Fast Ad-hoc and
iterative analysis

18. A Powerful, Simplified Architecture
Arcadia Enterprise runs on-cluster, connecting business users directly to the data. Leverage the scale,
data and security infrastructure of your existing cluster
Explore quickly & directly, don’t start with data marts, cubes, or extracts
Simple visual interface to exploration and semantic modeling on ALL of your data. Our active data store
continuously models data based on usage for fast concurrent access
Self-service advanced analytical insight, no coding required
Arcadia Enterprise puts advanced analytical capabilities in the hands of business users. Support for real
time as well as free text based analysis. Features like behavior-based segmentation, event analytics,
dimension/measure correlations are just a few clicks away

19. • Connect Arcadia directly to Hadoop
clusters
• Share and collaborate with visual data-
driven applications
• High performance via
direct access to HDP
• Integrated Management
& Security with Hortonworks
• Deployable in-cloud, on-premises
and in hybrid environments

21. 21 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Leads to Current State Complexity
⬢ Hundreds of point-to point
feeds to each enterprise
system from each
transaction/order booking
system
⬢ Data is independently
sourced leading to timing
and data lineage issues
⬢ Close processes are
complicated and error
prone
⬢ Reconciliation requires a
large effort and has
significant gaps
Book of Record Transaction Systems
Enterprise Risk, Compliance and Finance Systems

22. 22 © Hortonworks Inc. 2011 – 2016. All Rights Reserved

23. Build a complete picture of trade
history quickly across markets and
exchanges.
Fast Attribute Filtering
Drill through to
raw data
Order Flow
Reconstruction

24. • Rapidly inspect and issue ad-hoc queries with
fast filtering across multiple attributes.
• Incorporate unstructured data (email, IM, news, social media) to
recreate a true point in time picture of trader activity.
• Combine historical and real-time data
visually to correlate current activities with historical ones.
• Embed static and interactive visuals easily into case management applications.
• Email alerting on key metric changes.
• Iterative analysis on subsets of derived data
without the need to extract to a spreadsheet.
• Quickly retrace activity around a large block
transaction in a point & click manner.

25. Blogs:
www.arcadiadata.com/blog/
http://hortonworks.com/blog/
http://www.vamsitalkstech.com/?p=1157
http://www.vamsitalkstech.com/?p=1212
Upcoming Hortonworks / Arcadia
Events
Future of Data Roadshow:
• Toronto: October 20
• Atlanta: November 17
• New York: December 08
For details: http://hortonworks.com/roadshow/
Arcadia – Hortonworks Solution Overview:
Hortonworks Sandbox:
http://hortonworks.com/products/sandbox/