DataArt: Capital Markets – Case Studies


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DataArt: Capital Markets – Case Studies

  1. 1. January 29, 2015 1 DataArt: Capital Markets – Case Studies
  2. 2. January 29, 2015 2 Business Analysis (both in New York and Russia) Requirements Management (both in New York and Russia) Development and QA Post- Project Support Sample projects Front-office: cross-asset class trading, execution, allocation BA expertise is present, but not as strong as in Middle- Office Participate in and lead Requirements Management process for most of projects awarded to us Implemented over 20 systems in the past 3 years 90% of systems developed by DataArt continue to be maintained and supported by us • Cross-asset class OMS and Position Exporer for an ISV client (50,000 hrs effort) • Algo execution system for an ISV (10,000 hrs effort) • Trade Capture system for a Hedge Fund Administrator (10,000 hrs effort) Middle-office: reference data management, risk management, operations Very substantial experience in reference data management, ready to use BA team More than 15 onsite specification sessions Implemented over 30 systems Software and operations support in maintenance of reference T&C and other market data • Global Security Master for a Hedge Fund Administrator (5,000hrs effort) • Price Master for an ISV • Risk Management System for $2Bln Hedge • Stock loan management system Back-office: accounting and treasury, reconciliation, settlement Expertise in integration with popular fund accounting systems, including Geneva, VPM, AdvisorWare Both onsite and offshore Strong experience in reconciliation process (trades, positions, cash, margins). Implemented data adapters for all major Prime brokers. Post project support and reconciliation process assistance, custom accounting report writing • Reconciliation tool for a Hedge Fund Administrator and a number of Funds • Post-trade settlement process workflow Elaborate on your experience in business analysis, user requirements analysis, design and development of such systems. Moderate Moderate Strong Strong Strong Moderate Very Strong Exceptional Very Strong Very Strong Very Strong Very Strong
  3. 3. Primary Areas of Buy-Side Expertise January 29, 2015 3 Asset Management (including Alternative Asset Management) Functional View
  4. 4. Client: Large Financial ISV (client reference available under NDA). Project: Investor Relationship Management System Fund Accounting module in IRM / Fund Profiling solution •Advanced hierarchical structure of investor’s accounting information. Tracking balance and performance data at custodian, fund, subscription level. •Series accounting, profit allocations, roll-ups •Contributions, withdrawals, transfers •Liquidity analysis, what-if scenarios, stress testing •50+ standard reports •Integration With Third-Party Accounting Systems — VPM — Advent Geneva — Advent Partners — SS&C AdvisorWare Fund Accounting January 29, 2015 4
  5. 5. Clients: Multiple (both Hedge Funds directly and a product for an ISV) Projects: Investor Relationship Management System (fund performance / investor reporting modules) Fund Performance data: Based on time series of NAV (returns) of fund (products) and benchmarks (market indices) we can provide analytical information for fund performance. • Performance data - Historical and analytical data, Graphs with comparison of the fund data and more than 8 market indices, Classical statistical functions: Distribution, Alpha, Volatility, Correlation and Sharpe, Rolling by 12, 24, 36 months, Cumulative performance: quarter, 1 year, 3 years and 5 years comparison, Performance reports • Fund performance management - Fund performance analysis against indices such as CSFB/Tremont, Dynamic reports with charting support, Market comparison, Historical data import and analysis • Integration - Automatic Bloomberg data feeds for benchmark indices, External websites information retrieval, Corporate website integration, secure investor reporting Benchmarking January 29, 2015 5
  6. 6. Individual Investor Performance Analyzing investor transactions is possible to evaluate individual performance and provide comparison with the fund (product) or benchmark performance. • Overall investor performance • Investor performance by products • Investor performance comparison with benchmark • Individual performance analytics — Correlations — Drawdown — Growth of dollar Benchmarking (continued) January 29, 2015 6
  7. 7. • Integration with major Market data Providers (both file-based and real-time) — IDC services: – SIRS – IDSI – FTS (EXSHARE/EXBOND) — Reuters – Reuters Market Data System – Reuters Data Scope — Bloomberg – B-Pipe – B-Desktop ActiveX – Bloomberg Data License (T&C bulk load) • Integration with popular third-party products: — OMS/PMS: Macgregor, Charles River, Eze Castle, Alladin, Beauchamp, Tradar, Sophis — Accounding: VPM, Geneva, AdvisorWare — EMS: Inforeach, Portware — Analytical packages: Imagine, RiskMetrics, Barra, Yieldbook, Factset, FMC Data Interfaces (multiple clients and projects) January 29, 2015 7
  8. 8. Integration with major prime brokers (data adapters for position, trades and cash reconciliation) •Bear Sterns (BEST) •Morgan Stanley (MSCO) •Morgan Stanley SWAP (MSCOOTC) •Goldman, Sachs & Co. (GSCO) •Lehman (LEHM) •Lehman Futures (LEHMF) •Citibank (CITI) •UBS •Deutsche Bank (DMG) Data Interfaces (continued) January 29, 2015 8
  9. 9. • Familiar with FIX versions 4.0 through 5.0; FIXML, ISO 20022 • We have worked/integrated with several popular FIX implementations, including Javelyn (NYFIX), B2Bits FixAntenna/FixEdge, FixFlyer for various applications. • Member of our Advisory Board sits on FIX Technical Committee • Implemented FIX monitoring/performance management tools FIX Protocol January 29, 2015 9
  10. 10. 10 Technology Client Case Study: Front-to-Back Office Enterprise Solution for Hedge Funds (client name disguised)  Working under leadership of US-based business domain experts  Technology and architecture decisions are done within DataArt's team and approved by the client  System-based engineering team organization with universal functions shared across teams (QA, tech writing, service)  "Agile" process Project description  Developed complete front-to-back office enterprise solution for hedge funds, including cross-asset class order management, Global Security Master, portfolio analytics, pricing and reporting (excluding only accounting)  The solution is available to hedge funds and fund administrators as a hosted platform or an in-house installation.  Solution is adapted by one of the leading prime brokers as their base offering to hedge fund clients; other clients include over 10 fund administrators and many multi-billion hedge funds.  This technology is developed entirely offshore with relatively little US-based leadership. While many technology vendors use offshore resources for parts of their project volume, this is a unique story as fast-growing, well-funded ISV relied completely on offshore vendor for end-to-end IT operations. Technology  Microsoft platform (.NET, SQL Server 2005), Citrix Timelines   1.5 years Client benefits   40% savings compared with local cost (if client were to build its own team)  Time saved by engaging an readily available team vs hiring own team – 9-12 months Team configuration  30 people, 60% engineering, 20% QA, 20% technical support Project management 
  11. 11. 11  Developed a new generation Investor Relationship Management system for hedge funds and a fund profiling  system for fund of funds.  Replaced legacy system.   System deployed at over 200 asset managers with total of more than $250 billion Assets Under Management.   Product is a true enterprise class system with advanced functionality unquestionable leader among other competing  products.  2 years   Team of 15 engineers based offsite, periodic onsite milestone delivery, implementation and integration  Working as an extension to the client’s R&D team   30% savings compare to onsite costs  Client did not have inhouse resources to do the work necessary   Over 1 year time saving if client were to hire people to do the work internally  Microsoft .Net platform Project description Technology Timelines  Client benefits  Team configuration Project management    Multiple priorities had to be managed simultaneously: re-engineering legacy product, supporting  existing customers and adding new functionality Technology Client Case Study: Fund Runner (SS&C)
  12. 12. 12 Key features:  Fast and reliable communication with electronic brokers  Supports of electronic orders to perform ticket execution  Easy integration with third-party solutions for electronic  connectivity   Flexible support of different versions of FIX  Supports common scenarios  Standard Electronic Order Routing   Staging Order Destination  Third-Party Algorithmic Routing   Unsolicited Trade Reports  Case Study: Electronic Trading System with FIX connectivity FIX connectivity could be linked directly with various Sell-Side venues, including:  Direct Market Access (DMA) systems  Execution Management Systems (EMS)  Alternative Trading Systems (ATS) Architecture:   The Electronic Trading is performed through  Order Management Gateway (OMG) that is  connected to a FIX Engine. The FIX Engine  manages all physical FIX connections to various  destinations. In terms of electronic order  routing, OMG works with any standard FIX  Engine (running separately from OMG).   Currently, the system supports Appia FIX  Engine from NYFIX. 
  13. 13. 13  Complex trading workflow  Real-time collaboration  Portfolio analysis  Integration with legacy and external systems  Quick response to user requests  Modular design, shared components Highlights: Case Study: Trade Order Management System Integrated Trade Order Management  System Client: New York-based Hedge Fund
  14. 14. 14 Global Enterprise Market Data  Repository   Multi-source architecture  Automated pricing rules  Advanced UI  Data transformation Audit  HTTP Crawler for OTC securities  Exchange adapter for Prime broker market  data  Integration with leading market data providers:  Bloomberg, Reuters Highlights: Case Study: Multi-source pricing application (Price Master) Client: New York-based Hedge Fund
  15. 15. 15 Case Study: ETL and Pricing Data Warehouse Price Master: a global enterprise market data repository which plays a key role in STP  data flow of a financial organization. Its primary task is to collect instrument prices and other  market data from various data sources, parse it and using pricing rules provide a final set of  information for downstream systems.  Client: Multi-Strategy Hedge Fund with $2+bln AUM BUSINESS BENEFITS:  Single-entry point for all market related data  Supports various types of securities and various types of market  data  Pricing rules provide stable and flexible system for portfolio  pricing  Advanced audit and change tracking features HIGHLIGHTS  Advanced Data mapping  Extraction rules  BizTalk as a integrating and mapping  software  Dynamic Data structure system - XML  base schemas support Client: New York-based Hedge Fund
  16. 16. 16 Case Study: ETL and Pricing Data Warehouse  .Net C#  .Net Remoting  Web services  MS SQL 2000  BizTalk Server 2004  Infragistics Enterprise suite Client: New York-based Hedge Fund
  17. 17. 17 Case Study: ETL and Pricing Data Warehouse  Various data sources  System prioritization and pricing rules  Support for multiple types of securities  Flexible architecture provides ability to easily add new types of source data  Unified data management and conflict resolution systems  Highly customizable UI Client: New York-based Hedge Fund