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997913

Artificial Intelligence (AI) in Banking - Thematic Research

Published: | GlobalData | 42 Pages | Delivery time: 1-2 business days

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Artificial Intelligence (AI) in Banking - Thematic Research
Published: March 31, 2021
GlobalData
Content info: 42 Pages
Delivery time: 1-2 business days
  • Description
  • Table of Contents

AI is overhauling the way that banks interact with their clients. No longer do they rely on in-person customer service. Instead, they are innovating with intelligent chatbots that can provide 24/7 service, with almost zero human intervention and marginal cost. The use of big data in risk assessments gives banks more visibility over their clients than ever before, and the prospect of much greater personalization across credit pricing, day-to-day customer interaction, and digital financial guidance and advice. AI is also playing a critical role in the response to the growing frequency and severity of cyber-attacks. As cybercriminals employ more advanced tools, banks must keep pace by employing machine learning tools to hunt and counter these activities, which are too dynamic to be countered manually. The entire banking stack is being upended by AI; to survive, banks must make adopting it a priority - or risk losing out to cloud-native fintechs that have incorporate AI in their operations from day one.

The main focus of this report is technologies across the AI value chain. We have divided this segment into seven technologies: machine learning, data science, conversational platforms, computer vision, AI chips, smart robots, and context-aware computing.

Scope

  • GlobalData forecasts that retail banks will spend $4.9bn on AI platforms worldwide by 2024. This is up from $1.8bn in 2019, representing a compound annual growth rate of 21.8%.

Reasons to Buy

  • Identify key players within the AI value chain.
  • Understand key business challenges driving AI spend in banking.
  • Learn about priority AI investment areas for incumbent banks, supported by case study insight.
  • Access proprietary market sizing and growth forecast data for AI in banking.
Product Code: GDRB-TR-S030

Table of Contents

Table of Contents

Executive summary

  • AI value chain
  • Machine learning
  • Data science
  • Conversational platforms
  • Computer vision
  • AI chips
  • Smart robots
  • Context-aware computing
  • Banking challenges
  • The impact of AI on banking
  • Case studies
  • Market size and growth forecasts
  • Mergers and acquisitions
  • AI timeline
  • Companies
  • Sector scorecard
  • Glossary
  • Further reading
  • Our thematic research methodology
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