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市场调查报告书
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1432848

业务巨量资料分析：市场占有率分析、产业趋势与成长预测（2024-2029）

Big Data Analytics In Banking - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3个工作天内

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简介目录

业务巨量资料分析市场规模预计到 2024 年为 858 万美元，预计到 2029 年将达到 2,428 万美元，在预测期内（2024-2029 年）复合年增长率为 23.11%。

银行市场大数据分析

巨量资料分析可帮助银行根据多种见解的输入来了解客户行为，包括投资模式、购物趋势、投资动机、个人或财务背景等。

主要亮点

  • 产生的资料量的显着增加和政府要求是银行业采用巨量资料分析的主要驱动力。随着科技的进步，消费者使用更多的设备（例如智慧型手机）来发起交易，这会影响交易量。鑑于目前的资料成长速度，需要更好的资料收集、组织、整合和分析。
  • 政府法规和大量资料收集正在影响银行业。随着科技的发展，越来越多的消费者使用更多的设备（例如智慧型手机）来发起交易，增加了交易量。这推动了巨量资料分析，资料分析师可以在一处查看所有资料点并快速找到它们。借助这种统一的图片，团队成员可以交流可以加强银行业的见解。
  • 巨量资料分析解决方案提供发现新业务洞察所需的处理能力、持久性和分析能力，同时让企业将所有资料储存在灵活且经济实惠的环境中。巨量资料分析工具提供了收集和追踪结构化和非结构化资料以及组织资料各种来源的资料的技术。
  • 大多数旧有系统无法处理不断增加的负载。利用过时的基础设施来收集、储存和分析所需数量的资料可能会损害整个系统的稳定性。为了解决这个问题，组织必须提高处理能力或完全重新设计其係统。
  • 由于银行业越来越多地使用和采用资料分析来分析和探索消费者资料并实施有效的策略，COVID-19 的爆发对银行业的数据分析产生了重大影响。由于科技的快速发展，银行业的资料分析正在经历显着的成长。

业务巨量资料分析的市场趋势

全行风险管理和内部控制推动成长

  • 透过利用尖端技术，银行可以降低信用风险并根据各种风险标准做出更好的决策。借助巨量资料和分析平台，银行可以控制信用风险并避免违约情况。
  • 另一个明显的迹像是零售银行正在利用巨量资料分析进行信用风险管理。事实证明，应用基于支付交易行为模式的信用风险指标可以比基于帐户违约和逾期付款的传统指标更早侦测信用事件。
  • 使用资料和分析工具进行即时诈欺检测，可以更密切地监控债务人并具有预测贷款损失的能力，有助于降低信贷和流动性风险。
  • 正如美国银行所证明的那样，巨量资料可用于识别高风险帐户。美国银行的企业投资小组负责计算 950 万笔房屋抵押贷款的违约机率，这使得美国银行能够预测违约损失。该银行将计算坏帐所需的时间从 96 小时减少到 4 小时，从而提高了效率。

欧洲预计将出现显着成长

  • 管理金融机构如何交换和保护客户个人资讯的最着名的法规是欧盟的《一般资料保护条例》。
  • 此外，由于欧盟 (EU)付款服务指令 (PSD2)，现在可以透过开放应用程式介面 (API) 进行资料交换。由于资料现在可以自由共用，因此收集、操作和分析资料的能力变得越来越重要。
  • 此外，客户数量和监管变化预计将很快增加。因此，对客户分析和智慧技术的需求应该会增加。
  • 英国劳埃德银行业务集团采用资料分析来满足不同客户类别的需求，同时优化目标细分市场的成长。
  • 欧洲零售银行正在利用巨量资料分析解决方案，以「开放银行业务」趋势解决传统金融机构数十年来面临的问题。

业务巨量资料分析概述

业务的巨量资料分析市场高度分散，因为有许多全球公司为银行提供用于诈欺侦测和管理、客户分析和社群媒体分析等不同应用的巨量资料分析解决方案。该市场的主要参与企业包括 Oracle 公司、IBM 公司和 SAP SE。

  • 2023 年 2 月 - Alteryx 宣布为 Alteryx Inc 的云端基础的分析工具添加新的自助服务和企业级功能，以帮助您做出更快、更明智的决策。该平台现在包括对 Designer Cloud 的完全存取权限，并经过改进，可以为所有技能水平的员工提供熟悉且易于使用的拖放介面，而不会影响资料管治或安全标准。它已经完成了。
  • 2022 年 8 月 - Aspire Systems 宣布采用整体方法来加速实施。这项创新由人工智慧提供支持，可提高实施速度。透过这种新的自主应用程式实施方法，Aspire Systems 可以帮助企业从 Oracle 云端 ERP 应用程式实施中获得最大价值。

其他福利：

  • Excel 格式的市场预测 (ME) 表
  • 3 个月的分析师支持

目录

第一章简介

  • 研究假设和市场定义
  • 调查范围

第二章调查方法

第三章执行摘要

第四章市场洞察

  • 市场概况
  • 产业吸引力－波特五力分析
    • 新进入者的威胁
    • 买家/消费者的议价能力
    • 供应商的议价能力
    • 替代品的威胁
    • 竞争公司之间敌对关係的强度
  • 产业价值链分析
  • COVID-19 对市场的影响

第五章市场动态

  • 市场驱动因素
    • 落实政府倡议
    • 全行风险管理和内部控制推动成长
    • 银行产生的资料量增加
  • 市场挑战
    • 缺乏资料隐私和安全

第 6 章相关案例和使用案例

第七章市场区隔

  • 按解决方案类型
    • 资料发现和视觉化 (DDV)
    • 进阶分析 (AA)
  • 按地区
    • 北美洲
    • 欧洲
    • 亚太地区
    • 拉丁美洲
    • 中东/非洲

第八章 竞争形势

  • 公司简介
    • IBM Corporation
    • SAP SE
    • Oracle Corporation
    • Aspire Systems Inc.
    • Adobe Systems Incorporated
    • Alteryx Inc.
    • Microstrategy Inc.
    • Mayato GmbH
    • Mastercard Inc.
    • ThetaRay Ltd

第九章投资分析

第10章市场的未来

简介目录
Product Code: 53906

The Big Data Analytics In Banking Market size is estimated at USD 8.58 million in 2024, and is expected to reach USD 24.28 million by 2029, growing at a CAGR of 23.11% during the forecast period (2024-2029).

Big Data Analytics In Banking - Market

Based on the inputs obtained from numerous insights, such as investment patterns, shopping trends, investment motivation, and personal or financial background, big data analytics can help banks understand client behavior.

Key Highlights

  • The considerable increase in the volume of data generated and governmental requirements are the main forces behind adopting Big Data analytics in the banking sector. With the development of technology, consumers are using more and more devices to start transactions (such as smartphones), which impacts the volume of transactions. Given the current data growth rate, better data collection, organization, integration, and analysis are necessary.
  • Government rules and considerable data gathering are affecting the banking industry. As technology develops, more consumers are using more devices to start transactions (such as smartphones), which boosts the volume of transactions. This motivates big data analytics, which gives data analysts a single location to see and quickly locate all data points. Thanks to this consolidated picture, team members can exchange insights that could enhance the banking industry.
  • A Big Data Analytics solution offers the processing, persistence, and analytic capabilities necessary to unearth fresh business insights while enabling a company to store all its data in a flexible, affordable environment. An analytics tool for big data gathers and keeps track of structured and unstructured data and techniques for arranging enormous amounts of wildly different data from various sources.
  • The majority of legacy systems are unable to handle the rising burden. The entire system's stability may be compromised if the necessary amounts of data are gathered, stored, and analyzed utilizing an obsolete infrastructure. Organizations must either improve their processing capacity or entirely redesign their systems to tackle the issue.
  • Due to the rise in usage and adoption in banking sectors to analyze and research consumer data and implement efficient strategies, the COVID-19 pandemic has significantly impacted data analytics in the banking industry. Because of the rapid evolution of technology, data analytics in banking has seen tremendous growth.

Big Data Analytics in Banking Market Trends

Risk Management and Internal Controls Across the Bank to Witness the Growth

  • With the use of cutting-edge technologies, banks can reduce credit risk and make better decisions based on a variety of risk criteria. Banks can control credit risk and avert default circumstances thanks to the big data and analytics platform.
  • Additionally, a blatant indicator is the retail bank's use of Big Data analytics for credit risk management. It has been demonstrated that applying credit risk indicators based on behavioral patterns in payment transactions allows for the detection of credit events much sooner than conventional indicators based on overdrawn accounts and late payments.
  • Real-time fraud detection using data and analytics tools helps reduce credit and liquidity risk by enabling close monitoring of debtors and the ability to foresee loan default.
  • Big data can be used to identify high-risk accounts, as demonstrated by The Bank of America. For 9.5 million mortgages, the Corporate Investment Group is responsible for calculating the likelihood of default, which helped Bank of America forecast losses from loan defaults. By cutting the time needed to calculate loan defaults from 96 to 4 hours, the bank was able to increase its efficiency.

Europe to Expected to Witness Significant Growth

  • The most well-known rule governing how financial organizations exchange and safeguard customers' private information continues to be the General Data Protection Rule of the European Union.
  • Moreover, data exchange was made possible through open application programming interfaces (APIs) as a result of the Payment Services Directive (PSD2) by the European Union. Due to an environment where data can be shared freely, the capacity to collect, handle, and analyze data has grown in importance.
  • Additionally, it is anticipated that both the number of customers and regulatory revisions will rise shortly. The demand for customer analytics and intelligence technologies should consequently increase.
  • The UK-based Lloyds Banking Group employed data analytics to meet the needs of diverse client categories while optimizing growth in targeted segments.
  • European retail banks are using Big Data analytics solutions due to the "open banking" trend, which addresses problems that traditional financial institutions have faced for decades.

Big Data Analytics in Banking Industry Overview

Big Data Analytics In Banking Market is quite fragmented due to the existence of numerous global firms that provide a range of big data analytics solutions for banks for diverse applications, such as fraud detection and management, customer analytics, social media analytics, etc. Oracle Corporation, IBM Corporation, and SAP SE are some of the major market participants.

  • February 2023 - Alteryx announced new self-service and enterprise-grade capabilities to its Alteryx Inc cloud-based analytics tool to support clients in making quicker and more informed decisions. With full access to Designer Cloud now included, the platform has been improved to provide employees of all skill levels with an approachable, simple-to-use drag-and-drop interface without compromising data governance or security standards.
  • August 2022 - Aspire Systems launches the holistic approach to accelerate implementation. This innovation is powered by AI and drives implementation speeds. With this new autonomous application implementation methodology, Aspire Systems is geared to help businesses derive maximum value out of their Oracle Cloud ERP Application implementation.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions & Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Force Analysis
    • 4.2.1 Threat of New Entrants
    • 4.2.2 Bargaining Power of Buyers/Consumers
    • 4.2.3 Bargaining Power of Suppliers
    • 4.2.4 Threat of Substitute Products
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Industry Value Chain Analysis
  • 4.4 Impact of COVID-19 on the Market

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Enforcement of Government Initiatives
    • 5.1.2 Risk Management and Internal Controls Across the Bank to Witness the Growth
    • 5.1.3 Increasing Volume of Data Generated by Banks
  • 5.2 Market Challenges
    • 5.2.1 Lack of Data Privacy and Security

6 RELEVANT CASE STUDIES AND USE CASES

7 MARKET SEGMENTATION

  • 7.1 By Solution Type
    • 7.1.1 Data Discovery and Visualization (DDV)
    • 7.1.2 Advanced Analytics (AA)
  • 7.2 By Geography
    • 7.2.1 North America
    • 7.2.2 Europe
    • 7.2.3 Asia-Pacific
    • 7.2.4 Latin America
    • 7.2.5 Middle East and Africa

8 COMPETITIVE LANDSCAPE

  • 8.1 Company Profiles
    • 8.1.1 IBM Corporation
    • 8.1.2 SAP SE
    • 8.1.3 Oracle Corporation
    • 8.1.4 Aspire Systems Inc.
    • 8.1.5 Adobe Systems Incorporated
    • 8.1.6 Alteryx Inc.
    • 8.1.7 Microstrategy Inc.
    • 8.1.8 Mayato GmbH
    • 8.1.9 Mastercard Inc.
    • 8.1.10 ThetaRay Ltd

9 INVESTMENT ANALYSIS

10 FUTURE OF THE MARKET