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.

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. Your speakers for this webcast
Photo
Photo
Geoff Lunsford
Karthik Lalithraj
Sales Director, Americas
Terracotta
Director, Global Technical Services (East)
Terracotta

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
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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
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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
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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. 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. 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
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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.
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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
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11. CUSTOMER SUCCESS STORIES
Terracotta BigMemory in
Financial Services
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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
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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
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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
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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
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16. What could you do with instant
access to all of your data?
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17. Q&A
QUESTIONS?
Type them in the “Question” panel or in the chat window
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18. GET BIGMEMORY
1. Learn more + get your free download:
terracotta.org/bigmemory
2. Contact us: geoff@terracottatech.com,
sales@terracotta.org
3. Follow us on Twitter: @big_memory
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