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1 Mind Commerce Commerce Publishing v3122/ Publisher Sample Phone: (US) or or (Int'l) Hours: Monday - Thursday: 5:30am - 6:30pm EST Fridays: 5:30am - 5:30pm EST MarketResearch.com

2 Sample/Excerpts ONLY Not Full Report Big Data in Financial Services Market Trends, Challenges and Prospects December 2013

3 Table of Content EXECUTIVE SUMMARY 6 INTRODUCTION 7 BIG DATA MARKET TRENDS THE GLOBAL BIG DATA MARKET THE BIG DATA: AT A GLANCE THE UNSTRUCTURED DATA MARKET ADVENT OF 3RD PLATFORM TECHNOLOGY DIGITIZATION OF FINANCIAL PRODUCTS AND SERVICES DATA PROCESS MAGNITUDE TOWARDS THE ZETTABYTES MARKET DATA ANALYTICS AS THE BATTLEGROUND FOR COMPETITION 14 BIG DATA IN FINANCE: THE CHALLENGES FINANCIAL BIG DATA MANAGEMENT: REFERENCE DATA BIG DATA, CHANGING BUSINESS FINANCIAL MODELS BIG DATA IN FINANCE: ITS FUNCTIONAL LEVELS TECHNOLOGY ADVANCEMENT VIS-À-VIS EXPANDING CONSUMER EXPECTATION BEHAVIORAL AND TENDENCY DATA THRU PREDICTIVE ANALYTICS CUSTOMER FEEDBACK THRU SENTIMENT ANALYSIS MASS CUSTOMIZATION DATA REMODELING BIG DATA FOR BIG REVENUE BIG DATA FOR PREDICTIVE FINANCIAL CRIMES 24 BIG DATA IN FINANCE: AN ANALYSIS UNDERSTANDING THE RELEVANCE OF BIG DATA IN THE FINANCIAL SERVICE MARKET DIFFERENTIATING BIG DATA ANALYTICS FROM FINANCIAL ECONOMETRICS COULD FINANCIAL BIG DATA ANALYTICS PREVENT ECONOMIC RECESSION? TRANSFORMING BIG DATA ANALYTICS FOR FINANCIAL GAINS CUSTOMER-FOCUSED BIG DATA FINANCIAL INITIATIVES: BANKING SECTOR EXPERIENCE BIG DATA FOR EFFECTIVE FINANCIAL CONSOLIDATION: THE JABIL SUCCESS STORY 31 All Rights Reserved Page 2 of 12

4 1.24 BUSINESS INTELLIGENCE AVERTING FINANCIAL SERVICE PROBLEM: THE KLOUT S EXPERIENCE BIG DATA AND ANALYTICS IN FINANCIAL SERVICES: THE CASE OF BECKER UNDERWOOD BIG DATA SECURITY/PRIVACY ISSUES IN FINANCIAL SERVICES: THE GOOGLE LAWSUIT 33 BIG DATA IN FINANCE: THE COMPETITIVE MARKET LANDSCAPES BIG DATA FINANCIAL MANAGEMENT SOLUTIONS IBM HP TERADATA DELL ORACLE SAP EMC CISCO SYSTEMS MICROSOFT FUSION-IO SPLUNK NETAPP HITACHI OPERA SOLUTIONS CSC MU SIGMA BOOZ ALLEN HAMILTON AMAZON INTEL CAPGEMINI MARKLOGIC CLOUDERA ACTIAN SGI 70 All Rights Reserved Page 3 of 12

5 GOODDATA DATA GEN GOOGLE ALTERYX GUAVUS VMWARE PARACCEL TIBCO SOFTWARE INFORMATICA ATTIVIO QLIKTECH 82 BIG DATA IN FINANCE: PROSPECTS AND OPPORTUNITIES THE FUTURE OF BIG DATA IN FINANCIAL SERVICES MULTICHANNEL MARKETING IN BIG DATA EMERGING MARKETS IN BIG DATA IN FINANCE BRAZIL CHINA INDIA EUROPE NORTH AMERICA 91 CONCLUSIONS 93 List of Figures Figure 1 Big Data Market Forecast Figure 2 Big Data Paradigm 10 Figure 3 Migration Process of Platform Technology 11 Figure 4 Data Universe Zettabytes Generation Figure 5 Financial Big Data Management Paradigm 17 Figure 6 Big Data Approaches for Financial Services 20 Figure 7 Big Data Functional Levels 21 All Rights Reserved Page 4 of 12

6 Figure 8 Big Data for Predictive Financial Crimes 26 Figure 9 Big Data in Finance Market Figure 10 Big Data as Competitive Differentiator for Financial Services 36 Figure 11 Big Data Revenue Share by Vendor Solutions Figure 12 Hadoop and NoSQL Vendor Revenue Share Figure 13 Big Data in Finance Market Figure 14 Big Data Market in Brazil Figure 15 Market for Big Data in China Figure 16 Big Data Market in India Figure 17 Big Data Market in Europe Figure 18 Big Data Market in North American List of Tables Table 1 IBM Big Data Financial Management Solutions 40 Table 2 HP Big Data Financial Management Solutions 41 Table 3 Teradata Big Data Financial Management Solutions 44 Table 4 Dell Big Data Financial Management Solutions 45 Table 5 Oracle Big Data Financial Management Solutions 47 Table 6 SAP Big Data Financial Management Solutions 48 Table 7 EMC Big Data Financial Management Solutions 49 Table 8 Cisco Big Data Financial Management Solutions 50 Table 9 Microsoft Big Data Financial Management Solutions 52 Table 10 Fusion-IO Big Data Financial Management Solutions 53 Table 11 Splunk Big Data Financial Management Solutions 54 Table 12 NetApp Big Data Financial Management Solutions 55 Table 13 Hitachi Big Data Financial Management Solutions 57 Table 14 Opera Solutions Big Data Financial Management Solutions 58 Table 15 CSC Big Data Financial Management Solutions 59 Table 16 Mu Sigma Big Data Platforms 60 Table 17 MuSigma Big Data Financial Management Solutions 61 Table 18 Booz Allen Hamilton Big Data Financial Management Solutions 61 Table 19 Amazon Big Data Financial Management Solutions 63 All Rights Reserved Page 5 of 12

7 Table 20 Intel Big Data Financial Management Solutions 64 Table 21 Capgemini Big Data Financial Management Solutions 65 Table 22 MarkLogic Big Data Financial Management Solutions 66 Table 23 Cloudera Big Data Financial Management Solutions 67 Table 24 Actian Big Data Financial Management Solutions 69 Table 25 SGI Big Data Financial Management Solutions 70 Table 26 GoodData Big Data Financial Management Solutions 71 Table data Big Data Financial Management Solutions 72 Table 28 10gen Big Data Financial Management Solutions 74 Table 29 Google Big Data Financial Management Solutions 74 Table 30 Alteryx Big Data Financial Management Solutions 75 Table 31 Guavus Big Data Financial Management Solutions 76 Table 32 VMware Big Data Financial Management Solutions 77 Table 33 ParAccel Data Financial Management Solutions 78 Table 34 Tibco Software Big Data Financial Management Solutions 79 Table 35 Informatica Big Data Financial Management Solutions 81 Table 36 Attiivio Big Data Financial Management Solutions 82 Table 37 Qlick Tech Big Data Financial Management Solutions 83 All Rights Reserved Page 6 of 12

8 1.1 Big Data, Changing Business Financial Models Financial institutions are facing the challenge of catering to dynamic and different market overtime. This compels them to find adequate and efficient system to adapt to these new challenges, requiring them to transform their own business models to save shareholder confidence and sustain economies of scale. Proponents to new business models in Big Data include three approaches relevant for financial services. These include information based diversification, brokering essential information, and data monetization via delivery networks. a) Information-Based Sorting Information Based sorting takes into consideration efficient service offering thru contextual relevance of data with the end objective of satisfying customers. Google s Adsense belong to this category, including online retailers such as UPS, FedEx, which provide tracking services on package deliveries. On the other hand, Google, Microsoft, Yahoo and Apple provide map services. Big Data therefore allows customer satisfaction by availing of these services to improve efficiency based on the real time demand of consumers. For example, finding the nearest restaurants, gasoline station would conveniently save time and resources for one customer who would never mind a few dollars to avail of this contextual service just for the timely delivery of information. b) Information-Based Brokering Brokering essential data information allows providers to sell raw information, benchmark and deliver projections and analysis based on the current data needs. By adding value to information, data become marketable. Bloomberg, Dun & Bradstreet, and Experian provide and sell analyzed information based on structured data. The advent of Big Data includes brokering even the unstructured data information, such from social media, chat streams and video, and offers the most relevant information and analysis. Amazon sells raw information All Rights Reserved Page 7 of 12

9 based on the hottest purchase categories, providing retailers a competitive edge of understanding the most marketable good and services in the market. The advent of Big Data information allows brokers to align industries, geographies and user roles by considering age, location, interest and other relevant categories needed. In this manner, brokering is easier facilitated. c) Information based-delivery Information based delivery includes networks in the marketplace, drive deal making, and advertising. Brokers collect, improve and reconstitute data information to achieve consistency and relevance for the insight streams. Amazon, Apple, Bloomberg, Google and Microsoft are along this line as they offer cloud to device services. Cloud houses a considerable amount of data. AT&T, Verizon, Comcast, and BT are finding Big Data as an opportunity as well. This means offering relevant information shall be the baseline in leveraging market competition whereby network based on context, product, ownership, location, time, sentiment and intent are being considered. [ See Full Report for More Information ] All Rights Reserved Page 8 of 12

10 BIG DATA IN FINANCE: THE COMPETITIVE MARKET LANDSCAPES 2.0 Big Data as Competitive Differentiator for Financial Services The level of competition in the financial market is determined by the efficiency of companies to harness big data to its economic advantage. Financial companies which can efficiently process data are able to manage risk, and offer the best products, showing that big data is the new competitive differentiator. Mind Commerce compiles various ways of big data treatment to leverage competition in the financial market. a) Data for business value This means financial institutions are able to gain insights, requiring an analytical and visualization platform to deliver actionable data discovery across the organization. In this way, customer behavior is being taken into priority. b) Data for product value Firms could give business customers a platform to create offers and incentives. Through the analysis of demographic, social and payment data, the company sends targeted offers through mobile channels. Microsoft, for example, is into direction such as Commerce Platform for Windows Phone8, where the company provides exclusive mobile incentives to benefit banks by letting them target consumers based on buying habits and the use of the app to deliver highly relevant offer. c) Data for efficiency and increased productivity Firms provide powerful customers and product analytics to allow financial companies improve efficiency and productivity, enhance brand perception, customer acquisition, and cross-selling. Financial firms are able to provide analytics based on better analysis and understanding and what impacts cost [ See Full Report for More Information ] All Rights Reserved Page 9 of 12

11 2.1.1 Alteryx Alteryx Strategic Analytics works by managing data and decision-making environment of financial organization. Whether it is specific data types such as Big Data or Salesforce.com, or specific analytical capabilities such as location intelligence or predictive analytics, Alteryx provides solutions to facilitate effective analytics for the key decision makers. Alteryx leads the consumerization of analytics using capabilities for Big Data, Customer, Customer Churn, Hadoop, Predictive, R based Big Data, Saleforce.com, and Spatial. R for Big Data Analytics puts emphasis on the analysis of the historical performance of the business. Alteryx Strategic Analytics, with deep integration of the R statistics and predictive language provides sophisticated predictive analytics Mine Social Media Data for True Business Insight Social media channels, such as Twitter, Facebook, Yelp, Foursquare, and LinkedIn, provide a wealth of valuable information for forward-looking organizations, not only to better understand. Table 1 Alteryx Big Data Financial Management Solutions INITIATIVES See Full Report BIG DATA TRENDS See Full Report BIG DATA PROSPECTS IN FINANCE See Full Report Mind Commerce 2013 [ See Full Report for More Information ] All Rights Reserved Page 10 of 12

12 BIG DATA IN FINANCE: PROSPECTS AND OPPORTUNITIES Financial service industry faces the demands to modernize operations and to significantly improve business productivity, reduce cost and efficiently demands for diverse products and services. Big Data shall continue to have core applications in the financial services, especially in modernizing core banking applications as multilayer projects. This would mean the sustainable integration and management of data, migrating and moving, as well as archiving. 2.2 The Future of Big Data in Financial Services The future of big data in finance is anchored on the following: The proper migration of reference and transaction data from sources into a target system Increase value system by eliminating improper migration of reference and transaction data towards a target system Successful development and testing of test data results and making it risk free, and property mitigated from fraud. The competition therefore is greatly anchored on the market players to migrate system towards managing big data and moved away from merely a pure e-commerce player to the one which offer more than just products. Big Data in Finance Market is expected to reach $XX in 2018 and would continue to experience growth to $XX in [ See Full Report for More Information ] See Full Report for All Data Figure 1 Big Data in Finance Market All Rights Reserved Page 11 of 12

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