Big Data for Banking. Kaleem Chaudhry Senior Director, Sales Consulting, ASEAN. Copyright 2013, Oracle and/or its affiliates. All rights reserved.

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1 Big Data for Banking Kaleem Chaudhry Senior Director, Sales Consulting, ASEAN

2 Big Data in Financial Services Key Business Goals: Looking beyond the credit bureau report to assess consumer credit worthiness New sources for acquiring and targeting the right customers Improved Risk and Compliance controls Prevent payment fraud / mortgage fraud / ecommerce fraud Improve product/portfolio pricing and trading strategies Key Tools: Multi-Channel Customer Interactions, market data Location based information, news, financial reports Apply new metrics to pricing models, upsell, underwriting, trading strategies and fraud models

3 Big Data is a Big Deal Before Big Data After Big Data Decisions based upon transactional data Decisions based upon all data Video and images Documents Social data Machine-generated data

4 Banking Priorities 58% 43% 37% 36% 30%

5 Risk & Regulation Customer Experience Market Pressures

6 Managing life cycles, not transactions Aligning the brand promise with the brand execution Differentiate Orchestrated Experience > Profitability, Brand Equity, Enterprise Agility BUY CONSUME OWN

7 CROSS CHANNEL ENGAGEMENT IS THE NEW NORMAL Research Select Buy Receive Use Recommend Comparison Site Order Online Chat Change Order Complete Order Online Call for Info about Packaged Services Visit Branch Visit Branch Browse Web Site Web Search Kiosk Product Info Select Product Order Confirm w/rec Ask Facebook Friends Read Reviews Tweet About Purchase Experience Ask for Help on Community Chat Room

8 Customer Experience Risk & Regulation Customer Experience Market Pressures 19 % 25 % 35 % Electronic payments Online retail transactions Branch Access

9 Fragmented Data Multiple Systems Siloed Cross-Channel Experience

10 Control Back Costs Comply with Regulations Grow Revenues Exceptional Customer Experience

11 and Serve Customers with a Competitive Advantage & Operational efficiency Customer Insight Data Monetization Customer Insight Big Data Profile Enrichment Social Network Analytics Real Time Offers Location Based Offers and Advertisements Social Media Sentiment Analysis

12 Big Data Management System The Best of Both Worlds Unified Data Platform Data Reservoir + Data Warehouse

13 Oracle Big Data Analytics Platform Decide Oracle Real-Time Decisions Endeca Information Discovery Oracle BI Foundation Suite Oracle Event Processing Apache Flume Oracle GoldenGate Cloudera Hadoop Oracle NoSQL Database Oracle R Distribution Oracle Big Data Connectors Oracle Data Integrator Oracle Database Oracle Advanced Analytics Oracle Spatial & Graph Oracle Communications Data Model Stream Acquire Organize Analyze

14 Caixa Bank Creating a Data Reservoir to Serve Multiple Needs Objectives Maximize cross-channel opportunities Respond Quickly to New Stress Tests Increase Data Agility Data Reservoir Solution Economically capture all data Move to Data First Approach Consolidate Data Marts Federate Data Execute Analytics in the Data Pool Utilize Any Data The implementation of this Big Data solution will help Caixa Bank remain at the forefront of innovation in the financial sector, delivering the best and most competitive services to our customers Juan Maria Nin Chief Executive Officer, LaCaixa

15 JPMorgan Chase Creating a Data Reservoir to Serve Multiple Needs Objectives Comply with regulations requiring more data to support stress testing Reduce IT costs & streamline processing by eliminating duplicate data stores Results & Benefits Fast access to 85% more data Lower costs, simplified architecture and fast time to value Solution Single, reliable BDA/Exadata-based ODS supporting all downstream systems Landing zone & archival repository for both structured & unstructured data Use Exadata as 19 th BDA node

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