市场调查报告书

新技术带来丰富收获:亚太地区金融服务产业中早期导入人工智慧 (AI) 的20家企业案例

Many Things from the Shiny New Thing: 20 Early Adopters of Artificial Intelligence in Asia/Pacific Financial Services

出版商 IDC 商品编码 913848
出版日期 内容资讯 英文 24 Pages
订单完成后即时交付
价格
新技术带来丰富收获:亚太地区金融服务产业中早期导入人工智慧 (AI) 的20家企业案例 Many Things from the Shiny New Thing: 20 Early Adopters of Artificial Intelligence in Asia/Pacific Financial Services
出版日期: 2019年10月07日内容资讯: 英文 24 Pages
简介

人工智慧 (AI) 并非能够解决金融服务产业的所有问题。但透过适切的应用,将能大幅提升顾客体验/参与、优化营运效率、创造新产品/服务。预估在2022年,亚太地区超过50%的金融服务业者将投资相关的人工智慧 (AI) 技术。

本报告分析亚太地区 (日本以外) 金融服务市场的人工智慧 (AI) 导入情况和运用动向,汇整主要早期导入企业之目前应用情况、未来具潜力应用领域、以及推动未来普及时需解决的课题等情报。

摘要整理

概况

  • 谁在做什么?
  • 人工智慧 (AI) 正确定义
  • AI计画为何?
  • AI市场机会评估
    • 主要趋势
    • 益处
    • 课题
      • 识别适切案例
      • 数据呈现了最大难题
      • 核心策略中AI「缺少的那一片」
      • 变更管理的不适合尝试
      • 缺乏技术和人才
      • 缺乏技术基础建设
  • 最普遍的导入领域
  • AI领域早期导入者行动:代表案例 (20件)

技术买家建议

  • 需考虑的行动
    • 策略和赞助
      • 大胆思考,从小处开始
      • 管理代言问题
      • 建构多功能COE (Center of Excellence)
    • 流程识别和优化
      • 设定业务目标/问题
      • 流程的重新设计和重新构想
    • 人员和变更管理
      • 多功能合作:比想像还要重要
      • 专注主动变更管理
      • 思考新作用和技能
    • 可扩展的基础建设
      • 需要可扩展且可适应的技术基础建设
    • 数据和模式的生命周期管理
      • 注意数据各个面相
      • 思考AI生命周期管理模式
      • 强健安全性、合规性、治理能力可建立起信任

参考资料

  • 相关研究
  • 总结
目录
Product Code: AP43052218

In this report, IDC Financial Insights discusses how Asia/Pacific (excluding Japan) (APEJ) is embracing artificial intelligence (AI) and the many technologies that come under its ambit. Several early adopters of AI have emerged from the region, with a wide range of objectives from the ability to offer superior customer and employee experience and the augmentation of operations to the design and launch of new products and services.In our opinion, AI is not the answer to every business goal and problem. However, for those in which AI is the answer, it can significantly transform customer experience and engagement, optimize operational efficiencies, and create new products and services. Regardless of its promises and emerging evidence of significant benefits, AI adoption has been low. Most of the FSIs in the region were not born digital, and they are still stuck with traditional ways of thinking and working. They still do not consider AI as part of their core, enterprisewide strategy, and as a result, it is being implemented as part of a fragmented, siloed approach without any long-term road map to achieve scale.

However, we are nearing a tipping point and expect this situation to change considerably within the next two to three years as there are more successful use cases and real evidence of unprecedented benefits available in the market. This will further change with a better understanding of the capabilities of AI and as more institutions invest in AI readiness. Sneha Kapoor, research manager, IDC Financial Insights, says, "By 2022, IDC Financial Insights expects more than 50% of Asia/Pacific FSIs to invest in one or more AI technologies. Majority of projects will focus on three objectives: transform the customer experience, optimize operational efficiencies, and create new revenue streams. We also believe that AI will be one of the key technologies to drive institutions through digital business transformation."

Executive Snapshot

Situation Overview

  • Who Is Doing What?
  • Defining What Exactly Is AI
  • What Is an AI Project?
  • The AI Opportunity Assessment
    • Key Trends
    • Benefits
    • Challenges
      • Identifying the Right Use Cases
      • Data Presenting the Biggest Conundrum
      • Missing AI Piece in the Core Strategy
      • Inadequate Attempts at Change Management
      • Lack of Skills and Talent
      • Lack of Technical Infrastructure
  • Most Common Areas of Implementation so Far
  • 20 of the Best, Early Adopter Initiatives in AI

Advice for the Technology Buyer

  • Actions to Consider
    • Strategy and Sponsorship
      • Think Big But Definitely Start Small or at Least Somewhere
      • Management Endorsement Matters
      • Build a Cross-Functional COE
    • Process Identification and Optimization
      • Identify a Business Goal/Problem
      • Redesign and Reimagine Processes
    • People and Change Management
      • Cross-Functional Collaboration Is More Important Than You Think
      • Focus Proactive Change Management
      • Think About New Roles and New Skills
    • Scalable Infrastructure
      • Scalable and Adaptable Technical Infrastructure Is Needed
    • Data and Model Life-Cycle Management
      • Pay Attention to All Aspects of Data
      • Think About AI Model Life-Cycle Management
      • Strong Security, Compliance, and Governance Will Create Trust

Learn More

  • Related Research
  • Synopsis