Winning the Deep Forensic Analysis Arms Race for Compliance

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

• 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 Bonafideintra day order activity, Insider trading

• Recent cases include: ITG (fine), Knight Capital, E*Trade (G1 Execution Services – G1X)

• 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.

• 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

• 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.

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Big Data - Key focus areas within the financial services industry

Common Focus AreasSegments of Banking

Risk MgmtCyber Security

Fraud Detection

Predictive Analytics

Data

ComplianceDigital 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

+

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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.

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Capital Markets

Trade & Market Surveillance

Market integrity & investor protection

Trade Lifecycle Trade strategy development,

backtesting across asset classes; looking for

correlations etc.

Sentiment AnalyticsLeverage 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 ProductsAnalytic tools (statistical

modeling, functional grouping, time series analysis) to clients

around trade data;

Capital Markets

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 Datawith absolutely zero data movement

• Data summarization

• Big data fidelity loss

• No collaboration

• Higher security risk

• Management and operational complexity

DataTraps

Order Book Market Data Electronic Communications Trader Data OATS

Operational Data Sources

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

A Powerful, Simplified ArchitectureArcadia 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 extractsSimple 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 requiredArcadia 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

• Connect Arcadia directly to Hadoopclusters

• Share and collaborate with visual data-driven applications

• High performance via direct access to HDP

• Integrated Management & Security with Hortonworks

• Deployable in-cloud, on-premisesand in hybrid environments

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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

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Build a complete picture of trade history quickly across markets and

exchanges.

Fast Attribute Filtering

Drill through to raw data

Order Flow Reconstruction

• 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.

Blogs:www.arcadiadata.com/blog/http://hortonworks.com/blog/http://www.vamsitalkstech.com/?p=1157http://www.vamsitalkstech.com/?p=1212

Upcoming Hortonworks / Arcadia EventsFuture 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/