Data: the lifeblood connecting transactions, reporting and analytics

Transcription

1 Data: the lifeblood connecting transactions, reporting and analytics Temenos, CBA 18 th May 2016

2 Agenda 1. The Unified Data Platform 2. Data Lifecycle Management 3. DLM use-case: Commercial Bank of Africa 4. Business Reporting Models 5. Temenos Analytics

3 The Unified Data Platform Temenos

4 The business challenge 1 Manage the mass of banking data throughout its lifecycle 2 Transform it into accessible info & knowledge for queries and business decisions 3 Extract intelligence and wisdom from it to better understand customers and trends

5 Problems with the traditional approach Costly, Cumbersome Nonreal-time Transactionoptimized Bloated databases Slow queries Manual processes Limited perspectives Limited access (archives) Poor decision support Batch-based flows One step behind

6 Temenos Unified Data Platform Data Lifecycle Management Search (Google-style) Business Reporting Models Analytics Integration Data ($) Info & Knowledge ($$$) Wisdom ($$$$) Core Banking New Browser Reporting tools & digital queries Analytics XML -70% XML Core Banking Lifecycle database Core Core Banking Transactional Transactional database database Near-Real-Time Lucene Searchable database SQL Business Reporting Models database Near- Real- Time SQL Analytics database

7 Unified Data Platform business benefits Data Lifecycle Management Search (Google-style) Business Reporting Models Analytics Integration Data ($) Info & Knowledge ($$$) Wisdom ($$$$) Preserve performance Manage your data efficiently Search data conveniently Unlock & access data Extract value from your data Scalability Efficiency Usability Productivity Competitiveness

8 Data Lifecycle Management

9 Data Lifecycle Management managing your data Before DLM With DLM Core Banking Transactional database 70% size reduction CB Transactional database (live data) Preserved performance (live + aged data) SQL CB Lifecycle database (aged data) Partition Partition Partition Partition Seamless enquiries across databases Archive

10 Commercial Bank of Africa DLM use-case Dennis Volemi Head of Technology, New Business Ventures

11 Background

12 Commercial Bank of Africa Data Management Objectives 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 CBA KPI s Performance Number of hours it takes to complete COB and post COB activities Recovery Time Objective Time taken to restore service back to normal operations after an outage requiring a DB restore 1h KPI achievement Against Target 2h 5h 8h 12 h Time in hours 3h 6h 9h 12h 15h 18h 21h 24h 27h 36h Time in hours Production Fixes TAT Time taken to resolve production issues requirement a copy of production environment to simulate the failure Time to Market Time taken to carry out QA on production like environment before actual cutover and deployment Business Intelligence Availability of data in the data warehouse to support near realtime analytics for business decision making 1d 5d 10d 30d 45d 1 week 2 weeks 3 weeks 4 weeks 5 weeks 6 weeks KEY Duration in days Lead time in weeks Real-time D D-1 D-2 Current day delay in days DLM Project Target Business Requirement Current Achievement

13 Business Reporting Models

14 What are our Business Reporting Models? Mappings Integration Framework Events Data Model Enquiries Reports

15 Business Reporting Models Runtime tooling Near-real-time Process Scalable Models Fine-grained Bi-temporal Core Banking Transactional database Integration Framework XML Fetch Dispatch Transform Transform Transform Transform Load Load Load Load Business Reporting Models database XML XML LSQL DML SQL

16 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

17 Temenos Analytics Todd Winship

18 Temenos Analytics (aka Insight) R15 / R16 Highlights R15 New User Interface BI Platform Updates Post Closing Multi-Company Multi-Currency Analytics Lifetime Value Balance Prediction R16 OData Services Insight Mobile Analytics Embedded (Retail) Embedded (Corporate) ETL Performance

19 Launching Insight Mobile R16

20 Insight User Interface Refresh HTML 5 Multi-Tenant Integrated Power BI

21 Analytics Data Services (OData) Codeless Dynamic Integrated Expose Analytics and BI data to any OData consumer

22 Embedded Analytics for Corporate & Retail Corporate Loan Dashboard Customer 360 View Embed Analytics directly into T24 screens making users more intelligence, efficient, and enable better decision making

23 Analytics R17: Real-Time Analytics Pipeline Core Banking system CB Event Stream ETL Reporting Database Analytics CDC Analytics Real-Time Data Mart API Analytics Real-Time Tabular Power BI Profit Real-Time Dashboards API / Services Data Services Process Apps Core Banking Mobile Risk Real-Time Machine Learning

24 Conclusion

25 Our Data products Turn your data into info, knowledge, wisdom Make your bank scalable, productive, competitive Fast and easy to implement For banks of all sizes

26 Don t forget! Join the conversation Tweet or Facebook post the #tcf2016 Download this presentation now you can download this presentation and other TCF materials from the TCF2016 app Have your say take part in the 9th annual TCF survey, also available on the TCF2016 app

27 Thank you