銀行セクターのスコアカード：テーマ別調査

AIにおいて、主要銀行は、調査機関やプロトタイプに数百万米ドルを費やしています。現在の課題は、データの依存関係とアルゴリズム主導の意思決定に関する規制リスクの増大に対処しながら、顧客に最大の影響を与えるために、実証済みのユースケースを迅速に特定して展開することであると考えられています。

また、ビッグデータにおいて多くの銀行は、さまざまなサイロに存在する、不正確、不完全、および一貫性のないデータのフラグメントを含む異種アプリケーションポートフォリオを運用しています。ビッグデータの「V（データ量、速さ、多様性）」が増加するにつれて、レガシー処理およびストレージ技術はさらに弱くなっています。

当レポートは、銀行セクターのスコアカードについて調査しており、市場の動向や見通し、COVID-19による業界への影響、セクターごとの実績などの情報を提供しています。

目次

目次

イントロダクション

• テーママップ
• COVID-19リテールバンキングへの影響

セクター実績

• トップ10のテーマ
• セクタースコアカード：銀行
• 誰が？
• テーマ別画面
• 評価画面
• 付録：調査手法

This report assesses the key themes that are transforming the banking market right now, utilizing our thematic scoring methodology to identify which companies will do well in the market in the future - and the companies that will falter as a result of their lack of investment in the key banking themes. In this report, we score over 50 of the world's leading banking players against the 10 themes that are impacting their industry the most. Our resulting thematic engine helps us identify the strongest and weakest players in the banking sector over the next two years.

It's not necessary to be a 'bank' to disrupt banking. Niche fintechs - highly specialized, free from legacy, and able to bypass bank regulation - have 'unbundled' component pieces of financial services, giving consumers more of what they want more quickly than incumbent banks can. Big tech, meanwhile, leveraging platform economics and data-driven business models, have brought new levels of personalization and convenience to payments, lending, product comparison, and money management. However, a banking license does confer the right to hold deposits and earn net interest margin, and the revenue pool associated with those activities exceeded $5tn in 2019. That business is not going away any time soon. Rather, it is being digitally transformed - re-invented, even - by 10 key themes.

Scope

• Within AI: Leading incumbent banks are spending millions on research institutes and prototypes. The challenge now is identifying and deploying those most 'proven' use cases quickly for maximum customer impact, while addressing data dependencies and growing regulatory risks around algorithm-led decision-making. Because AI-driven business models typically have fly-wheel momentum, big-tech companies have significant first-mover advantages that incumbent banks will likely prove unable to make up.
• Within big data: Many banks operate on a heterogeneous application portfolio with fragments of often inaccurate, incomplete, and inconsistent data that reside in various silos. As the Vs of big data increase every day - more data (volume), coming in more quickly (velocity), from different sources and of different types (variety) - legacy processing and storage techniques creak even further.

Reasons to Buy

• Identify which themes drive share price performance for the leading retail banks.
• Understand which banks are best positioned for success within critical themes and why.
• Learn which banks are under-invested in key themes and most vulnerable to disruption.
• Understand which themes your institution can address (and how) to drive share price.

Table of Contents

Table of Contents

INTRODUCTION

• Theme map
• COVID-19 IMPACT ON RETAIL BANKING

SECTORPERFORMANCE

• TOP 10THEMES
• SECTOR SCORECARD: BANKING
• Who's who
• Thematic screen
• Valuation screen
• APPENDIX: OUR THEMATIC RESEARCH METHODOLOGY