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Big Data vs. Big Risk: Real-Time Trade Surveillance in Financial Markets


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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.

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Big Data vs. Big Risk: Real-Time Trade Surveillance in Financial Markets

  1. 1. Real-Time Trade Surveillance in Financial Markets Winning the Deep Forensic Analysis Arms Race for Compliance
  2. 2. Vamsi Chemitiganti General Manager – Financial Services HORTONWORKS Shant Hovsepian Co-Founder & CTO ARCADIA DATA David M. Fishman VP Marketing ARCADIA DATA Moderator Shailesh Ambike Executive Co-Chair, Compliance & Legal Section (CLS) Education Sub-committee INVESTMENT INDUSTRY REGULATORY ORGANIZATION OF CANADA (IIROC) Panelists
  3. 3. Agenda 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
  4. 4. Capital Markets: Background, Behavior, Risk, and the New Reality
  5. 5. Market Conduct - Background • 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. 6. Risks to Market Integrity – Automated Order Systems • 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. 7. Direct Electronic Access / Foreign Routing Arrangements – added complexities • 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. 8. New Reality – Big Data Analytics • 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.
  9. 9. Role Of Big Data in Financial Services & Capital Markets
  10. 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. 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. 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
  13. 13. Introduction To Arcadia Data + Hortonworks Solution
  14. 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 Create business value from Big Data – OUR FOUNDING VISION – High performance and scalable visualization for Big Data with absolutely zero data movement
  15. 15. Challenges of Trade Surveillance in a Big Data world • Data summarization • Big data fidelity loss • No collaboration • Higher security risk • Management and operationalcomplexity BI/VIZ TOOLS BI/SERVER (CUBES) DATA MART (EXTRACTS) DATA WAREHOUSE (EXTRACTS) ALL DATA <EXTRACTS> DATA USERS /ANALYSTS Data Traps Order Book Market Data Electronic Communications Trader Data OATS Operational Data Sources
  16. 16. How Does Arcadia Data Change This?
  17. 17. Distributed BI & Analytics Engineruns 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 Arcadia Data Converged Analytics Platform Fast Ad-hoc and iterative analysis
  18. 18. What makes Arcadia Data different 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 The only Hadoop Native Analytics Platform™:
  19. 19. Arcadia – Hortonworks Integration • 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
  20. 20. Customer Use Case: Real-time Trade Surveillance Customer: Financial Services and Banking giant in North America
  21. 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. 22 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
  23. 23. Compliance Officer Toolbox Build a complete picture of trade history quickly across markets and exchanges. Fast Attribute Filtering Drill through to raw data Order Flow Reconstruction
  24. 24. Compliance Officer Toolbox • 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. 25. Resources Blogs: Upcoming Hortonworks / Arcadia Events Future of Data Roadshow: • Toronto: October 20 • Atlanta: November 17 • New York: December 08 For details: Arcadia – Hortonworks Solution Overview: Hortonworks Sandbox:
  26. 26. Q&A