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GigaSpaces XAP for Financial Services

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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 …

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.


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  • 1. XAP FOR FINANCIAL SERVICES
  • 2. AGENDA 2 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 3
  • 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. 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. 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. 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. 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. 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. 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. 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. 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. 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 18
  • 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. 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. ® 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. Thank You! ® Copyright 2011 Gigaspaces Ltd. All Rights Reserved22