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フィンテックにおけるAI:ロボアドバイザー、融資、インシュアテック&レグテック 2018-2022年

AI in Fintech

Roboadvisors, Lending, Insurtech & Regtech 2018-2022

 

出版社 出版年月電子媒体価格ページ数
Juniper Research
ジュニパーリサーチ社
2018年1月GBP2,250
企業ライセンス
77

サマリー

このレポートはフィンテックにおける人工知能(AI)を調査し、AIの新しい利用により与えられる従来の、いわゆるやっかいとも言えた金融サービスへの影響・破壊を分析しています。

分析は下記のサービスセグメント別に行われています。

  • ロボアドバイザー
  • チャットボット
  • 融資
  • 保険
  • 規制への対応と不正

フィンテックにおけるAIへのベンチャーキャピタルの投資分析

  • ベンチャーキャピタルから出資された企業100社
  • AIの焦点のブレイクダウン
  • 総投資

地域別分析

  • ブラジル
  • カナダ
  • 中国
  • デンマーク
  • フランス
  • インド
  • ドイツ
  • 日本
  • メキシコ
  • ノルウェー
  • ポルトガル
  • スペイン
  • スウェーデン
  • 英国
  • 米国

OverView

Juniper’s latest AI in Fintech research highlights how the financial industry is being further disrupted through novel use of AI (artificial intelligence) to deliver services in a manner that upends traditional, cumbersome services.

Juniper’s incisive research provides unique insights into the market, examining key regulatory forces, service provider challenges alongside recommendations and strategic opportunities.

The analysis covers key industry service segments, including:

  • Roboadvisors
  • Chatbots
  • Lending
  • Insurance
  • Regulatory Compliance & Fraud
This research suite comprises:
  • Market Trends & Competitive Landscape (PDF)
  • 5 Year Market Sizing & Forecast (PDF & Excel)

Key Features

  • Sector Dynamics: AI drivers, Regional regulatory landscape analysis, strategic opportunities and recommendations for:
    • Roboadvisors
    • Chatbots
    • Lending
    • Insurance
    • Regulatory Compliance & Fraud
  • Investment Landscape: analysis of VC investment in AI in Fintech, covering:
    • 100 venture-backed companies
    • Breakdown of AI focus
    • Total investment received
  • Juniper Leaderboard: Key player capability and capacity assessment for 12 emerging AI in Fintech service providers.
  • Benchmark industry forecasts: market segment forecasts for key AI in Fintech verticals, including:
    • Roboadvisors
    • Consumer Lending
    • Insurance
    • Regulatory Compliance

Key Questions

  1. How is the regulatory landscape expected to impact the development of AI-driven services in Fintech?
  2. Which strategies should service providers look to apply when developing AI-driven Fintech services?
  3. What are the key trends shaping the AI in Fintech market?
  4. What are the strategic opportunities available to stakeholders?
  5. What is the size of the revenue opportunity for AI in Fintech?

Companies Referenced

Profiled: ComplyAdvantage, Elliptic, Kabbage, Lemonade, Onfido, Scalable, Capital, Sentient Technologies, The Floow, Tractable, Upstart, Wealthfront, ZestFinance.
 
Mentioned: Active.ai, Acuity Trading, Affirm, Ageas, Agero, AIA (American Insurance Association), Aidyia Limited, AIM, Aire, Alchemedia, Algoriz, Allianz, Alpaca, AlphaSense, Alpine Data Labs, Amazon, American Express, Anodot, Apple, Applied Data Finance, AppZen, Argon Credit, Argyle Data, Ascensus, ASEAN (Association of Southeast Asia Nations), Avant, AXA, Ayasdi, Baidu, BehavioSec, Bigstream Solutions, Binatix, BlackRock, Bosch, Cape Analytics, Captricity, CFPB (Consumer Financial Protection Bureau), Change Labs, Charles Schwab, Checkrecipient, Citibank, Clarity Money, Cleo, Clinc, Clone Algo, CognitiveScale, Coinbase, CollectAI, Context Relevant, cortical.io, Couchsurfing, Creamfinance, Credit Suisse, CreditVidya, Cyence, Dataminr, DataRobot, Descartes Labs, Deutsche Bundesbank, Digit, Digital Asset Holdings, Digital Reasoning Systems, Dimebox, Direct Line, Domeyard, EBA (European Banking Authority), eBay, EIOPA (European Insurance & Occupation Pensions Authority), Encompass Corporation, Endeca/Oracle, Equifax, ESMA (European Securities & Markets Authority), Etsy, Experian, Facebook, FCA (Financial Conduct Authority), FeedStock, FeedZai, Float, Ford, Form3, Fortia Financial Solutions, ForwardLane, Fosun Group, Fount, Fraugster, FutureAdvisor, Fyle Technologies, Gem, Google, Groupe PSA, H2O.ai, Habito, Homebot, Horizons Ventures, HSBC, Indico Data Solutions, ING, iSentium, IWF (Internet Watch Foundation), James, JD.com, Jewel Paymentech, Kasisto, Kensho Technologies, Lending Club, LexisNexis, Lloyd’s of London, Lucena Research, M Systems, Mastercard, Microsoft, Mitchell, MoneyLion, Naborly, NAIC (National Association of Insurance Commissioners), Narrative Science, NCIB (National Insurance Crime Bureau), NetChain Squared, Neurensic, Nissan, Numenta, Numerai, OCC (Office of the Comptroller of the Currency), Opera Solutions, Orbital Insight, Paxata, Payment Rails, PayPal, Penny App, Personetics Technologies, Pit.ai, Powermat, PredicSis, PwC, QuickBooks, Railsbank, Rakuten, Redfin, Renault, RiskGenius, Sage, Salesforce, SanDisk, Santander, Scotiabank, SEC (Securities & Exchange Commission), Shift Technology, Siemens, Sift Science, Signal Media, SigOpt, Silvergate Bank, Skytree, SmartZip Analytics, Socure, SoftBankm Stripe, Tata Communications, Trifacta, Trim, TrueAccord, Trumid, UberEATS, Understory, Vanguard, Venmo, Wag, Walnut Algorithms, WeCash, Wint, Wonga, WorkFusion, Xero, XL Catlin, Y Combinator, Zeitgold, Zendrive, Zipcar, Zurich.
 

Data & Interactive Forecast

Juniper’s AI in Fintech forecast suite includes:
  • Segment splits for:
    • Roboadvisors
    • Consumer Lending
    • Insurance
    • Regulatory Compliance
  • Regional splits for 8 key regions, as well as country level data splits for:
    • Brazil
    • Canada
    • China
    • Denmark
    • France
    • India
    • Germany
    • Japan
    • Mexico
    • Norway
    • Portugal
    • Spain
    • Sweden
    • UK
    • US
  • Interactive Scenario Tool allowing users to manipulate Juniper’s data for 6 different metrics.
  • Access to the full set of forecast data of 27 tables and over 3,100 datapoints.
Juniper Research’s highly granular interactive Excels enable clients to manipulate Juniper’s forecast data and charts to test their own assumptions using the Interactive Scenario Tool; and compare select markets side by side in customised charts and tables. IFxls greatly increase clients’ ability to both understand a particular market and to integrate their own views into the model.
 
Regions:
8 Key Regions - includes North America, Latin America, West Europe, Central & East Europe, Far East & China, Indian Subcontinent, Rest of Asia Pacific and Africa & Middle East
Countries:
Brazil, Canada, China, Denmark, France, Germany, India, Japan, Mexico, Norway, Portugal, Spain, Sweden, UK, USA

 



目次

Table of Contents

1. Key Takeaways & Strategic Recommendations

1.1 Key Takeaways . 6
Figure 1.1: AI in Fintech Market Forecast Snapshot, 2022 . 6
1.2 Strategic Recommendations . 7

2. AI in Fintech: Introduction

2.1 Introduction . 9
Figure 1.1: AI Skills in Fintech . 9
2.2 Impact on the Financial Industry . 10
2.3 Investment Landscape . 11
Figure 1.2: AI in Fintech Funding, Split by Application/Service Field, Selected Companies 2004-2017 . 11
Table 1.3: AI in Fintech VC Funding . 12
2.4 Key Market Forces . 17
2.4.1 Data . 17
Figure 1.4: Natural Language Classification Algorithm Performance, According to Number of Words in the Dataset . 18
2.4.2 Cost . 18
2.4.3 Regulation . 19
2.4.4 Overhype . 19

3. AI: Disruption in Fintech

3.1 Roboadvisors . 21
3.1.1 AI Drivers . 21
Case Study: Scalable Capital . 21
3.1.2 Regulatory Environment in Key Markets . 21
i. US . 21
ii. UK . 23
iii. EU . 24
3.1.3 Opportunities & Recommendations . 24
Table 2.1: AI Roles in Roboadvisors . 25
i. Conclusions . 26
3.2 Chatbots . 27
3.2.1 AI Drivers . 27
Case Study: AMEX Bot . 27
3.2.2 Regulatory Environment . 28
i. Complaints - US . 28
ii. Complaints - EU . 28
3.2.3 Opportunities & Recommendations . 29
3.3 Lending . 29
3.3.1 AI Drivers . 30
Case Study: Upstart . 30
3.3.2 Regulatory Environment . 31
i. US . 31
ii. EU . 31
3.3.3 Opportunities & Recommendations . 32
3.4 Insurtech . 33
3.4.1 AI Drivers . 33
Case Study: Tractable . 34
3.4.2 Regulatory Environment . 34
i. US . 34
ii. UK . 35
3.4.3 Opportunities & Recommendations. 35
3.5 Regtech & Fraud . 36
3.5.1 AI Drivers . 36
i. AML (Anti Money-Laundering) & Fraud . 36
ii. KYC (Know Your Customer) . 36
Case Study: Feedzai . 37
3.5.2 Regulatory Environment . 37
i. US . 37
ii. UK . 38
iii. Global . 38
3.5.3 Opportunities & Recommendations. 38

4. AI in Fintech: Vendor Analysis

4.1 Introduction . 41
4.2 Juniper Leaderboard . 41
Table 3.1: AI Fintech Vendor Capability Assessment Criteria . 42
4.3 Leaderboard Scoring Results . 43
Table 3.2: AI Fintech Leaderboard. 43
Figure 3.3: AI Fintech Leaderboard . 44
4.3.1 Vendor Groupings . 45
i. Established Leaders . 45
ii. Leading Challengers. 45
iii. Disruptors & Emulators . 45
4.4 AI in Fintech Movers & Shakers . 47
4.5 Vendor Profiles . 49
4.5.1 ComplyAdvantage . 49
i. Corporate . 49
ii. Geographic Spread . 49
iii. Key Clients & Strategic Partnerships . 49
iv. High Level View of Offering . 50
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 50
4.5.2 Elliptic . 50
i. Corporate . 50
ii. Geographic Spread . 50
iii. Key Clients & Strategic Partnerships . 50
iv. High Level View of Offerings . 51
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 51
4.5.3 Kabbage . 52
i. Corporate . 52
ii. Geographic Spread . 52
iii. Key Clients & Strategic Partnerships . 52
iv. High Level View of Offerings . 52
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 53
4.5.4 Lemonade . 53
i. Corporate . 53
ii. Geographic Spread . 53
iii. Key Clients & Strategic Partnerships . 53
iv. High Level View of Offerings . 53
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 54
4.5.5 Onfido . 54
i. Corporate . 54
ii. Geographic Spread . 55
iii. Key Clients & Strategic Partnerships . 55
iv. High Level View of Offerings . 55
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 55
4.5.6 Scalable Capital . 56
i. Corporate . 56
ii. Geographic Spread . 56
iii. Key Clients & Strategic Partnerships . 56
iv. High Level View of Offerings . 56
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 56
4.5.7 Sentient Technologies. 57
i. Corporate . 57
ii. Geographic Spread . 57
iii. Key Clients & Strategic Partnerships . 57
iv. High Level View of Offerings . 57
v. Juniper’s View: Key Strengths & Development Opportunities . 58
4.5.8 The Floow . 58
i. Corporate . 58
ii. Geographic Spread . 58
iii. Key Clients & Strategic Partnerships . 58
iv. High Level View of Offerings . 59
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 59
4.5.9 Tractable . 59
i. Corporate . 59
ii. Geographic Spread . 60
iii. Key Clients & Strategic Partnerships . 60
iv. High Level View of Offerings . 60
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 60
4.5.10 Upstart . 61
i. Corporate . 61
ii. Geographic Spread . 61
iii. Key Clients & Strategic Partnerships . 61
iv. High Level View of Offerings . 61
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 62
4.5.11 Wealthfront . 62
i. Corporate . 62
ii. Geographic Spread . 62
iii. Key Clients & Strategic Partnerships . 62
iv. High Level View of Offerings . 62
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 63
4.5.12 ZestFinance . 63
i. Corporate . 63
ii. Geographic Spread . 63
iii. Key Clients & Strategic Partnerships . 63
iv. High Level View of Offerings . 63
v. Juniper’s View: Key Strengths & Development Opportunities . 64

5. AI in Fintech: Market Forecasts

5.1 Introduction . 66
5.2 Assumptions & Methodology . 66
Figure 4.1: Roboadvisor Methodology . 68
Figure 4.2: Consumer Lending Methodology . 69
Figure 4.3: Insurtech Methodology. 70
Figure 4.4: Regtech Methodology . 71
5.3 Roboadvisors . 72
5.3.1 Assets Under Management . 72
Figure & Table 4.5: Total Roboadvisor AUM ($bn), Split by 8 Key Regions, 2017-2022 . 72
5.3.2 Platform Revenues . 73
Figure & Table 4.6: Roboadvisor Service Provider Platform Revenues ($m), Split by 8 Key Regions 2017-2022. 73
5.4 Consumer Lending . 74
5.4.1 Unsecured Loans Origination. 74
Figure & Table 4.7: Total Value of Unsecured Consumer Loans Originated ($m), Split by 8 Key Regions 2017-2022 . 74
5.4.2 Platform Revenues . 75
Figure & Table 4.8: Service Provider Platform Revenues from Unsecured Consumer Loans ($m), Split by 8 Key Regions 2017-2022 . 75
5.5 AI Insurtech . 76
Figure & Table 4.9: Total Insurtech Premiums Generated by AI Systems ($m) Split by 8 Key Regions 2017-2022 . 76
5.6 AI Regtech: KYC . 77
Figure & Table 4.10: Total Cost Saving on KYC Checks Utilising AI Systems ($m), Split by 8 Key Regions 2017-2022 . 77

 

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