Welcome!

News Feed Item

Big Data in Financial Services Industry: Market Trends, Challenges, and Prospects 2013 - 2018

NEW YORK, Jan. 6, 2014 /PRNewswire/ -- Reportlinker.com announces that a new market research report is available in its catalogue:

Big Data in Financial Services Industry: Market Trends, Challenges, and Prospects 2013 - 2018

http://www.reportlinker.com/p01937235/Big-Data-in-Financial-Services-Industry-Market-Trends-Challenges-and-Prospects-2013---2018.html#utm_source=prnewswire&utm_medium=pr&utm_campaign=Financial_Services

Overview:

Big Data is making a big impact already in certain industries such as the healthcare, industrial, and retail sectors. With the exception of the government sector, no other industry has more to gain from leveraging Big Data than the financial services sector. Big Data technology will help financial institutions maximize the value of data and gain competitive advantage, minimize costs, convert challenges to opportunities, and minimize risk in real-time.

Big Data technologies provide financial services firms with the capability to capture and analyze data, build predictive models, back-test and simulate scenarios. Through iteration, firms will determine the most important variables and also key predictive models.

There is a huge opportunity for financial services firms to apply new data sets and new algorithms to optimize capital allocation, cash management, and currency processing. The financial implications are manifest in improved capital flows and profitability for many firms within the ecosystem.

This report evaluates Big Data prospects and opportunities within the financial services sector and answers the following key questions:

How is Big Data expected to impact the financial services industry?
What are the Big Data players financial management solutions and their impact?
What are the Big Data financial management models and how are they applied?
What are the near-term and long-term benefits to the financial services industry?
What are the specific challenges that the financial services industry faces with Big Data?
The report also analyzes Big Data prospects for financial services within the emerging markets including Brazil, China, and India.

Target Audience:

Big Data companies
Telecom service providers
Financial services companies
Data services and analytics companies
Cloud and telecom infrastructure providers

Companies in Report:

1010DATA
10GEN 65
ACTIAN
ALTERYX
AMAZON
ATTIVIO
BMC
BOOZ ALLEN HAMILTON
CAPGEMINI
CISCO SYSTEMS
CLOUDERA
CSC
DELL
EMC
FUSION-IO
GOODDATA
GOOGLE
GUAVUS
HITACHI
HP
IBM
INFORMATICA
INTEL
MARKLOGIC
MICROSOFT
MU SIGMA
NETAPP
OPERA SOLUTIONS
ORACLE
PARACCEL
QLIKTECH
SAP
SGI
SPLUNK
TERADATA
TIBCO SOFTWARE
VMWARE
EXECUTIVE SUMMARY 6
INTRODUCTION 7
BIG DATA MARKET TRENDS 9
1.1 THE GLOBAL BIG DATA MARKET 9
1.2 THE BIG DATA: AT A GLANCE 10
1.3 THE UNSTRUCTURED DATA MARKET 10
1.4 ADVENT OF 3RD PLATFORM TECHNOLOGY 11
1.5 DIGITIZATION OF FINANCIAL PRODUCTS AND SERVICES 12
1.6 DATA PROCESS MAGNITUDE 13
1.7 TOWARDS THE ZETTABYTES MARKET 13
1.8 DATA ANALYTICS AS THE BATTLEGROUND FOR COMPETITION 14
BIG DATA IN FINANCE: THE CHALLENGES 16
1.9 FINANCIAL BIG DATA MANAGEMENT: REFERENCE DATA 16
1.10 BIG DATA, CHANGING BUSINESS FINANCIAL MODELS 18
1.11 BIG DATA IN FINANCE: ITS FUNCTIONAL LEVELS 20
1.12 TECHNOLOGY ADVANCEMENT VIS-À-VIS EXPANDING CONSUMER EXPECTATION 22
1.13 BEHAVIORAL AND TENDENCY DATA THRU PREDICTIVE ANALYTICS 22
1.14 CUSTOMER FEEDBACK THRU SENTIMENT ANALYSIS 23
1.15 MASS CUSTOMIZATION DATA REMODELING 23
1.16 BIG DATA FOR BIG REVENUE 24
1.17 BIG DATA FOR PREDICTIVE FINANCIAL CRIMES 24
BIG DATA IN FINANCE: AN ANALYSIS 27
1.18 UNDERSTANDING THE RELEVANCE OF BIG DATA IN THE FINANCIAL SERVICE MARKET 27
1.19 DIFFERENTIATING BIG DATA ANALYTICS FROM FINANCIAL ECONOMETRICS 28
1.20 COULD FINANCIAL BIG DATA ANALYTICS PREVENT ECONOMIC RECESSION? 29
1.21 TRANSFORMING BIG DATA ANALYTICS FOR FINANCIAL GAINS 30
1.22 CUSTOMER-FOCUSED BIG DATA FINANCIAL INITIATIVES: BANKING SECTOR EXPERIENCE 31
1.23 BIG DATA FOR EFFECTIVE FINANCIAL CONSOLIDATION: THE JABIL SUCCESS STORY 31
1.24 BUSINESS INTELLIGENCE AVERTING FINANCIAL SERVICE PROBLEM: THE KLOUT'S EXPERIENCE 32
1.25 BIG DATA AND ANALYTICS IN FINANCIAL SERVICES: THE CASE OF BECKER UNDERWOOD 33
1.26 BIG DATA SECURITY/PRIVACY ISSUES IN FINANCIAL SERVICES: THE GOOGLE LAWSUIT 33
BIG DATA IN FINANCE: THE COMPETITIVE MARKET LANDSCAPES 36
4.1 BIG DATA FINANCIAL MANAGEMENT SOLUTIONS 40
4.1.1 IBM 40
4.1.2 HP 41
4.1.3 TERADATA 42
4.1.4 DELL 45
4.1.5 ORACLE 47
4.1.6 SAP 48
4.1.7 EMC 49
4.1.8 CISCO SYSTEMS 50
4.1.9 MICROSOFT 52
4.1.10 FUSION-IO 53
4.1.11 SPLUNK 54
4.1.12 NETAPP 56
4.1.13 HITACHI 57
4.1.14 OPERA SOLUTIONS 58
4.1.15 CSC 59
4.1.16 MU SIGMA 60
4.1.17 BOOZ ALLEN HAMILTON 62
4.1.18 AMAZON 63
4.1.19 INTEL 64
4.1.20 CAPGEMINI 65
4.1.21 MARKLOGIC 66
4.1.22 CLOUDERA 67
4.1.23 ACTIAN 69
4.1.24 SGI 70
4.1.25 GOODDATA 71
4.1.26 1010DATA 72
4.1.27 10GEN 73
4.1.28 GOOGLE 74
4.1.29 ALTERYX 75
4.1.30 GUAVUS 76
4.1.31 VMWARE 77
4.1.32 PARACCEL 78
4.1.33 TIBCO SOFTWARE 79
4.1.34 INFORMATICA 80
4.1.35 ATTIVIO 81
4.1.36 QLIKTECH 82
BIG DATA IN FINANCE: PROSPECTS AND OPPORTUNITIES 84
4.2 THE FUTURE OF BIG DATA IN FINANCIAL SERVICES 84
4.3 MULTICHANNEL MARKETING IN BIG DATA 85
4.4 EMERGING MARKETS IN BIG DATA IN FINANCE 86
4.4.1 BRAZIL 86
4.4.2 CHINA 87
4.4.3 INDIA 88
4.4.4 EUROPE 90
4.4.5 NORTH AMERICA 91
CONCLUSIONS 93

List of Figures

Figure 1 Big Data Market Forecast 2013-2018 9
Figure 2 Big Data Paradigm 10
Figure 3 Migration Process of Platform Technology 11
Figure 4 Data Universe Zettabytes Generation 2013-2020 14
Figure 5 Financial Big Data Management Paradigm 17
Figure 6 Big Data Approaches for Financial Services 20
Figure 7 Big Data Functional Levels 21
Figure 8 Big Data for Predictive Financial Crimes 26
Figure 9 Big Data in Finance Market 2013-2018 28
Figure 10 Big Data as Competitive Differentiator for Financial Services 37
Figure 11 Big Data Revenue Share by Vendor Solutions 2013 38
Figure 12 Hadoop and NoSQL Vendor Revenue Share 2011-2013 39
Figure 13 Big Data in Finance Market 2014-2020 85
Figure 14 Big Data Market in Brazil 2013-2018 87
Figure 15 Market for Big Data in China 2013-2018 88
Figure 16 Big Data Market in India 2013-2018 89
Figure 17 Big Data Market in Europe 2013-2018 91
Figure 18 Big Data Market in North American 2013-2018 92

List of Tables

Table 1 IBM Big Data Financial Management Solutions 41
Table 2 HP Big Data Financial Management Solutions 42
Table 3 Teradata Big Data Financial Management Solutions 45
Table 4 Dell Big Data Financial Management Solutions 46
Table 5 Oracle Big Data Financial Management Solutions 48
Table 6 SAP Big Data Financial Management Solutions 49
Table 7 EMC Big Data Financial Management Solutions 50
Table 8 Cisco Big Data Financial Management Solutions 51
Table 9 Microsoft Big Data Financial Management Solutions 53
Table 10 Fusion-IO Big Data Financial Management Solutions 54
Table 11 Splunk Big Data Financial Management Solutions 55
Table 12 NetApp Big Data Financial Management Solutions 56
Table 13 Hitachi Big Data Financial Management Solutions 58
Table 14 Opera Solutions Big Data Financial Management Solutions 59
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 62
Table 18 Booz Allen Hamilton Big Data Financial Management Solutions 62
Table 19 Amazon Big Data Financial Management Solutions 64
Table 20 Intel Big Data Financial Management Solutions 65
Table 21 Capgemini Big Data Financial Management Solutions 66
Table 22 MarkLogic Big Data Financial Management Solutions 67
Table 23 Cloudera Big Data Financial Management Solutions 68
Table 24 Actian Big Data Financial Management Solutions 70
Table 25 SGI Big Data Financial Management Solutions 71
Table 26 GoodData Big Data Financial Management Solutions 72
Table 27 1010data Big Data Financial Management Solutions 73
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 77
Table 32 VMware Big Data Financial Management Solutions 78
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

To order this report: Big Data in Financial Services Industry: Market Trends, Challenges, and Prospects 2013 - 2018
http://www.reportlinker.com/p01937235/Big-Data-in-Financial-Services-Industry-Market-Trends-Challenges-and-Prospects-2013---2018.html#utm_source=prnewswire&utm_medium=pr&utm_campaign=Financial_Services

__________________________
Contact Clare: [email protected]
US: (339)-368-6001
Intl: +1 339-368-6001

SOURCE Reportlinker

More Stories By PR Newswire

Copyright © 2007 PR Newswire. All rights reserved. Republication or redistribution of PRNewswire content is expressly prohibited without the prior written consent of PRNewswire. PRNewswire shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon.

Latest Stories
ChatOps is an emerging topic that has led to the wide availability of integrations between group chat and various other tools/platforms. Currently, HipChat is an extremely powerful collaboration platform due to the various ChatOps integrations that are available. However, DevOps automation can involve orchestration and complex workflows. In his session at @DevOpsSummit at 20th Cloud Expo, Himanshu Chhetri, CTO at Addteq, will cover practical examples and use cases such as self-provisioning infra...
"Storpool does only block-level storage so we do one thing extremely well. The growth in data is what drives the move to software-defined technologies in general and software-defined storage," explained Boyan Ivanov, CEO and co-founder at StorPool, in this SYS-CON.tv interview at 16th Cloud Expo, held June 9-11, 2015, at the Javits Center in New York City.
You know you need the cloud, but you’re hesitant to simply dump everything at Amazon since you know that not all workloads are suitable for cloud. You know that you want the kind of ease of use and scalability that you get with public cloud, but your applications are architected in a way that makes the public cloud a non-starter. You’re looking at private cloud solutions based on hyperconverged infrastructure, but you’re concerned with the limits inherent in those technologies.
Is advanced scheduling in Kubernetes achievable?Yes, however, how do you properly accommodate every real-life scenario that a Kubernetes user might encounter? How do you leverage advanced scheduling techniques to shape and describe each scenario in easy-to-use rules and configurations? In his session at @DevOpsSummit at 21st Cloud Expo, Oleg Chunikhin, CTO at Kublr, answered these questions and demonstrated techniques for implementing advanced scheduling. For example, using spot instances and co...
As Marc Andreessen says software is eating the world. Everything is rapidly moving toward being software-defined – from our phones and cars through our washing machines to the datacenter. However, there are larger challenges when implementing software defined on a larger scale - when building software defined infrastructure. In his session at 16th Cloud Expo, Boyan Ivanov, CEO of StorPool, provided some practical insights on what, how and why when implementing "software-defined" in the datacent...
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, whic...
The use of containers by developers -- and now increasingly IT operators -- has grown from infatuation to deep and abiding love. But as with any long-term affair, the honeymoon soon leads to needing to live well together ... and maybe even getting some relationship help along the way. And so it goes with container orchestration and automation solutions, which are rapidly emerging as the means to maintain the bliss between rapid container adoption and broad container use among multiple cloud host...
The cloud era has reached the stage where it is no longer a question of whether a company should migrate, but when. Enterprises have embraced the outsourcing of where their various applications are stored and who manages them, saving significant investment along the way. Plus, the cloud has become a defining competitive edge. Companies that fail to successfully adapt risk failure. The media, of course, continues to extol the virtues of the cloud, including how easy it is to get there. Migrating...
Blockchain is a shared, secure record of exchange that establishes trust, accountability and transparency across business networks. Supported by the Linux Foundation's open source, open-standards based Hyperledger Project, Blockchain has the potential to improve regulatory compliance, reduce cost as well as advance trade. Are you curious about how Blockchain is built for business? In her session at 21st Cloud Expo, René Bostic, Technical VP of the IBM Cloud Unit in North America, discussed the b...
Imagine if you will, a retail floor so densely packed with sensors that they can pick up the movements of insects scurrying across a store aisle. Or a component of a piece of factory equipment so well-instrumented that its digital twin provides resolution down to the micrometer.
The need for greater agility and scalability necessitated the digital transformation in the form of following equation: monolithic to microservices to serverless architecture (FaaS). To keep up with the cut-throat competition, the organisations need to update their technology stack to make software development their differentiating factor. Thus microservices architecture emerged as a potential method to provide development teams with greater flexibility and other advantages, such as the abili...
In his keynote at 18th Cloud Expo, Andrew Keys, Co-Founder of ConsenSys Enterprise, provided an overview of the evolution of the Internet and the Database and the future of their combination – the Blockchain. Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settle...
Blockchain. A day doesn’t seem to go by without seeing articles and discussions about the technology. According to PwC executive Seamus Cushley, approximately $1.4B has been invested in blockchain just last year. In Gartner’s recent hype cycle for emerging technologies, blockchain is approaching the peak. It is considered by Gartner as one of the ‘Key platform-enabling technologies to track.’ While there is a lot of ‘hype vs reality’ discussions going on, there is no arguing that blockchain is b...
Product connectivity goes hand and hand these days with increased use of personal data. New IoT devices are becoming more personalized than ever before. In his session at 22nd Cloud Expo | DXWorld Expo, Nicolas Fierro, CEO of MIMIR Blockchain Solutions, will discuss how in order to protect your data and privacy, IoT applications need to embrace Blockchain technology for a new level of product security never before seen - or needed.
As DevOps methodologies expand their reach across the enterprise, organizations face the daunting challenge of adapting related cloud strategies to ensure optimal alignment, from managing complexity to ensuring proper governance. How can culture, automation, legacy apps and even budget be reexamined to enable this ongoing shift within the modern software factory? In her Day 2 Keynote at @DevOpsSummit at 21st Cloud Expo, Aruna Ravichandran, VP, DevOps Solutions Marketing, CA Technologies, was jo...