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The Future of Financial Information Services

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Financial professionals receive information through diverse dedicated user interfaces and systems built on decade old foundations. With the explosion in information, the consumer space is fast evolving to distribute and capture massive amounts of complex information quickly and in an organized way. Technology has also evolved to handle orders of magnitudes larger data sets. Consumers are effectively viewing and responding to information at home and on the go. In many ways, financial information delivery has not quite adapted to the pace, usability and uniformity that consumer information delivery has. This presentation covers new approaches to accessing and delivering financial information emphasizing practices and technologies that are best suited to disrupt this space.
Speech up at http://www.infoq.com/cn/presentations/the-future-of-financial-information-services
http://www.perpetualny.com

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The Future of Financial Information Services

  1. 1. The Future of Financial Information Services QCON Shanghai Nov 2013 Amish Gandhi www.perpetualny.com
  2. 2. Finance Telecom Media Amish Gandhi Founder and Principal at Perpetual: Product innovation and development for financial, media and telecom www.perpetualny.com Financial services background • Worked at Thomson Reuters for 3 years – Global Product Manger for Reuters Messenger – Product manager for financial video service Reuters Insider MS Computer Science from Univ of Texas, Austin BS Computer Science from Bombay University The Future of Financial Information Services
  3. 3. Outline • The rise of consumer internet – 1995 – 2007 – 2013 • How did we get here? – Resulting technologies • Difference between Consumer and Finance – Innovators Dilemma in Finance • 10 Predictions for the Future of Finance The Future of Financial Information Services
  4. 4. Rise of consumer tech Consumer Internet/Tech Landscape Pre 1995 Financial Technology Landscape Pre 1995 Motorola Pageboy Financial Service Providers Service Distribution Mainframe
  5. 5. 1995
  6. 6. 2007
  7. 7. 2007 Left to right info flow Ideo Bloomberg Concept UI similar to modern websites Electronic notepad reused like a virtual Post-it Gaming-inspired system that would track and display the expertise of users around the world. Bloomberg Wherever—allows users to take a small-scale Bloomberg terminal device beyond their desks.
  8. 8. 2013 Realtime
  9. 9. How did we get here?
  10. 10. Search Social Communication Ecommerce Gaming User Interface Internet of things
  11. 11. Before 1995 ? ? ? ? Search
  12. 12. 1995 Onwards ? ? ? ? Search
  13. 13. Search
  14. 14. Before 1995 -Snail mail -/dev/null Social
  15. 15. Comments Social
  16. 16. Social
  17. 17. Big Data Ecosystem Search/Social
  18. 18. 3G WhatsApp 4G Skype Communication BBM
  19. 19. 1990’s and pre $ $ $ $ ECommerce
  20. 20. Massively multiplayer online role-playing game (MMORPG) & Social Gaming Gaming
  21. 21. Consumer Products: Professional User Interfaces Radian 6 User Interface
  22. 22. Internet
  23. 23. Technologies Born from Consumer USER INTERFACE HTML5 CSS3 Firefox/Chrome Javascript JS frameworks Backbone Ember Angular UI:PROCESS UCD A/B testing Lean User testing INTERNET OF THINGS Sensors Event driven computing Websockets vs. http Bluetooth and other NFC Material science Electromyography-sensors Accelerometers Speech recognition Power consumption … SEARCH GAMING Advanced graphics Game theory implemented Advanced GPUs Advanced GPU programming MapReduce Google Bigtable Google BigQuery LAMP/Commodity scaling Lucene SOLR Elastic Search Ajax Twitter Storm Apache S24 … Technologies born from Consumer COMMUNICATION Smartphones Android ECOMMERCE iOS Cloud Computing (EC2) 3G/4G Online payments SMS Mobile payments MMS Online payment gateways iMessage Bitcoin Erlang … WebRTC … SOCIAL NoSQL Cassanrda Hbase/Hadoop Twitter Storm Location based services Natural Language Processing …
  24. 24. Consumer Internet/Tech Landscape Present Pre 1995 AWS Android Mapreduce Bigtable Hadoop Hbase NodeJS Scala Cloud Computing Big Data D3.js Coffee Script/Backbone Data Visualization Elastic search Nginx Hudson GO R require.js less/sass/compass, HTML5…
  25. 25. Difference between Consumer and Finance Applications
  26. 26. Consumer Experiences Open Connected Rich Financial Experiences Scalable Fast Reliable Highly competitive high volume market driven evolution Secure Compliant Established traditional business model
  27. 27. Innovators Dilemma
  28. 28. Technologies Born from Consumer USER INTERFACE HTML5 CSS3 Firefox/Chrome Javascript JS frameworks Backbone Ember Angular UI:PROCESS UCD A/B testing Lean User testing INTERNET OF THINGS Sensors Event driven computing Websockets vs. http Bluetooth and other NFC Material science Electromyography-sensors Accelerometers Speech recognition Power consumption … SEARCH GAMING Advanced graphics Game theory implemented Advanced GPUs Advanced GPU programming MapReduce Google Bigtable Google BigQuery LAMP/Commodity scaling Lucene SOLR Elastic Search Ajax Twitter Storm Apache S24 … Technologies born from Consumer COMMUNICATION Smartphones Android ECOMMERCE iOS Cloud Computing (EC2) 3G/4G Online payments SMS Mobile payments MMS Online payment gateways iMessage Bitcoin Erlang … WebRTC … SOCIAL NoSQL Cassanrda Hbase/Hadoop Twitter Storm Location based services Natural Language Processing …
  29. 29. Innovators Dilemma AWS Android Mapreduce Bigtable Hadoop Hbase NodeJS Scala Cloud Computing Big Data D3.js Coffee Script/Backbone Data Visualization Elastic search Nginx Hudson GO R require.js less/sass/compass, HTML5…
  30. 30. The Future of Financial Information Services 10 Predictions
  31. 31. Prediction 1 There will be a revolution in financial information visualization
  32. 32. Visualization -Financial Data is complex & large scale -Visualization of financial mostly same last 15 years -Current visualization relies on a variety of charts -Consumer BigData visualization has evolved rapidly Products at the forefront Current Custom HTML5 Support/ Javascript API Prediction 1
  33. 33. Prediction 1
  34. 34. Technologies in play Emerging Technology: Present -Canvas -Raphael -Protovis Prediction 1 Future Technology >3 years: Gaming Engines
  35. 35. Prediction 2 Cloud services will be used much more for computation
  36. 36. GPUs in Finance • • • • • Significant advancement in GPUs for gaming physics engines High speed computation Can have 512 cores (<10 in avg. CPU) Can have 10x bandwidth 100 X fast calculation of typical derivative model Pros: Ideal for well defined structured computation Cons: Not very flexible, steep learning curve Prediction 2
  37. 37. GPU Opportunities in Finance • • • • • • Derivatives Pricing Speeding up risk analysis (can take days/weeks) Trading strategy prospecting (back testing) HFT (complex event processing) Tick data (added value data feeds in real time) Data visualization High Performance Computing (HPC) to leverage GPU arrays available on Amazon Prediction 2
  38. 38. Prediction 3 Realtime solutions will be adapted from consumer world
  39. 39. Realtime in Consumer World Advertising • Ad serving user real-time • Capture and process model Analytics • Usage in realtime • Content usage tracking to adapt strategies • Usage tracking to manage load Prediction 3 Social media data processing • Multiple streaming sources • Capture and process model • Real-time ad response • Real-time engagement Messaging and Communication • 2 way real-time comms – Mobile – Desktop vs - Text -Images -Video
  40. 40. Realtime in finance Use-cases – Exchange streaming pricing – Reference data access and display – Liquidity analysis & risk – News – Communication – Alerts – Active compliance …social media Technical solutions today: -MQ Series/Tibco -FPGA processors -Custom C++ solutions -Traditional RDBMS -Rules engines -Processing -Storage …stream processing
  41. 41. Realtime Data Processing Model Price servers Market movement News Rates changes Capture Stream Processing Result storage Distribution Ref: Real Time Data Processing - Technical Terrain by Prakash Khemani Prediction 3
  42. 42. Realtime Data Processing Model Exchange price servers ticker plants Aggregates and indices News feeds Rates and other adjunct prices Realtime modeling Sensors -Write-ahead-logging -At-least-once delivery guarantees Best-effort delivery guarantee Millwheel -Large scale fault tolerant stream processing -Used for Google Zeitgeist Persistent queue -Price queue -Index queue -News queue Capture Prediction 3 In-memory database JMS -Transactional guarantees -Strict ordering guarantees -Limited throughput Stream Result Distribution Processing storage
  43. 43. Twitter Storm: at-least once processing guarantee for every record Exchange price servers ticker plants YARN Hadoop NextGen MapReduce Local state Aggregates and indices Zookeper News feeds Streaming Rates and other adjunct prices Realtime modeling Trident: Exactly-once processing mode of storm. Allows you to seamlessly mix -high throughput + stateful stream processing -low latency distributed querying Compute node/cluster Management Persistent Queue -Pull data from persistent Q Input -Scheduling computation -Maintaining checkpoints Sensors Capture Prediction 3 -Does not persist output at every stage -Keeps track of each record's lineage -Can replay the data to recreate the records when needed -Fast -Cons: Unordered batch completions, low guarantees Pregel (Built on Bigtable) All in the same system: -Event Capture Storage -Computation State -Result Storage Stream Processing Result storage Distribution
  44. 44. Realtime Data Processing Model Exchange price servers ticker plants Distributed, scalable Time Series Database (TSDB) written on top of HBase -Store batches into storage -Do the aggregations at read time Aggregates and indices News feeds Rates and other adjunct prices Specializes in exporting key/value data from Hadoop Persistent Queue Input -Buffer up the updates to many keys -Do a sequential merge with historical data Realtime modeling Sensors Capture Prediction 3 Stream Processing Result Storage Distribution
  45. 45. Exchange price servers ticker plants Aggregates and indices News feeds Rates and other adjunct prices Persistent Queue Input Realtime modeling Capture Sensors Prediction 3 Stream Processing Result Storage Distribution
  46. 46. Prediction 4 Wave of improved general UX
  47. 47. Mozilla labs design contest: Flickr @peterheads
  48. 48. Prediction 4
  49. 49. Prediction 4
  50. 50. Prediction 4
  51. 51. Prediction 4
  52. 52. Prediction 4
  53. 53. Prediction 4
  54. 54. Prediction 4
  55. 55. Prediction 4
  56. 56. 1 2 1 4 1 Prediction 4 3 5
  57. 57. Prediction 5 There will be a major change in the tiered architecture with HTML5
  58. 58. HTML 5 Offline Database Cross Browser Multimedia Mobile Offline App support Geo-location Improved forms support Prediction 5
  59. 59. Current Pricing Engine Windows/ HTML Front End Middle Layer (App server with business and transformation logic) News Service Research Historical Data Events Other… Prediction 5
  60. 60. Future SOA (Service Oriented Architecture) Pricing Engine News Service HTML 5 UI Research Historical Data Events A B External 3rd party services Prediction 5 Other…
  61. 61. Technologies in-play • Websockets Products – Realtime bi-directional – Event programming : no http overhead – Javascript coming to the forefront on top of web sockets • Server support for Websockets Prediction 5
  62. 62. Prediction 6 In-desktop communication will be enhanced with Web RTC and similar technology
  63. 63. Communication over financial products • Skype/Softphones exploded on the web • PSTN/VoIP/Cellular phones still used in finance environments • Communication endpoints will emerge on desktops & mobile finance apps – Enabling realtime comm. including video conferencing Prediction 6
  64. 64. Communication over financial products Technologies • Jabber / XMPP – Open syndication of messaging across networks • Web RTC will play a big role • Enhanced on-desktop communication and FIX integration • Rise of Erlang for messaging eg eJabberd Prediction 6
  65. 65. The rise of Erlang • • • • • • Large scale concurrency Soft real-time Distributed Hardware interaction Software maintenance on-the-fly Fault tolerance …. and many more Prediction 6
  66. 66. Prediction 7 Analyst research will take on a much richer format beyond PDF and will be published to permissioned microsites *Same for other frequently shared information eg earnings calls
  67. 67. Analyst Research • Current analyst research reports – Static PDF Distribution through financial research aggregators Advanced entitlement model restricting access. Physical file sent through several intermediaries Prediction 7
  68. 68. Relevant Technologies • • • • HTML5 CSS3 Web app stack: PHP/Python/Ruby JS frameworks – Backbone – Ember – Angular ...... Prediction 7
  69. 69. Prediction 8 Financial training will be revolutionized to incorporate gaming and other aspects seen on consumer web
  70. 70. Financial Training There is a vast amount of financial related training Series 7 Series 86/87 certifications CFA prep Compliance related training • Education based apps and readers are much more widely available on mobile • Financial training will see a rapid adoption of mobile and gaming based innovations Prediction 8
  71. 71. Technologies • Game theory • iOS/Android/Windows Phone • ePub adoption Prediction 8
  72. 72. Prediction 9 Android based OS will become a dominant force, starting with consumer banking
  73. 73. Android Usage More than 1 million new Android devices are activated worldwide. Daily. Prediction 9 1.5 billion downloads a month and growing. The next 1 billion internet activations in remote areas will be on an Android device.
  74. 74. Technology • Android • vs. Chrome OS Prediction 9
  75. 75. Prediction 10 Direct sensor tracking for assets like Commodities & Energy
  76. 76. Changes • From vessel to batch level sensors – Deeper insight into supply chain • Connected sensors tracing – Volume – Quality – Speed – Location • Combined with following real-time data – Weather – Transportation – Government events Access to high volume, low latency data for new level of accuracy Prediction 10
  77. 77. Predictions Summary 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. Revolution in financial information visualization Much more GPU and GPU cloud computing Realtime solutions will be adapted from consumer world Wave of improved general UX on financial terminals Major change in the tiered architecture with HTML5 Communication will be enhanced with Web RTC & similar Analyst research go from static PDFs to dynamic microsites Financial training will incorporate social and gaming aspects Android based OS will dominate for financial info services Direct sensor tracking for assets like commodities & energy www.perpetualny.com

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