The BigMemory Revolution in Financial Services


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Dozens of financial institutions — including 30% of Fortune 500 banks and credit card companies — already use Terracotta BigMemory Max to speed fraud detection, meet previously unthinkable service level agreements (SLAs), and revolutionize performance around risk analysis, portfolio tracking, and compliance. In this webcast, you'll learn how BigMemory Max can keep ALL of your data in machine memory for instant, anytime access.

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The BigMemory Revolution in Financial Services

  1. 1. FEATURED SPEAKERSThe BigMemory Geoff Lunsford Sales Director, Americas Terracotta Revolution in Karthik Lalithraj Financial Director, Global Technical Services (East) Terracotta Services TERRACOTTA WEBCAST SERIES
  2. 2. Your speakers for this webcast Photo Photo Geoff Lunsford Karthik Lalithraj Sales Director, Americas Director, Global Technical Services (East) Terracotta Terracotta
  3. 3. Financial services companies have a variety ofBig Data challenges Big Data is not just analytics! You have a Big Data problem if you want to speed up your applications in any of these areas: – Trade and transaction processing – Risk mitigation & fraud detection – Customer service & support – Portfolio valuation – Compliance-mandated reporting But fast access to large volumes of data means better decisions and increased profitability 3
  4. 4. The in-memory revolution: From disks andmilliseconds to RAM and microseconds 90% of Data in 90% of Data in Database Memory Memory MODERNIZE Database Using an in-memory store with App Response Time DB-like capabilities:  High Availability Milliseconds  Persistence  Data Consistency / Coherency  Transactions  Query  … App Response Time Microseconds 4
  5. 5. Plummeting RAM prices and exploding volumes ofvaluable data make real-time Big Data possible In-Memory Big Data Maximize inexpensive memory Unlock the value in your data Explosion in Steep drop in volume of price of RAM business data 5
  6. 6. Terracotta BigMemory powers real-time Big Data applications across many industries Fraud detection slashed from Terracotta customers 45 minutes to mere seconds Media streaming in real time to millions of devices Customer service transaction throughput increased by 100x Flight reservations load on mainframes reduced 80% Highway traffic updates delivered to millions of global customers in real time
  7. 7. That’s because in-memory computing solvesbig challenges facing CIOs Scale and Decoupling from Real-time Mainframeperformance databases Big Data modernizationin the cloud for agility in-memory data store
  8. 8. Financial services firms have been especiallyquick to adopt Terracotta BigMemory  30% of Fortune 500 banks use BigMemory  World’s largest credit card and online transactions processors use BigMemory  Most popular financial services use cases: – Real-time fraud detection at Big Data scale – Real-time portfolio valuation at Big Data scale – Real-time transaction/payment processing at Big Data scale 8
  9. 9. BigMemory lets you use all the RAM availablein your servers, without expensive tuningWithout WithBigMemory BigMemoryApplications can Applications canstore only a few use ALLGB of data in available RAMRAM before while achievinggarbage extremelycollection low, predictabledegrades latency at anyperformance. scale. 9
  10. 10. BigMemory Max is the hub of a new in-memory architecture for financial services In-memory Speed Get low, predictable latency (microseconds at TB scale) Simple, Fast to Deploy Use Java’s defacto Ehcache APIScale up Massive Scale Keep as much data in memory as your data center can hold Scale out Data Consistency Guarantees Ensure data stays in synch across the array Fault-tolerance + Fast Restart Get 99.999% availability thanks to mirrors and persistent backup 10
  11. 11. CUSTOMER SUCCESS STORIESTerracotta BigMemory inFinancial Services 11
  12. 12. Fortune 500 online payments processorBoosting profits through real-time fraud detection What the company was after – Tens of millions of dollars in additional profit by improving fraud detection speed and accuracy (30 cents of every $100 lost to fraud) Before BigMemory – Adding one new rule to fraud detection algorithm would save $12 million annually, but performance at scale only allowed 50 rules – Company failed to meet 800 millisecond SLA for fraud detection – Impossible to meet SLA with existing architecture After BigMemory – Reduced fraud processing time to less than 500ms – Thousands of rules added to fraud detection algorithm – 99.999% completed transactions 12
  13. 13. Fortune 100 commercial bankMeeting SLAs for end-of-day trade reconciliation What they were after – CIO had to meet 4-hour SLA for end-of-day reconciliations Before BigMemory – Unable to process trade reconciliations within 4-hour window – 240GB of trades, asset prices, etc. kept in slow, disk-bound databases – End-of-day reconciliation was infamous as the firm’s most unstable and underperforming application After BigMemory – Consistently meeting 4-hour SLA by improving speed by 3x – Terracotta BigMemory processing 500GBs of trade reconciliations – Application went from the firm’s most unstable and underperforming to its most stable and best performing in 3 months 13
  14. 14. Fortune 20 commercial bankDelivering collateral automation to 1000s of global clients What they were after – With demand rising for collateral automation (real-time re-pricing, re-allocation), the business wanted to build a new “virtual global longbox” for real-time views of collateral positions anywhere in the world Before BigMemory – Disk-bound database bottlenecks made scaling impossible – Difficult to pull data from many sources for pricing, allocation and asset recall – Not possible to scale as needed with existing infrastructure After BigMemory – Terracotta Big Memory solution provides real-time access to assets, securities, collateral across multiple accounts. – BigMemory keeps 200GB of prices and portfolio data in memory for ultra-fast re-pricing and allocations – BigMemory and Quartz allowed the firm to increase volume of collateralized loans and more effectively complete with competition 14
  15. 15. BigMemory + Hadoop: Real-time Intelligence Request Real-time response (e.g., "Is this "Yes" or "No," transaction informed by latestFortune 500 fraudulent?" intelligenceonline payments REAL-TIME INTELLIGENCE REAL-TIME INTELLIGENCEprocessor BigMemoryWorkingtogether, BigMemory and Hadoop are Hadoop feeds Hadoop feeds BigMemory feeds BigMemory feedscreating a virtuous Long-term, BigMemory with BigMemory with Real-time latest Hadoop with Hadoopwith latestcycle for real-time intelligence data iterative about intelligence about transactions to transactions to in-memory dataintelligence around analysis fraud patterns fraud patterns improve intelligence improve intelligencefraud detection. DEEP (SLOW) INTELLIGENCE DEEP (SLOW) INTELLIGENCE 15
  16. 16. What could you do with instantaccess to all of your data? 16
  17. 17. Q&AQUESTIONS?Type them in the “Question” panel or in the chat window 17
  18. 18. GET BIGMEMORY1. Learn more + get your free download: Contact us:, sales@terracotta.or g3. Follow us on Twitter: @big_memory 18