表紙
市場調査レポート

世界の金融業におけるビッグデータへのIT投資:2015年〜2019年

Global Big Data IT Spending in Financial Sector - Market Research 2015-2019

発行 TechNavio (Infiniti Research Ltd.) 商品コード 341159
出版日 ページ情報 英文 82 Pages
即納可能
価格
本日の銀行送金レート: 1USD=104.18円で換算しております。
Back to Top
世界の金融業におけるビッグデータへのIT投資:2015年〜2019年 Global Big Data IT Spending in Financial Sector - Market Research 2015-2019
出版日: 2015年09月30日 ページ情報: 英文 82 Pages
概要

現在、多くの金融機関が顧客データ管理、リスク、従業員のモビリティ、多経路における有効性などの課題に対応するため、従来型データインフラの改善を検討しており、これらの課題が長期戦略としての金融機関へのビッグデータの導入を推進しています。ビッグデータは2014年末には過去5年間で金融業界においてもっとも急速に導入が進んだ技術となる見込みです。世界の金融業界におけるビッグデータへのIT投資額は、2014年から2019年にかけて25.5%のCAGRで成長すると予測されています。

当レポートでは、世界の金融業におけるビッグデータへのIT投資の動向について調査し、ビッグデータの定義、金融サービス部門におけるビッグデータの重要性、製品および地域別の主要動向、市場規模の推移と予測、市場成長への各種影響因子の分析、競合環境、主要ベンダーのプロファイルなどをまとめています。

第1章 エグゼクティブサマリー

  • ハイライト

第2章 調査範囲

  • 市場概要
  • 主要ベンダーの提供製品

第3章 市場調査手法

  • 調査手法
  • 経済指標

第4章 イントロダクション

  • 主な市場概況

第5章 市場環境

  • ビッグデータの定義
  • 金融サービス部門におけるビッグデータ
  • 市場規模・予測

第6章 製品別市場

  • ハードウェア収益
  • ソフトウェア
  • サービス

第7章 地域分析

  • 南北アメリカ
  • アジア太平洋
  • 欧州・中東・アフリカ

第8章 市場成長因子

第9章 市場成長因子の影響

第10章 市場の課題

第11章 成長因子と課題の影響

第12章 市場動向

第13章 ベンダー情勢

  • 競合シナリオ
  • 他の有力ベンダー

第14章 主要ベンダーの分析

  • Alteryx
  • Capgemini
  • IBM
  • Oracle
  • SAP
  • SAS Institute

第15章 付録

  • 略語リスト

第16章 Technavioについて

図表

目次
Product Code: IRTNTR7055

About big data IT spending in financial services

The financial services are among the most data-driven industries. Financial services institutions operate within regulatory environments that require firms to store and analyze several years of transactional data. For making the most from the businesses, financial services relies on relational technologies coupled with business intelligence tools to handle the ever increasing data and analytics burden. In today's world of information, the financial service industry is witnessing a disruptive change in the way do businesses worldwide. Regulatory reforms majorly drive this change. Ailing business and customer settlements, continuous economic crisis in other industry verticals, high cost of new technology and business models, and high degree of industry consolidation and automation are some of the other growth drivers.

Many financial services currently focus on improving their traditional data infrastructure as they have been addressing issues such as customer data management, risk, workforce mobility, and multichannel effectiveness. These daily problems led financial organization to deploy big data as a long-term strategy. By the end of 2014, big data has turned out to be the fastest growing technology adopted by the financial institutions over the past five years.

Technavio's analysts forecast global big data IT spending in financial services market to grow at a CAGR of 25.5% over the period 2014-2019.

Covered in this report

This report covers the present scenario and the growth prospects of the global big data IT spending in financial services for 2015-2019. To calculate the market size, the report considers revenue generated from the sale of big data solutions only in the financial services sector.

It includes big data hardware, software, and services revenue to calculate the market size. In order to calculate hardware, software, and IT services spending, the following sub-segments have been considered:

  • Hardware: Servers, networking equipment, and storage equipment
  • Software: Apache Hadoop-related solutions and cloud solutions
  • Services: Analytics, consulting, support, and professional services

Technavio's report, Global Big Data IT Spending in Financial Services Market 2015-2019, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers Americas, APAC, and EMEA. It also covers the landscape of the global big data IT spending in financial services market and its growth prospects in the coming years. The report includes a discussion of the key vendors operating in this market.

Key regions

  • Americas
  • APAC
  • EMEA

Key vendors

  • Capgemini
  • IBM
  • Oracle
  • SAP
  • SAS Institute

Other Prominent Vendors

  • Alteryx
  • Atos
  • Chartio
  • Cirro
  • Clearstory Data
  • Continuum Analytics
  • Datameer
  • DataStax
  • Emc2
  • Enthought
  • Maana
  • MapR technologies
  • Predixion Software

Key market driver

  • Explosive data growth
  • For a full, detailed list, view our report

Key market challenge

  • Lack of big data technology expertise
  • For a full, detailed list, view our report

Key market trend

  • High spending in customer engagements
  • For a full, detailed list, view our report

Key questions answered in this report

  • What will the market size be in 2019 and what will the growth rate be?
  • What are the key market trends?
  • What is driving this market?
  • What are the challenges to market growth?
  • Who are the key vendors in this market space?
  • What are the market opportunities and threats faced by the key vendors?
  • What are the strengths and weaknesses of the key vendors?

Table of Contents

PART 01: Executive summary

  • Highlights

PART 02: Scope of the report

  • Market overview
  • Top-vendor offerings

PART 03: Market research methodology

  • Research methodology
  • Economic indicators

PART 04: Introduction

  • Key market highlights

PART 05: Market Landscape

  • Definition of big data
  • Big data in financial services sector
  • Market size and forecast

PART 06: Market segmentation by product

  • Hardware revenue
  • Software segment
  • Services segment

PART 07: Geographical Segmentation

  • Americas
  • APAC
  • EMEA

PART 08: Market Growth Drivers

PART 09: Impact of drivers

PART 10: Market Challenges

PART 11: Impact of drivers and challenges

PART 12: Market Trends

PART 13: Vendor landscape

  • Competitive scenario
  • Other prominent vendors

PART 14: Key vendor analysis

  • Alteryx
  • Capgemini
  • IBM
  • Oracle
  • SAP
  • SAS Institute

PART 15: Appendix

  • List of abbreviations

PART 16: Explore Technavio

List of Exhibits

  • Exhibit 01: Product, services, and solutions
  • Exhibit 02: Applications of big data
  • Exhibit 03: Applications of big data in financial services sector
  • Exhibit 04: Global big data IT spending market in financial services sector 2014-2019 ($ billions)
  • Exhibit 05: Global big data IT spending market in financial services by product 2014
  • Exhibit 06: Global big data IT spending market in financial services sector by product 2014-2019
  • Exhibit 07: Hardware segment 2014-2019 ($ billions)
  • Exhibit 08: Hardware revenue segmentation 2014
  • Exhibit 09: Software segment 2014-2019 ($ billions)
  • Exhibit 10: Global big data IT spending market in financial services sector 2014-2019 ($ billions)
  • Exhibit 11: Geographical Segmentation 2014
  • Exhibit 12: Geographical segmentation 2014-2019
  • Exhibit 13: Big data IT spending market in financial services sector in Americas 2014-2019 ($ billions)
  • Exhibit 14: Big data IT spending market in financial services sector in APAC 2014-2019 ($ billions)
  • Exhibit 15: Big data IT spending market in financial services sector in EMEA 2014-2019 ($ billions)
  • Exhibit 16: Activities that determine which solutions vendors adopt
  • Exhibit 17: Impact of drivers
  • Exhibit 18: Impact of drivers and challenges
  • Exhibit 19: Alteryx: Products
  • Exhibit 20: Capgemini: Business segmentation by revenue 2014
  • Exhibit 21: Capgemini: Business segmentation by revenue 2013 and 2014 ($ billion)
  • Exhibit 22: Capgemini: Geographical segmentation by revenue 2014
  • Exhibit 23: IBM: Business segmentation
  • Exhibit 24: Global technology services revenue
  • Exhibit 25: Oracle: Business segmentation by revenue 2014
  • Exhibit 26: Oracle: Business segmentation by revenue 2013 and 2014 ($ millions)
  • Exhibit 27: Oracle: Geographical segmentation by revenue 2014
  • Exhibit 28: SAP: Business segmentation by revenue 2014
  • Exhibit 29: SAP: Business segmentation by revenue 2013 and 2014 ($ billions)
  • Exhibit 30: SAP: Geographical segmentation by revenue 2014
  • Exhibit 31: SAS: Revenue segmentation by industry 2014
  • Exhibit 32: SAS: Revenue segmentation by geography 2014
Back to Top