Financial services front and back office applications require the use of various messaging standards and formats as well as an extremely scalable data ingestion and processing platform. This slide deck describes the benefits of GigaSpaces XAP in that specific context.

1. XAP FOR FINANCIAL SERVICES

2. AGENDA
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The Business Case for
Messaging Standards
Common Message Standards in the
Financial Vertical
Technical Challenges
GigaSpaces XAP
What’s Next

3. THE DRIVE FOR MESSAGING STANDARDIZATION
 Speed Up Trade Processing
 Reduce risk
 Support ever-growing
transaction rates
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4. THE DRIVE FOR MESSAGING STANDARDIZATION
 Reduce Fragility and Trade Processing Costs
 Decrease manual intervention
 Standardize IT system achieving uniform protocols shared
by banks and different markets
 Transform back office silos and diversity into uniform stack
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5. MESSAGING STANDARDS IN THE FINANCIAL MARKETS
FpML
(Financial products
Markup Language )
FIXML
(Financial Information
eXchange Markup
Language)
XBRL
(eXtensible
Business Reporting
Language)
Swift / ISO
20022
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6. SWIFT UTILIZATION OF STANDARDS
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Pre-Trade / Trade
Post- Trade / Pre-
settlement
Clearing and
settlement
reporting
Asset servicing
Portfolio
administration
Payments and
cash
management
Collateral
Management
Financing
securities
lending and
borrowing
IOI/ Quotes, Trade,
Execution, Pre-
allocation
Trade allocation,
Trade affirmation,
confirmation,
notification and
matching,
Transaction reporting
Settlement
instructions,
confirmation,
Statements of
pending
settlements,
Statements of
movements
Data distribution,
Corporate actions,
Proxy voting
Total portfolio
administration
Payments
initiation, Cash
reporting,
Exception and
investigation
Margin calles,
Reponse,
Administration
Repo, Reverse
repo, Trade
confirmation and
matching,
Settlement and
reporting
ISO, FIX ISO, FIX, FpML ISO ISO ISO ISO ISO ISO
Equities, Fixed
Income, Listed
derivatives
Equities, Fixed
income, Listed
derivatives FX, MM
and FX options,
Syndicated loans,
Commodities, OTC
derivatives
Equities, Fixed
income, Listed
derivatives
Equities, Fixed
income, Listed
derivatives
Cash, Funds Cash Cash, Securities
and bank
guaranties
Equities, Fixed
income, Repos

7. WHAT IS NEEDED
 A fast, scalable and reliable data
integration platform to bridge front office
and back office
 Allow Straight Through Processing for many
millions of trades
 Better reconciliation through complex real time
matching
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8. THE TECHNICAL CHALLENGES
 Support for complex yet fast queries over
large set of data:
 Deeply nested object graphs
 Many millions (or even billions) of objects
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9. THE TECHNICAL CHALLENGES
 Store massive amounts of data for the
longer term:
 Tens of millions of messages a day, or more…
 Working set is relatively small (typically up to a
few days worth of data)
 But longer term analysis (and regulation) requires
data to be persisted for years
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10. THE TECHNICAL CHALLENGES
 Quickly adjust to ongoing standards
updates and message format variations
 Reduce time to market
 Reduce unexpected runtime errors and mistakes
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11. THE TECHNICAL CHALLENGES
 Easily implement various event based
workflows using the same data platform
 By processing the data in place
 Or as it flows into the system
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12. THE TECHNICAL CHALLENGES
 Provide a native, easy
to use programming
interface for
developers
 I work in Java / Scala (or
any other language for
that matter)
 I want my type safety
 I want my intellisense
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13. STEP BACK – IN MEMORY COMPUTING
13
“In memory computing (IMC) … provides
transformational opportunities. The execution of
certain-types of hours-long batch processes can be
squeezed into minutes or even seconds …
Millions of events can be scanned in a matter of a few
tens of millisecond to detect correlations and patterns
pointing at emerging opportunities and threats "as
things happen.”

14. IN MEMORY IS MORE ECONOMICAL THAN BEFORE

15. THE PROBLEM
Current architectures
Perform complex calculations in real time to improve your business performance, e.g. recommendations/
promotions in an e-commerce web site, instant risk analysis / reconciliation in investment banks (STP)

16. IMC FOUNDATIONS
Ultra High Performance
High Availability
Linear Scalability

17. PUTTING IT INTO YOUR STACK
GigaSpaces

18. KEY FEATURES
Schema Free Data Model
schema-free data API that supports upgrading the application’s
data model on the fly
Indexing
Predefined and ad-hoc property indexing for blazing- fast data
access
Querying
Sophisticated query engine with support for SQL and example
queries
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19. Data partitioning
Transparent content-based data partitioning to evenly and
intelligently distribute data across servers
Fully ACID Transactions
Local, distributed or XA
Two Way NoSQL Integration
For long term data storage and loading
CORE CAPABILITIES - DATA
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20. Native to Scala and Java/Spring
Use Scala-native constructs such as immutable objects, predicates
and closures
Strong Eventing Support
React in real time, in place, to changes to the data
In-Grid, Distributed Code Execution
Dynamic code loading and map/reduce like execution across the
grid for optimized processing and data access
CORE CAPABILITIES - DATA
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21. ® Copyright 2011 Gigaspaces Ltd. All Rights Reserved
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Challenge Solution
Frequent message format changes Schema free model
Complex, sub second queries XPath like queries on objects and strong
indexing support
Store massive amounts of data for the
longer term
Built in NoSQL integration
Process messages as they flow into the
system
Event containers and distributed code
execution
Developer friendliness Native Java/Spring, Scala support
MEETING THE CHALLENGES, OR WHY USE XAP

22. Thank You!
® Copyright 2011 Gigaspaces Ltd. All Rights Reserved22