The Future of Capital Markets. i Irfan Khan, (@i_khana) SVP & CTO SAP Database & Technology, SAP AG.

Transcription

1 The Future of Capital Markets Reimagined i Irfan Khan, (@i_khana) SVP & CTO SAP Database & Technology, SAP AG.

2 SAP Has a substantial presence in Capital Markets Top 20 banks use SAP for market and/or credit risk 45% of front and middle office operations run on SAP 3.2 million live market quotes/ second powered by SAP HANA and SAP ESP 400 Business Analytics clients database clients 50 Cloud clients 2013 SAP AG. All rights reserved. 2

3 Select customers in capital markets Today Trading and/or Risk Management Business Analytics Cloud Enterprise Applications 2013 SAP AG. All rights reserved. 3

4 SAP capital markets ecosystem SIs ISVs, ASPs & Content Providers Analytics Structured Products Pricing Data Vendors Market and Reference Data News News Analytics Sapient Derivatives Analytics R statistical language Time Series Analysis 2013 SAP AG. All rights reserved. 4

5 SAP Assertions - What is shaping our future thinking? Today s Enterprise Landscape Evolution of IT Systems Increased Real-time capabilities Increased Predictive Analytics Increased Landscape simplification New Deployment models & Architectures New Data & Application paradigms New Open Technology Stack 2013 SAP AG. All rights reserved. 5

6 Real-time enterprise is the new frontier Smarter Algorithms Flash crash fever Market Data in Cloud Emerging Markets Government Regulations Left Brain Right Brain Precision Trading News Analytics In-memory Multi-asset Risk Modeling Cloud Social Mobile Sentiment Analytics Run-the Business Grow-the Business 2013 SAP AG. All rights reserved. 6

7 Fundamental Shifts in Economics Up-Time COSTS RISING WHILE H/W Infrastructure COSTS Declining d Managing complexity Consultants Business disruptions Energy and Operations Hardware per unit performance Integration tools Communications infrastructure Data storage Data processing 2013 SAP AG. All rights reserved. 7 7

8 Banking Firms infrastructure is at a critical inflection point Government Regulations Flash crash fever Emerging Markets Smarter Algorithms Innovation & Transformation Personal Computer Distributed Computing WWW B2B/ B2C Internet Self-Service Technology Value Mobile Multi- Channel Social Application Silos, Data Sprawl Cloud Service- Level Challenges Big Data Real-Time Computing Scalability Limitations Technology Debt End-of-Life Market Data in Cloud Precision Trading News Analytics Multi-asset Risk Modeling Sentiment t Analytics Legacy Maintenance 2013 SAP AG. All rights reserved. 8

9 Critical success factors for trading infrastructure Q. What are the key components of a fully managed trading infrastructure (Please check all applicable)? Low latency data Trading network Access to global markets Colocation/proximity environment Access to multiple asset classes Risk controls Reference data/back-testingtesting Latency monitoring SOR Strategy testing lab Compliance reporting Post-trade capabilities Anti-gaming Liquidity souring capabilities EMS/OMS Canned execution algorithms SOURCE: Aite Group 2013 SAP AG. All rights reserved. 9

10 Firms Need to rethink Infrastructure Foundations REIMAGINING THE DATA Processing FOUNDATIONS Natively In-Memory Massively Parallel OLTP + OLAP Structured + Unstructured Legacy + New 3B Scans /s /core 12.5M aggregates /s /core 1.5M inserts/s 250TB HANA Cluster: World s Largest In-Memory System 2013 SAP AG. All rights reserved

11 SAP HANA: In-memory platform Semantics Breakthrough Transaction and Analytics Performance Insert: 1.5M Records/sec ROW BUFFER COLUMN BUFFER COLUMN STORE Harvest Insight in Real Time 2013 SAP AG. All rights reserved. 11

12 SAP HANA: In-memory platform Transforming the core, enabling next generation Capital Market applications Developers Data Scientists Traders Risk Managers Consumers Applications & Tools Industry LoB Consumer Analytics Social Cloud Mobile SAP HANA PLATFORM Development Con nnectivity Lifecycle Manageme ent Services Application Services Application Server UI Integration Services Web Server Processing Engine Event Processing Planning Calculation Predictive Analytics Database Services Transactions Analytics Partitioning Compression Availability Encryption Rules Text Mining Search Application Function Libraries Geospatial Integration Services Mobile XaaS High-volume Replication Real-time Replication Hadoop Unified Adminis stration Security Services 2013 SAP AG. All rights reserved. 12

13 SAP HANA: In-memory platform Process ANY Data, in ANY combination, instantaneously with SQL Embed sentiment fact extraction in same SQL Embed geospatial in same SQL Analyze using standard SQL. Embed fuzzy text search in same SQL CREATE FULLTEXT INDEX i1 ON PSA_TRANSACTION( AMOUNT, TRAN_DATE, POST_DATE, DESCRIPTION, CATEGORY_TEXT ) FUZZY SEARCH INDEX ON SYNC; SELECT SCORE() AS SCR, * FROM "SYSTEM"."PSA_TRANSACTION" WHERE CONTAINS (*, 'Sarvice', fuzzy) ORDER BY SCR DESC; SQL Advanced text analytics Analyze text in all columns of table and text inside binary files with advanced text Structure unstructured data Use advanced text analytics, such as sentiment fact extraction, to structure unstructured data. Streaming data Analyze streaming data from integrated t ESP in combination with data in SAP HANA. SAP HANA Geospatial data Analyze streaming data from integrated ESP in combination with data in SAP HANA. Any Data Customer Data RFID HADOOP Mobile Point of Sale Geospatial Machine Time Structured Data Data Series Data Clickstream lk Social Network Text Data 2013 SAP AG. All rights reserved. 13

14 SAP In-Memory Data Management innovation Time compression is a competitive advantage The Thirty-millisecond advantage In high-frequency trading, computers buy and sell stocks lightning fast. Some marketplaces, like NASDAQ, often offer such traders a peek at orders for 30 milliseconds 0.03 seconds before they are shown to everyone else. This allows traders to profit by very quickly trading shares they know will soon be in high demand. Each trade earns pennies, sometimes millions of times a day. 9:31:00 a.m. Investor submits order A slow-moving mutual fund submits an order to purchase 5,000 shares of company XYZ 9:31: :31:00.03 a.m. Fast traders get to preview orders Before that order is sent to the broad marketplace, it is routed to highfrequency traders for 30 milliseconds 9:31:00.05 a.m. Traders buy The high-frequency traders, knowing that an order is coming, flood the market with buy orders, scooping up all available shares of XYZ at $ :31:00.30 a.m. Mutual fund orders executed The mutual fund order hits the marketplace, and the high-frequency traders sell their shares at $21.01, pocketing the 1-cent profit for a total of $50 in this case Share price $21.02 $21.01 Cache VS Order Pre-trade analytics Algorithmic Execution Transactions + Analysis Directly Inmemory Elapsed time 0.0 seconds seconds The New York Times $ SAP AG. All rights reserved. 14

15 Enabling next-generation Real-time Trading Traditional Market Data Currency rates Volume rates Pricing Volatility Order Depth Algorithms are approved for production Model Definition Defining the Trades Model Explosion Model Back-testing Research & Development Live Trading Portfolio Allocation Executing Model Refinements Attribution Algorithms refinements Events used as circuit breakers in trading Recorded Future Atomic Events Momentum Hedges Composites of events Sentiment 2013 SAP AG. All rights reserved. 15

16 Solutions across the life-cycle Pre-trade Trade Post-Trade Publish Prices, Decide to Trade Place Order Market Analysis Trade Execution Positions, Risk Compliance Market Data Enrichment Select source Filter Combine Analyze Consolidated Order Book (MLA) Auto-pricing Quantitative Trading Algorithmic Execution Smart Order Routing Real-time Risk Monitoring, i Limitsit Risk Aggregation Order Flow Monitoring Real-time P&L Short range data analytics Deep history with complex math/stat analysis Benefit from in-memory capability 2013 SAP AG. All rights reserved. 16

17 Liquidity Risk Management Enabling new generation of applications Liquidity Risk App SAP HANA ETL Cash Flow Engine Strategy Analyzer Operational Systems Loans Deposits Securities Derivatives 2013 SAP AG. All rights reserved. 17

18 SAP Liquidity Risk Management test results 290M Cash Flows >60 minutes Latest result: 1.8 billion cashflows in 2.4 seconds 4000x faster Aggregated & Selected <1 seconds Standard System In-Memory System 2013 SAP AG. All rights reserved. 18

19 SAP HANA (Data Warehouse) for capital markets External Disclosure Decision Makers and Managers VaR, Liquidity Risk, Credit Considerations, etc. Generate Once Analytics Apps Store Once Reporting and Analysis Data Warehouse Standard Sourcing Atomic Level Data and Result Sets Automated Compliance Based Business Rules Processes Integrate Data Sources Trading Portfolio Mgmt Order Mgmt Systems Systems Systems Finance Product Data Market Data 2013 SAP AG. All rights reserved. 19

20 Experience SAP HANA In the Cloud SAP HANA One and SAP HANA One Premium Two options available for realtime business Self-service, subscription-based model Build any kind of SAP HANA application or analytics, for proof-of-concept f or production Run your SAP systems in the public Cloud Pay as you go hourly or annually 2013 SAP AG. All rights reserved. 20

21 SAP HANA in the Cloud related offerings Subscription pricing, Pay-As-You-Go, Bring Your Own License SAP HANA Cloud SAP HANA One SAP HANA One Premium SAP HANA Enterprise Cloud SAP HANA in the public cloud Use cases: Departmental Instant access in less than 15 minutes Start and stop when needed Subscription Pricing $0.99/h License $2.50/hr AWS Infrastructure SAP HANA One plus: SAP Cloud Integration Licensed to SAP source data Use cases: Departmental All SAP HANA One SAP Business Suite, SAP NetWeaver Business Warehouse Instant access with SAP Enterprise Support included Annual subscription $75k Enterprise-Class Managed Cloud: Bring Your Own License Fully outsourced, no license Use Cases: All SAP HANA: Combines OLTP/OLAP Big Data, text & predictive analytics SAP HANA appliance: Hosting on certified HW for a monthly fee Single-tenant, bare-metal (nonvirtualized) servers 2013 SAP AG. All rights reserved. 21

22 Designing Tomorrow s Capital Markets University Alliance Contest

23 SAP at SIFMA Tech 2013 Panel Discussion: Markets Data Aggregation g and Analytics in Cloud 2:00 pm today in the Data Management & Cloud Infrastructure Track Featuring panelists from State Street, Bank of America, A-Team Group & SAP Learning Lab: Developing low-latency applications using SAP HANA 1:00 pm Wednesday Visit us at Booth #1417 Talk to our experts about SAP solutions in Capital Markets See a Demo Win some great prizes 2013 SAP AG. All rights reserved. 23

24 The Future of Capital Markets Reimagined i Irfan Khan, (@i_khana) SVP & CTO SAP Database & Technology, SAP AG.

25 Complete trading analytics life-cycle support Portfolio & Risk Analysis Trade Execution Intelligent trading desk Fixed Income & equity analytics Portfolio construction/what-if analysis Risk modeling & reporting P&L Analysis Executive oversight Order management Pre-trade compliance Placements STP to brokers & ECNs Risk Management, Control & Oversight Comprehensive risk and position reporting across all assets Full information transparency Centralized source of data Reduce commission cost Ease of use Increase trader productivity Precision execution Reduce latency Price improvement Execution consistency Portfolio Administration Data Control & Operations Performance & attribution Security & broker data Reconciliation management Cash forecasting Post-trade compliance Interfaces with accounting Trade confirmation notification systems Corporate actions procession 2013 SAP AG. All rights reserved. 25