John Avery discusses opportunities in big data and graph analytics for financial services. Big data involves storing, processing, and analyzing large amounts of structured and unstructured data across distributed systems. It can help financial firms reduce the effort to analyze more data and enable new types of analyses. Graph analytics uses relationships in data to power applications in areas like risk management, trading, and regulatory compliance. Firms should explore applying these technologies to problems like counterparty risk analysis, market surveillance, and systemic risk oversight.

1. www.sungard.com
Opportunities in #BigData & Beyond
John Avery
Partner
SunGard Global Services
Nov 18, 2010

2. Why am I here?
Professional
• SunGard #2 in 2010 FINTECH 100
• Products & Services across the FS spectrum
• Exploring impacts of Big Data approach for past
18 months
Personal
• 13+ years of development on Wall Street
• Intersection of Global Services Advanced
Technology & Information Management Practices
• Development + Databases + Data Warehousing
+ Trading + Risk Management

3. What is #BigData?
 An approach to storing, processing & analyzing
data that
 Can be “Internet” scale - think Google, Facebook, LinkedIn,
Yahoo, Twitter
 “Not Just Relational” - augments and/or supplements
traditional relational databases and approaches
 Economically leverages commodity or cloud-based hardware
using the more flexible & scalable NoSQL ecosystem
 Enables analysis & insight on data & problems typically left out
to pasture
Parallel Distributed Analysis
Parallel Distributed Processing
Parallel Distributed Storage
Machine 1 Machine 10 Machine 100 Machine N

4. Why is #BigData Important?
Data is Growing Faster
than “Moore’s Law”
• Americans consuming on average
34GB/day and uploading 15x more
data in 2009 than 2006
• 281 exabytes of online data in 2009
• Business cycle across technology
sector very dependent on 40+ years
of Moore’s Law assumptions
In Financial Services the
quest for global trading,
risk & transparency creates
an insatiable need for data
• Regulatory Reform / Systemic Risk
Oversight
• Hi-Fi trading is 50-75% of cash
trading market activity today
• The Rise of Unstructured Data &
Social Network Analysis

5. The #BigData Opportunity in Financial Services
Take hint from “Internet Scale” B2C players who manage
hundreds of terabytes more than what financial services
require
• Reduce the effort & time to aggregate & analyze data
• Economically enable new classes of analysis
As an industry, there is no “killer app” for Big Data yet,
firms are exploring & learning on their own
• Explore new analyses of current & historical system data
• Use new programming languages & tools to create solutions
Get continued leverage on legacy systems by exposing
their data
• Expose vertical system data in its raw form to the NoSQL technology
ecosystem - in parallel with any other data management initiatives
• Years & Years of Proprietary Data History - Can this data be packaged up &
resold?

6. What I Find Interesting About @AsterData
5+ Years of Big Data and Advanced Analytics
Commercial, Not Open Source
Creating a bridge to a world of SQL-trained Developers & Analysts
Exposing data to a world of xDBC database access code (Java, .NET,
etc…)
Providing Big Data analysis abstractions on top of SQL
(e.g.,: SQL-MapReduce)
Baked-in “Graph” analytics (more on this in forthcoming slides)

7. Will #BigData evolve into SmartData (or #BigGraph)?
Freedom from perceived (or real) relational constraints via
BigData
• Regulatory Transparency
• Requires consistency & connectedness – globally
• Unstructured Data
• News, Social Media, Machine learning, linguistics,
etc…
• Mobile & Tablet Interfaces
• Create a new and rapidly growing need for integrated
aggregated data in digestible & relevant form
• Social Networks
• Remind us of hundreds of years of graph theory
• Recent Google Infrastructure Overhaul
• Elevated importance of graph-based processing

8. Graph Analytics in Retail Banking

9. Graph Gallery 1 – MBS Market Structure
Image credits - @ValidsKrebs on Twitter

10. Graph Gallery 2 – Counterparty Networks
Image credit - @ValidsKrebs on Twitter

11. Immediate Opportunities for Graph Analytics
Wealth & Investment
Management
• Portfolio analysis &
construction
Trading
• Pre-trade analysis
• Unstructured data input into
algo trading + backtesting
Risk
• Counterparty Credit Risk
Network Analysis
Regulatory &
Compliance
• Systemic Risk Transparency
• Surveillance & Fraud
Detection
• Behavioral Analysis

12. Will Richer Semantics enable more Graph Analytics?
Can These Be Input into A Whole New Class of
Relationship Based Graph Analyses?
Counterparty
Relationships
Financial Product
& Portfolio
Relationships
Fundamental
Balance Sheet
Analysis
Market Structure
Analysis
Structured Data Formats du jour
XBRL SWIFT FPML Proprietary

13. BigGraph Opportunity #1 – Pre-Trade Analysis
 Commodities Markets
 Thousands of relationships
upon relationships
 Freight <-> Oil
 Oil, Gas, Coal <-> Power
 Base metals <-> Industrials
 Agriculture <-> Fuels
 Agriculture <-> Foods

14. BigGraph Opportunity #2 – Risk Management
For A Single
Entity
• Counterparty
relationships
intersecting with
financial instruments
Across Entities
• Counterparty
relationships
intersecting with
financial
instruments
Systemic Risk
Oversight (US
FSOC & Office
of Financial
Research)
Image credit - @ValidsKrebs on Twitter

15. A Call to Action – Wholesale Financial Services
The tools are here!
We need more
exploratory application
of the technology to new
or unanswered problems
in the institutional world
We need more
Advocacy of Exploration
We need more People
interested and beginning
to Explore
We need more POCs

16. Let’s Chat
 John Avery, SunGard Global Services
 John.Avery@SunGard.com
 On Twitter
 @john_avery
 Hashtags
 #BigData
 #NoSQL
 #GraphDB

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