Customer expectations are changing fast, while customer-related data is pouring in at an unprecedented rate and volume. Join this webinar, to hear leading experts from DataStax, discuss how DataStax Enterprise, the data management platform trusted by 9 out of the top 15 global banks, enables innovation and industry transformation. They’ll cover how the right data management platform can help break down data silos and modernize old systems of record as an operational data layer that scales to meet the distributed, real-time, always available demands of the enterprise. Register now to learn how the right data management platform allows you to power innovative banking applications, gain instant insight into comprehensive customer interactions, and beat fraud before it happens. Video: https://youtu.be/319NnKEKJzI Explore all DataStax webinars: https://www.datastax.com/resources/webinars

1. An Operational Data Layer is Critical for
Transformative Banking Applications
Richard Henderson
Solution Engineer
DataStax

2. Todays Agenda
• Introduction
• Who DataStax are
• Why transformation is needed
• Customer success stories
• The key requirements
• The common features that meet those requirements
• Where the solution lives in your architecture
• How it should be implemented
• Why it also works internally
• Live Q & A

3. Some of our customers

4. In a rapidly evolving world…
accelerates expectations
© 2017 DataStax, All Rights Reserved. Company Confidential

5. You must respond
User
Expectations
And Behaviours
Regulatory change
Non-traditional Players
(Fintechs,
Challenger Banks)

6. The Opportunity is now!
Requirements:
• Present the data we already have to
customer applications.
• Combine deep analytics with session
data (“fast analytics”) to provide
intelligent predictions to applications.
• Present the data we already have to
internal applications.
• Safely and efficiently expose the
data we already have to 3rd parties.
• Have unified data for a customer
across products.

7. Macquarie
THE CHALLENGE: Drive digital transformation initiatives to
enhance customer experience.
7
• Transformed from no retail presence to a digital consumer banking leader in less than 2 years.
• Macquarie used DSE as the core of a operational data-layer to enhance rather than replace.
• Consolidated data from many existing disparate systems delivers 360o, real-time customer visibility.
• Their world-class consumer banking app utilizes real-time analytics and full text search

8. ING Focuses on Customer
Experience and Micro-Services
• Focusing on customer experience ING has moved to a
touch-point architecture based increasingly on micro-
services
• Need for availability, consistency, and scalability
• Lots of small use cases, DevOps teams, no ephemeral
storage
• 12 clusters (4/5 environments)
• Cassandra eases availability challenges by being
active-active and having an always-on architecture.
THE CHALLENGE: Availability.
© DataStax, All Rights Reserved.

9. Banking Transformation with an
Operational Data Layer

10. Requirement Zero:
Be Demonstrably Secure

11. DSE advanced security features
© DataStax, All Rights Reserved.
● At-rest Transparent Data Encryption
○ Local Key
○ External Key Manager via KMIP
○ Configuration Value Encryption
○ System Info Encryption
● Authentication
○ Internal or Password Authentication
○ Kerberos Authentication
○ LDAP Authentication
○ Unified Authenticator
○ Proxy Authentication
● Authorization
○ Role Based Access Control
○ Internal Role Management
○ External Role Management
○ Row Level Access Control
● In-flight Encryption
○ Inter-node SSL
○ client-to-node SSL
● Auditing
● OpsCenter Security

12. CONTEXTUAL
Transformative banking applications
have these qualities
ALWAYS-ON DISTRIBUTED SCALABLEREAL-TIME
© 2017 DataStax, All Rights Reserved. Company Confidential

13. Where the operational data layer lives
© DataStax, All Rights Reserved.
New
Application
Bank App
3rd Party
Web
Applications
Open API
24/7/365 Expectations
Scalable Low Latency
Embedded Search
Secure Data Exposure
??

14. Don’t just add an API gateway and a search engine
© DataStax, All Rights Reserved.
High Cost Scale Up Front
Batch/Mostly Available
Separate
Search
More Complexity
Directly Exposed Data
Application
Integration
Service
New
Application
Bank App
3rd Party
Web
Applications
Open API
24/7/365 Expectations
Scalable Low Latency
Embedded Search
Secure Data Exposure

15. Add a simple integrated operational data layer
© DataStax, All Rights Reserved.
Operational
Data Layer
Scale On Demand
100% Always On Integrated Search
Embedded
Search
Isolated Datasets
24/7/365 Expectations
Scalable Low Latency
Embedded Search
Secure Data Exposure
New
Application
Dataset per
Customer
Bank App
3rd Party
Web
Applications
Open APICustomer

16. Bank App
3rd Party
Customer
New
Application
Web
Applications
Open API
Reuse it inside the business
© DataStax, All Rights Reserved.
Scale On Demand
100% Always On Integrated Search
Isolated Datasets
24/7/365 Expectations
Scalable Low Latency
Embedded Search
Secure Data Exposure
Operational
Data Layer
Embedded
Search
New
Application
Dataset per
Service
Employee
App
Peer Org
[Micro-]
Services
Internal APIEmployee

17. The full-scale architecture with analytics
24/7/365 expectations
Mega writes / s
Contextual/Personal
Real-time/Responsive
Batch
Analytics
Operational
Data Layer
Fast-path
Analytics
Multi-model
Scalable write
100% Always On Combine Session and History
Online Stream Analytics
New
Application
[Micro-]
Services
Event API Embedded
Search
New
Application
Web
Applications
© DataStax, All Rights Reserved.

18. Unify your data
© DataStax, All Rights Reserved.
Mortgage Bank Account
House
Insurance
Life Cover

19. DataStax Enterprise
© DataStax, All Rights Reserved.
Linear Scalability
Geographically Distributed
Continuously Available
Instantaneously Responsive
Integrated Search
Integrated Operational Analytics
Always On,
Multi-model,
Mixed Workload,
Scalable Data Layer