XAP FOR FINANCIAL SERVICES
AGENDA
2
The Business Case for
Messaging Standards
Common Message Standards in the
Financial Vertical
Technical Challenges...
THE DRIVE FOR MESSAGING STANDARDIZATION
 Speed Up Trade Processing
 Reduce risk
 Support ever-growing
transaction rates...
THE DRIVE FOR MESSAGING STANDARDIZATION
 Reduce Fragility and Trade Processing Costs
 Decrease manual intervention
 Sta...
MESSAGING STANDARDS IN THE FINANCIAL MARKETS
FpML
(Financial products
Markup Language )
FIXML
(Financial Information
eXcha...
SWIFT UTILIZATION OF STANDARDS
6
Pre-Trade / Trade
Post- Trade / Pre-
settlement
Clearing and
settlement
reporting
Asset s...
WHAT IS NEEDED
 A fast, scalable and reliable data
integration platform to bridge front office
and back office
 Allow St...
THE TECHNICAL CHALLENGES
 Support for complex yet fast queries over
large set of data:
 Deeply nested object graphs
 Ma...
THE TECHNICAL CHALLENGES
 Store massive amounts of data for the
longer term:
 Tens of millions of messages a day, or mor...
THE TECHNICAL CHALLENGES
 Quickly adjust to ongoing standards
updates and message format variations
 Reduce time to mark...
THE TECHNICAL CHALLENGES
 Easily implement various event based
workflows using the same data platform
 By processing the...
THE TECHNICAL CHALLENGES
 Provide a native, easy
to use programming
interface for
developers
 I work in Java / Scala (or...
STEP BACK – IN MEMORY COMPUTING
13
“In memory computing (IMC) … provides
transformational opportunities. The execution of
...
IN MEMORY IS MORE ECONOMICAL THAN BEFORE
THE PROBLEM
Current architectures
Perform complex calculations in real time to improve your business performance, e.g. rec...
IMC FOUNDATIONS
Ultra High Performance
High Availability
Linear Scalability
PUTTING IT INTO YOUR STACK
GigaSpaces
KEY FEATURES
Schema Free Data Model
schema-free data API that supports upgrading the application’s
data model on the fly
I...
Data partitioning
Transparent content-based data partitioning to evenly and
intelligently distribute data across servers
F...
Native to Scala and Java/Spring
Use Scala-native constructs such as immutable objects, predicates
and closures
Strong Even...
® Copyright 2011 Gigaspaces Ltd. All Rights Reserved
21
Challenge Solution
Frequent message format changes Schema free mod...
Thank You!
® Copyright 2011 Gigaspaces Ltd. All Rights Reserved22
Upcoming SlideShare
Loading in …5
×

GigaSpaces XAP for Financial Services

897 views

Published on

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.

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
897
On SlideShare
0
From Embeds
0
Number of Embeds
45
Actions
Shares
0
Downloads
21
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

GigaSpaces XAP for Financial Services

  1. 1. XAP FOR FINANCIAL SERVICES
  2. 2. AGENDA 2 The Business Case for Messaging Standards Common Message Standards in the Financial Vertical Technical Challenges GigaSpaces XAP What’s Next
  3. 3. THE DRIVE FOR MESSAGING STANDARDIZATION  Speed Up Trade Processing  Reduce risk  Support ever-growing transaction rates 3
  4. 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 4
  5. 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 5
  6. 6. SWIFT UTILIZATION OF STANDARDS 6 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. 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 7
  8. 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 8
  9. 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 9
  10. 10. THE TECHNICAL CHALLENGES  Quickly adjust to ongoing standards updates and message format variations  Reduce time to market  Reduce unexpected runtime errors and mistakes 10
  11. 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 11
  12. 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 12
  13. 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. 14. IN MEMORY IS MORE ECONOMICAL THAN BEFORE
  15. 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. 16. IMC FOUNDATIONS Ultra High Performance High Availability Linear Scalability
  17. 17. PUTTING IT INTO YOUR STACK GigaSpaces
  18. 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 18
  19. 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 19
  20. 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 20
  21. 21. ® Copyright 2011 Gigaspaces Ltd. All Rights Reserved 21 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. 22. Thank You! ® Copyright 2011 Gigaspaces Ltd. All Rights Reserved22

×