Big Data in the Financial Services Industry Growth Prospects Till, 2030 : Radiant Insights, Inc

“Big Data” originally emerged as a term to describe datasets whose size is beyond the ability of traditional databases to capture, store, manage and analyze. However, the scope of the term has significantly expanded over the years. Big Data not only refers to the data itself but also a set of technologies that capture, store, manage and analyze large and variable collections of data, to solve complex problems.

Amid the proliferation of real-time and historical data from sources such as connected devices, web, social media, sensors, log files and transactional applications, Big Data is rapidly gaining traction from a diverse range of vertical sectors. The financial services industry is no exception to this trend, where Big Data has found a host of applications ranging from targeted marketing and credit scoring to usage-based insurance, data-driven trading, fraud detection and beyond.

SNS Telecom & IT estimates that Big Data investments in the financial services industry will account for nearly $9 Billion in 2018 alone. Led by a plethora of business opportunities for banks, insurers, credit card and payment processing specialists, asset and wealth management firms, lenders and other stakeholders, these investments are further expected to grow at a CAGR of approximately 17% over the next three years.

The “Big Data in the Financial Services Industry: 2018 - 2030 - Opportunities, Challenges, Strategies & Forecasts” report presents an in-depth assessment of Big Data in the financial services industry including key market drivers, challenges, investment potential, application areas, use cases, future roadmap, value chain, case studies, vendor profiles and strategies. The report also presents market size forecasts for Big Data hardware, software and professional services investments from 2018 through to 2030. The forecasts are segmented for 8 horizontal submarkets, 6 application areas, 11 use cases, 6 regions and 35 countries.

The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

 Topics Covered

The report covers the following topics: 

 - Big Data ecosystem
- Market drivers and barriers
- Enabling technologies, standardization and regulatory initiatives
- Big Data analytics and implementation models
- Business case, application areas and use cases in the financial services industry
- 30 case studies of Big Data investments by banks, insurers, credit card and payment processing specialists, asset and wealth management firms, lenders, and other stakeholders in the financial services industry
- Future roadmap and value chain
- Profiles and strategies of over 270 leading and emerging Big Data ecosystem players
- Strategic recommendations for Big Data vendors and financial services industry stakeholders
- Market analysis and forecasts from 2018 till 2030

Interested in this report? Get your FREE sample now! https://www.radiantinsights.com/research/big-data-in-the-financial-services-industry-2018-2030/request-sample

 Hardware, Software & Professional Services

- Hardware
- Software
- Professional Services

Horizontal Submarkets

- Storage & Compute Infrastructure
- Networking Infrastructure
- Hadoop & Infrastructure Software
- SQL
- NoSQL
- Analytic Platforms & Applications
- Cloud Platforms
- Professional Services

Application Areas

- Personal & Business Banking
- Investment Banking & Capital Markets
- Insurance Services
- Credit Cards & Payment Processing
- Lending & Financing
- Asset & Wealth Management

Table of Contents

Chapter 1: Introduction 22
1.1 Executive Summary 22
1.2 Topics Covered 24
1.3 Forecast Segmentation 25
1.4 Key Questions Answered 28
1.5 Key Findings 29
1.6 Methodology 30
1.7 Target Audience 31
1.8 Companies & Organizations Mentioned 32

Chapter 2: An Overview of Big Data 35
2.1 What is Big Data? 35
2.2 Key Approaches to Big Data Processing 35
2.2.1 Hadoop 36
2.2.2 NoSQL 38
2.2.3 MPAD (Massively Parallel Analytic Databases) 38
2.2.4 In-Memory Processing 39
2.2.5 Stream Processing Technologies 39
2.2.6 Spark 40
2.2.7 Other Databases & Analytic Technologies 40
2.3 Key Characteristics of Big Data 41
2.3.1 Volume 41
2.3.2 Velocity 41

If you have any special requirements, please let us know and we will offer you the report as you want.

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