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 SPEAKERS The BigMemory Revolution in Financial Services Geoff Lunsford Sales Director, Americas Terracotta Karthik Lalithraj Director, Global Technical Services (East) Terracotta TERRACOTTA WEBCAST SERIES
  2. 2. Your speakers for this webcast Photo Photo Geoff Lunsford Karthik Lalithraj Sales Director, Americas Terracotta Director, Global Technical Services (East) Terracotta
  3. 3. Financial services companies have a variety of Big 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 and milliseconds to RAM and microseconds 90% of Data in Database Memory 90% of Data in Memory MODERNIZE App Response Time Milliseconds Database Using an in-memory store with DB-like capabilities:  High Availability  Persistence  Data Consistency / Coherency  Transactions  Query  … App Response Time Microseconds 4
  5. 5. Plummeting RAM prices and exploding volumes of valuable data make real-time Big Data possible In-Memory Maximize inexpensive memory Steep drop in price of RAM Big Data Unlock the value in your data Explosion in volume of business data 5
  6. 6. Terracotta BigMemory powers real-time Big Data applications across many industries  Fraud detection slashed from 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 Terracotta customers
  7. 7. That’s because in-memory computing solves big challenges facing CIOs Scale and performance in the cloud Real-time Big Data Mainframe modernization in-memory data store Decoupling from databases for agility
  8. 8. Financial services firms have been especially quick 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 available in your servers, without expensive tuning Without BigMemory With BigMemory Applications can store only a few GB of data in RAM before garbage collection degrades performance. Applications can use ALL available RAM while achieving extremely low, predictable latency at any 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) Scale up Simple, Fast to Deploy Use Java’s defacto Ehcache API 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 STORIES Terracotta BigMemory in Financial Services 11
  12. 12. Fortune 500 online payments processor Boosting 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 – – Company failed to meet 800 millisecond SLA for fraud detection –  Adding one new rule to fraud detection algorithm would save $12 million annually, but performance at scale only allowed 50 rules 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 bank Meeting 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 – – 240GB of trades, asset prices, etc. kept in slow, disk-bound databases –  Unable to process trade reconciliations within 4-hour window 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 bank Delivering 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 – – Difficult to pull data from many sources for pricing, allocation and asset recall –  Disk-bound database bottlenecks made scaling impossible 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 Fortune 500 online payments processor Request (e.g., "Is this transaction fraudulent?" Real-time response "Yes" or "No," informed by latest intelligence REAL-TIME INTELLIGENCE REAL-TIME INTELLIGENCE BigMemory Working together, BigMemo ry and Hadoop are creating a virtuous cycle for real-time intelligence around fraud detection. Hadoop feeds Hadoop feeds Long-term, BigMemory with BigMemory with iterative about intelligence data intelligence about analysis fraud patterns fraud patterns BigMemory feeds BigMemory feeds Hadoopwith latest Hadoop with Real-time latest transactions to transactions to in-memory data improve intelligence improve intelligence DEEP (SLOW) INTELLIGENCE DEEP (SLOW) INTELLIGENCE 15
  16. 16. What could you do with instant access to all of your data? 16
  17. 17. Q&A QUESTIONS? Type them in the “Question” panel or in the chat window 17
  18. 18. GET BIGMEMORY 1. Learn more + get your free download: 2. Contact us:, 3. Follow us on Twitter: @big_memory 18