data: the lifeblood connecting transactions, reporting and ... · manage the mass . of banking...
TRANSCRIPT
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Data: the lifeblood connecting transactions, reporting and analytics
Temenos, CBA
18th May 2016
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1. The Unified Data Platform
2. Data Lifecycle Management
3. DLM use-case: Commercial Bank of Africa
4. Business Reporting Models
5. Temenos Analytics
Agenda
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The Unified Data Platform
Temenos
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The business challenge
Manage the mass of banking data
throughout its lifecycle
Transform it into accessible info & knowledge
for queries and business decisions
1
2
Extract intelligence and wisdom from it
to better understand customers and trends
3
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Problems with the traditional approach
Non-real-time
• Bloated databases
• Manual processes
• Limited access (archives)
• Slow queries
• Limited perspectives
• Poor decision support
• Batch-based flows
• One step behind
Transaction-optimized
Costly,Cumbersome
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Temenos’ Unified Data Platform
Analyticsdatabase
SQL
Core Banking
Data Lifecycle Management
Reporting tools & digital queries Analytics
Near-Real-Time
Data ($) Info & Knowledge ($$$) Wisdom ($$$$)
Business Reporting Models
Analytics Integration
Searchabledatabase
Lucene
New Browser
Core Banking Lifecycledatabase
XML
Core Banking Transactionaldatabase
XML
Business Reporting Models
database
SQL
Near-Real-Time
Search (Google-style)
Core Banking Transactional
database
-70%
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Unified Data Platform – business benefits
Scalability Efficiency Productivity CompetitivenessUsability
Preserve performance
Manage your data efficiently
Unlock & accessdata
Extract value from your data
Search data conveniently
Data Lifecycle Management
Data ($) Info & Knowledge ($$$) Wisdom ($$$$)
Business Reporting Models
Analytics Integration
Search (Google-style)
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Data LifecycleManagement
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Core Banking Transactional
database
(live + aged data)
CB Lifecycle database
(aged data)
Data Lifecycle Management – managing your data
Partition Partition Partition Partition
Archive
70% sizereduction
Seamless enquiriesacross databases
Before DLM
SQL
CB Transactional database (live data)
With DLM
Preserved performance
Commercial Bank of Africa
DLM use-case
Dennis Volemi
Head of Technology, New Business Ventures
Background
KEY
Commercial Bank of Africa – Data Management Objectives
CBA KPI’sKPI achievement Against Target
Time in hours
2h 5h 8h 12 h
PerformanceNumber of hours it takes to complete COB and post COB activities
Lead time in weeks1 week 3 weeks 6 weeks
Time to MarketTime taken to carry out QA on production like environment before actual cutover and deployment
Duration in daysProduction Fixes TATTime taken to resolve production issues requirement a copy of production environment to simulate the failure
1d 5d 10d 30d
Time in hoursRecovery Time Objective Time taken to restore service back to normal operations after an outage requiring a DB restore
1h
Current day – delay in daysBusiness IntelligenceAvailability of data in the data warehouse to support near real-time analytics for business decision making
Real-time D D-1 D-2
Commercial Bank of Africa has embarked on ambitious project to implement Temenos Data Life Cycle Management in an effort to address the following business objectives and KPI’s
3h 6h 9h 12h 15h 18h 21h 24h 27h 36h
DLM Project Target Business Requirement Current Achievement
45d
4 weeks2 weeks 5 weeks
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Business ReportingModels
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What are our Business Reporting Models?
Integration Framework
EventsData
ModelEnquiries Reports
Mappings
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Business Reporting Models – Runtime tooling
Integration Framew
ork
Core BankingTransactional
database
XML
BusinessReporting
Modelsdatabase
Fetch LoadTransform
LoadTransform
LoadTransform
LoadTransform
Dispatch
XML LSQL
ProcessNear-real-time Scalable
ModelsFine-grained Bi-temporal
DMLXML SQL
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Business Reporting Models - availability
Available now Coming soon Mid-term
• Balance Reporting • Financial• Credit/Limit
• Banking Framework• Retail• Corporate• Treasury• Risk• Payments• Wealth• Front Office• Operational Reporting
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Temenos Analytics
Todd Winship
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R15 New User Interface
BI Platform Updates
Post Closing
Multi-Company
Multi-Currency
Analytics Lifetime Value
Balance Prediction
Temenos Analytics (aka Insight) R15 / R16 Highlights
R16 OData Services
Insight Mobile
Analytics
Embedded (Retail)
Embedded (Corporate)
ETL Performance
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Launching Insight Mobile R16
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HTML 5
Multi-Tenant
Integrated Power BI
Insight User Interface Refresh
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Analytics Data Services (OData)
Codeless
Dynamic
Integrated
Expose Analytics and BI data to any OData consumer
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Embedded Analytics for Corporate & RetailCorporate Loan Dashboard Customer 360 View
Embed Analytics directly into T24 screens making users more intelligence, efficient, and enable better decision making
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CBEvent
Stream
API / Services Process Apps
Core Banking
Data Services
Mobile
Analytics R17: Real-Time Analytics Pipeline
AnalyticsReal-Time
TabularReporting Database
Power BIAPIReal-Time
Dashboards
Profit
Risk
Core Bankingsystem
ETL
Real-Time MachineLearning
AnalyticsCDC
AnalyticsReal-TimeData Mart
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Conclusion
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Our Data products…
Turn your data into info, knowledge, wisdom
Fast and easy to implement
For banks of all sizes
Make your bank scalable, productive, competitive
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Thank you