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 2019-2023年
AI in Fintech
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従来型の手作業中心で煩雑な金融サービスに与えられる影響・破壊を分析しています。
分析は下記のサービス... もっと見る
「Deep Dive Strategy & Competition」「Deep Dive Data & Forecasting」の部分購入が可能です。詳しくはお問い合わせ下さい。
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従来型の手作業中心で煩雑な金融サービスに与えられる影響・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
主な掲載内容 ※ 目次より抜粋
-
Deep Dive Strategy & Competition
-
フィンテックにおけるAI:イントロダクション
-
AI: フィンテックの破壊/ディスラプション
-
フィンテックにおけるAI: ステークホルダー分析とリーダーボード
-
Deep Dive Data & Forecasting
-
フィンテックにおけるAIのイントロダクション
-
ロボアドバイザーの市場規模
-
AIの消費者融資市場予測
-
AIのビジネス融資市場予測
-
AIのインシュアテック市場予測
-
AIのレグテック市場予測
-
チャットボット市場予測
OverView
Juniper’s latest AI in Fintech research highlights the ways in which the traditional financial industry is being disrupted through the use of AI (Artificial Intelligence) to deliver services in a manner that upends highly manual, cumbersome services.
Juniper’s incisive research provides unique insights into the rapidly expanding market; examining key regulatory forces across regions, service provider advantages and challenges, as well as a set of key recommendations and strategic opportunities.
The analysis covers key industry service segments, including:
-
Roboadvisors
-
Chatbots
-
Lending
-
Insurance
-
Regulatory Compliance & Fraud
This research suite includes:
-
Deep Dive Strategy & Competition (PDF)
-
5-Year Deep Dive Data & Forecasting (PDF & Excel)
-
Executive Summary & Core Findings (PDF)
-
12 months' access to harvest online data platform
-
Sector Dynamics: AI drivers, regional regulatory landscape analysis, strategic opportunities and recommendations for:
-
Roboadvisors
-
Chatbots
-
Lending
-
Insurance
-
Regulatory Compliance & Fraud
-
Interviews: Leading AI in Fintech vendors across the value chain interviewed, including:
-
Feedzai
-
Juvo
-
Kabbage
-
Kasisto
-
Mimiro
-
ZestFinance
-
Juniper Leaderboard: Key player capability and capacity assessment for 15 emerging AI in Fintech service providers.
-
AI in Fintech Disruptors & Challengers Quadrant: Analyses 15 of the emerging and innovative technology companies with the potential to disrupt key fintech markets.
-
Benchmark Industry Forecasts: Market segment forecasts for key AI in Fintech verticals, including:
-
Roboadvisors
-
Banking Chatbots
-
Consumer & Business Unsecured Lending
-
AI Insurtech
-
AI Regulatory Compliance & Fraud
-
How is the regulatory landscape expected to impact the development of AI-driven services in fintech?
-
What are the key regional forces influencing the development of the AI in Fintech market?
-
How are vendors dealing with AI challenges, such as the ‘black box’ issue?
-
What is the size of the revenue opportunity for AI in Fintech?
-
Who are the leading vendors in the AI in Fintech space and what differentiates them?
Interviewed: Feedzai, Juvo, Kabbage, Kasisto, Mimiro, ZestFinance.
Profiled: ABC Fintech, Feedzai, Habito, Kabbage, Kasisto, Lemonade, Mimiro, NetGuardians, OakNorth, Onfido, Scalable Capital, Tractable, Upstart, Wealthfront, ZestFinance.
Case Studied: Hanzo, Juvo, LendUp, Qplum,
Included in Disruptors & Challengers Quadrant: Aire, Arkera, Axyon AI, CashShield, Clinc, Dataiku, Elliptic, Featurespace, Finn AI, Pagaya Investments, Parashift, Petal, The Floow, Zesty.ai.
Mentioned: 37Games, Abacus, Acorns, Ada Support, AdNovum, Aegon, Ageas, AIG, Alibaba, Allianz, Altea Business Services, Amazon, Analyst.ai, Ant Financial, Anthem, Ascensus, ATB Financial, Atom Bank, Avaloq, BaFin (Bundesanstalt für Finanzdienstleistungsaufsicht), Baidu, Bambu, Bank of America, Banpro, Barclays, Basis AI, BBC, BehavioSec, Betterment, BGL BNP Paribas, Bitstamp, Blue Turtle Technologies, BMO, BuzzCompany.com, Cashcow, Charles Schwab, Charlie, Chase Bank, Chip, Citi Group, Cleo, Coinbase, Couchsurfing, Credorax, Cuscal, DBS, Deloitte, Direct Line Group, eBay, Egress, EMI, Etsy, European Space Agency, Experian, EY, FCA (Financial Conduct Authority), Fidelidade, First Ontario Credit Union, FirstData, Flinks, Fraugster, Fukoku Mutual Life Insurance, GIC, Goldman Sachs, Google, Green Flag, HDI, HSBC, IBM, ING, Intuit, Isbank, JPMorgan, JUMO, K2, Lending Club, Liberty Mutual, Lloyd’s of London, Lloyds Banking Group, Magnetis, MarketInvoice, MAS (Monetary Authority of Singapore), Mastercard, Microsoft, MindBridge, Mitchell, Moneythor, Multex.com, N26, NatWest, North Face, NSPCC, Nubank, Oak HC/FT, OCC (Office of the Comptroller of Currency), Ola, Orbium, Oristeba, Oxford Development Abroad, PayPal, Ping An, Plymouth Rock Assurance, Prestige Financial Services, PWC, Quantemplate, QuickBooks, RAND Corporation, Rapid Ratings International, Razer, Redfin, Renault Nissan Mitsubishi, Rubique, Sage, Sagesure Insurance Managers, Santander, SAP, Scotiabank, SEC (Securities & Exchange Commission), Sherpa, SoftBank, SpeechCycle Corp, Square, Standard Chartered, Stripe, Sunlight Financial, Swisscom, Synchronoss Technologies, Tango Card, TD Bank, Temenos, Tencent, The Student Room, Ticketmaster, T-Mobile, TruNarrative, Twitter, UberEATS, UBS, Union Pacific, UnitedHealthcare, Valantic, Venmo, Visa, Vodafone, Wag, Wells Fargo, Xero, Xiaomi, Xiaozhu, XL Catlin, Yandex, YayPay, ZestMoney, Zipcar.
Data & Interactive Forecast
Juniper’s latest AI in Fintech forecast suite includes:
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Regional splits for 8 key regions, as well as country level data splits for:
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Brazil
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Canada
-
China
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Denmark
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France
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India
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Germany
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Japan
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Mexico
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Norway
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Portugal
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Spain
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Sweden
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UK
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US
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Roboadvisor forecasts, including total assets under management and revenues for platform providers.
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Banking chatbot forecasts, including total number of successful interactions, total cost savings for consumers and total cost savings for banks.
-
Consumer & business unsecured AI lending forecasts, including total number of loans originated using AI, total value of AI-underwritten lending and revenues for platform providers.
-
AI-powered insurtech forecasts, including total value of premiums in the motor, life, property and health segments underwritten by AI, as well as total cost savings from assessing claims with AI.
-
AI-powered regtech forecasts, including the total cost savings from employed AI for KYC (Know Your Customer) checks.
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Access to the full set of forecast data of 40 tables and over 4,950 datapoints.
-
Interactive Excel Scenario tool allowing users the ability to manipulate Juniper’s data for 6 different metrics.
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, India, Japan, Mexico, Norway, Portugal, Spain, Sweden, UK, USA
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目次
Table of Contents
1. Deep Dive Strategy & Competition
1. AI in Fintech: Introduction
1.1 Introduction . 7
Figure 1.1: AI Skills in Fintech . 7
Figure 1.2: Types of AI . 8
1.2 Investment Landscape . 8
Table 1.3: Selected AI in Fintech Investments, 2018-19 . 9
1.3 Investment/Start-Up Activity by Region . 10
1.3.1 North America . 10
i. Investment/Development Activity . 10
ii. Juniper’s View: Future Prospects . 10
1.3.2 Latin America . 11
i. Investment/Development Activity . 11
ii. Juniper’s View: Future Prospects . 11
Case Study: Juvo . 12
1.3.3 West Europe . 12
i. Investment/Development Activity . 12
ii. Juniper’s View: Future Prospects . 13
1.3.4 Central & East Europe . 13
i. Investment/Development Activity . 13
ii. Juniper’s View: Future Prospects . 13
1.3.5 Far East & China . 14
i. Investment/Development Activity . 14
ii. Juniper’s View: Future Prospects . 14
1.3.6 Indian Subcontinent . 14
i. Investment/Development Activity . 14
ii. Juniper’s View: Future Prospects . 15
1.3.7 Rest of Asia Pacific . 15
i. Investment/Development Activity . 15
ii. Juniper’s View: Future Prospects . 15
1.3.8 Africa & Middle East . 16
i. Investment/Development Activity . 16
ii. Juniper’s View: Future Prospects . 16
2. AI: Disruption in Fintech
2.1 Disruptive AI in Fintech ? Impact Assessment . 18
2.1.1 Summary . 18
Table 2.1: AI in Fintech Impact Assessment. 18
Table 2.2: AI in Fintech Impact Assessment Heatmap Key . 18
2.1.2 AI in Fintech Impact Assessment Methodology . 19
Table 2.3: Impact Assessment Methodology . 19
2.2 Growth Phase Analysis for AI Use in Fintech . 20
Figure 2.4: Juniper Phased Evolution Model for AI Use in Fintech . 20
2.3 AI in Fintech - Segment Analysis . 21
2.3.1 Roboadvisors . 21
i. AI Drivers . 21
Table 2.5: AI Role Classification in Roboadvisors . 21
ii. Regulatory Environment in Key Markets . 22
iii. Cost Savings . 23
iv. Current Deployment Level. 24
Case Study: Qplum . 24
v. Juniper’s View: Future Outlook . 25
Figure 2.6: Roboadvisor Assets Under Management, Hybrid vs Fully
Autonomous, 2018 . 26
2.3.2 Chatbots . 26
i. AI Drivers . 26
ii. Regulatory Environment in Key Markets . 26
iii. Cost Savings . 27
iv. Current Deployment Level. 27
v. Juniper’s View: Future Outlook . 27
Figure 2.7: Number of Successful Banking Chatbot Interactions (m), 2018 . 28
2.3.3 Lending . 29
i. AI Drivers . 29
Case Study: LendUp . 30
ii. Regulatory Environment in Key Markets . 30
iii. EU . 31
iv. Cost Savings . 31
v. Current Deployment Level . 32
Figure 2.8: EU28 Survey, Access to Finance as a Concern of SMEs, Mean Rating
Between 1-10 (10 Highest, 1 Lowest), Selected Countries . 32
vi. Juniper’s View: Future Outlook. 32
2.3.4 Insurtech . 33
Figure 2.9: AI in Insurance Applications . 34
i. AI Drivers . 34
Figure 2.10: Combined Ratio at 4 Leading US Insurers, (%), All Lines, 2013-
2017 . 35
Case Study: Hanzo . 36
ii. Regulatory Environment in Key Markets . 36
iii. Current Deployment Level . 37
iv. Juniper’s View: Future Outlook . 37
2.3.5 Regtech & Fraud . 37
i. AI Drivers . 37
ii. AI for Transaction Monitoring . 38
iii. AI Behavioural Monitoring . 39
iv. AI for AML & KYC Checks . 39
v. AI as a Regulation Compliance Tool. 40
vi. Regulatory Environment in Key Markets . 40
Figure 2.11: US Regulatory Framework . 40
Figure 2.12: Regulatory Fines Imposed by the FCA, ($m) 2014-2018 . 42
vii. Cost Savings . 42
Figure 2.13: Number of Regulations Applicable per Industry, Selected NAIC
Sectors, US, 2017 . 42
viii. Current Deployment Level . 43
ix. Juniper’s View: Future Outlook . 43
2.4 AI in Fintech: Disruptors & Challengers Quadrant . 45
2.4.1 Introduction . 45
Figure 2.14: Juniper Disruptors & Challengers Quadrant ? AI in Fintech . 45
2.4.2 Landscape Analysis . 46
i. Disruptors . 46
ii. Nascent . 46
iii. Catalysts . 47
iv. Embryonic Stakeholders . 49
3. AI in Fintech: Stakeholder Analysis & Leaderboard
3.1 Vendor Analysis & Leaderboard . 52
3.1.1 Introduction . 52
3.1.2 Stakeholder Assessment Criteria. 52
Table 3.1: AI in Fintech Player Capability Criteria . 53
Figure 3.2: AI in Fintech Platform Vendor Leaderboard . 54
Table 3.3 AI in Fintech Leaderboard Scoring . 55
3.1.3 Vendor Groupings . 56
i. Established Leaders . 56
ii. Leading Challengers . 56
iii. Disruptors & Emulators . 57
3.1.4 Limitations & Interpretation . 58
3.2 AI in Fintech Movers & Shakers . 59
3.3 Vendor Profiles . 61
3.3.1 ABC Fintech . 61
i. Corporate . 61
Table 3.4: Key Investors & Funding Rounds for ABC Fintech . 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
3.3.2 Feedzai . 62
i. Corporate . 62
Table 3.5: Feedzai Funding Rounds . 62
ii. Geographic Spread . 62
iii. Key Clients & Strategic Partnerships . 63
iv. High Level View of Offerings . 63
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 63
3.3.3 Habito . 64
i. Corporate . 64
Table 3.6: Habito Funding Rounds . 64
ii. Geographic Spread . 64
iii. Key Clients & Strategic Partnerships . 64
iv. High Level View of Offerings . 64
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 65
3.3.4 Kabbage . 65
i. Corporate . 65
ii. Geographic Spread . 66
iii. Key Clients & Strategic Partnerships . 66
iv. High Level View of Offerings . 66
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 66
3.3.5 Kasisto . 67
i. Corporate . 67
Table 3.7: Kasisto Funding Rounds . 67
ii. Geographic Spread . 67
iii. Key Clients & Strategic Partnerships . 67
iv. High Level View of Offerings . 68
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 68
3.3.6 Lemonade . 68
i. Corporate . 68
ii. Geographic Spread . 69
iii. Key Clients & Strategic Partnerships . 69
iv. High Level View of Offerings . 69
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 69
3.3.7 Mimiro . 70
i. Corporate . 70
Table 3.8: Mimiro Funding Rounds . 70
ii. Geographic Spread . 70
iii. Key Clients & Strategic Partnerships . 70
iv. High Level View of Offering . 71
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 71
3.3.8 NetGuardians . 72
i. Corporate . 72
Table 3.9: NetGuardians Funding Rounds . 72
ii. Geographic Spread . 72
iii. Key Clients & Strategic Partnerships . 72
iv. High Level View of Offerings . 72
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 73
3.3.9 OakNorth. 73
i. Corporate . 73
Table 3.10: OakNorth Funding Rounds . 73
ii. Geographic Spread . 74
iii. Key Clients & Strategic Partnerships . 74
iv. High Level View of Offerings . 74
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 74
3.3.10 Onfido . 75
i. Corporate . 75
Table 3.11: Onfido Funding Rounds . 75
ii. Geographic Spread . 75
iii. Key Clients & Strategic Partnerships . 75
iv. High Level View of Offerings . 76
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 76
3.3.11 Scalable Capital . 76
i. Corporate . 76
Table 3.12: Scalable Capital Funding Rounds . 77
ii. Geographic Spread . 77
iii. Key Clients & Strategic Partnerships . 77
iv. High Level View of Offerings . 77
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 77
3.3.12 Tractable . 78
i. Corporate . 78
Table 3.13: Tractable Funding Rounds . 78
ii. Geographic Spread . 78
iii. Key Clients & Strategic Partnerships . 78
iv. High Level View of Offerings . 78
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 79
3.3.13 Upstart . 79
i. Corporate . 79
Table 3.14: Upstart Funding Rounds . 79
ii. Geographic Spread . 80
iii. Key Clients & Strategic Partnerships . 80
iv. High Level View of Offerings . 80
Figure 3.15: Upstart Bad Debt Performance versus Selected Alternative Lenders,
By Weighted Average FICO Score . 80
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 81
3.3.14 Wealthfront . 81
i. Corporate . 81
Table 3.16: Wealthfront Funding Rounds . 81
ii. Geographic Spread . 81
iii. Key Clients & Strategic Partnerships . 82
iv. High Level View of Offerings . 82
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 82
3.3.15 ZestFinance . 83
i. Corporate . 83
Table 3.17: ZestFinance Funding Rounds . 83
ii. Geographic Spread . 83
iii. Key Clients & Strategic Partnerships . 83
iv. High Level View of Offerings . 83
v. Juniper’s View: Key Strengths & Development Opportunities . 84
2. Deep Dive Data & Forecasting
1. Introduction to AI in Fintech
1.1 Introduction . 4
Figure 1.1: AI Areas of Disruption . 4
2. Roboadvisors Market Forecasts
2.1 Introduction . 6
Table 2.1: AI Role Classification in Roboadvisors . 6
2.1.1 Methodology & Assumptions . 7
Figure 2.2: Roboadvisors Forecast Methodology . 8
2.2 Roboadvisors . 9
2.2.1 AUM (Assets Under Management) . 9
Figure & Table 2.3: Roboadvisors Assets under Management ($bn), Split by 8
Key Regions 2018-2023 . 9
2.2.2 Roboadvisor Platform Revenues . 10
Figure & Table 2.4: Roboadvisor Platform Revenues ($m), Split by 8 Key Regions
2018-2023 . 10
3. AI Consumer Lending Market Forecasts
3.1 Introduction . 12
3.2 Assumptions & Methodology . 12
Figure 3.1: Consumer Lending Forecast Methodology . 13
3.3 Consumer Lending . 14
3.3.1 Unsecured Loans Origination. 14
Figure & Table 3.2: Total Value of Unsecured Consumer Loans Originated ($m),
Split by 8 Key Regions 2018-2023 . 14
3.3.2 Platform Revenues . 15
Figure & Table 3.3: Service Provider Platform Revenues from Unsecured
Consumer Loans ($m), Split by 8 Key Regions 2018-2023 . 15
4. AI Business Lending Market Forecasts
4.1 Introduction . 17
4.2 Assumptions & Methodology . 17
Figure 4.1: Business Lending Forecast Methodology . 18
4.3 Business Lending . 19
4.3.1 Unsecured Loans Origination . 19
Figure & Table 4.2: Total Annual Machine Learning Aided Unsecured Business
Loan Value ($m), Split by 8 Key Regions 2018-2023 . 19
4.3.2 Platform Revenues . 20
Figure & Table 4.3: Annual Machine Learning Aided Unsecured Business Lending
Platform Revenues ($m), Split by 8 Key Regions 2018-2023 . 20
5. AI Insurtech Market Forecasts
5.1 Introduction . 22
5.2 Methodology & Assumptions . 22
Figure 5.1: Insurtech Forecast Methodology . 23
5.3 AI Insurtech Forecasts . 24
5.3.1 AI Premiums Generated . 24
Figure & Table 5.2: Total Value of Motor, Home, Life & Health Insurance
Premiums Underwritten by AI Underwriting Systems ($m) Split by 8 Key Regions
2018-2023 . 24
5.3.2 AI Claims Gross Cost Savings . 25
Figure & Table 5.3: Total Gross Cost Saving Assessing Motor, Home, Life &
Health Insurance Claims via AI ($m) Split by 8 Key Regions 2018-2023 . 25
Table 5.4: Total Gross Cost Saving Assessing Motor, Home, Life & Health
Insurance Claims via AI ($m) Split by Line 2018-2023 . 25
6. AI Regtech Market Forecasts
6.1 Introduction . 27
6.2 Methodology & Assumptions . 27
Figure 6.1: KYC Validation Forecast Methodology . 28
6.3 AI Regtech KYC Forecasts . 29
6.3.1 Cost Savings in Banking . 29
Figure & Table 6.2: Total Cost Saving on KYC Checks for Banking Utilising AI
Systems ($m), Split by 8 Key Regions 2018-2023 . 29
6.3.2 Cost Savings in Property Sales . 30
Figure & Table 6.3: Total Cost Saving on KYC Checks for Property Sales Utilising
AI Systems ($m), Split by 8 Key Regions 2018-2023 . 30
7. Chatbots Market Forecasts
7.1 Introduction . 32
7.2 Assumptions & Methodology . 32
Figure 7.1: Methodology for Messaging Application Chatbots . 33
Figure 7.2: Methodology for Discrete Application Chatbots . 34
Figure 7.3: Methodology for Web-based Chatbots . 35
7.3 Chatbot Banking Forecast . 36
7.3.1 Successful Chatbot Interactions . 36
Figure & Table 7.4: Number of Successful Banking Chatbot Interactions (m) Split
by 8 Key Regions 2018-2023. 36
7.3.2 Chatbot Cost Savings for Business . 37
Figure & Table 7.5: Total Banking Chatbots Cost Savings for Businesses ($m)
Split by 8 Key Regions 2018-2023 . 37
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Summary
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従来型の手作業中心で煩雑な金融サービスに与えられる影響・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
主な掲載内容 ※ 目次より抜粋
-
Deep Dive Strategy & Competition
-
フィンテックにおけるAI:イントロダクション
-
AI: フィンテックの破壊/ディスラプション
-
フィンテックにおけるAI: ステークホルダー分析とリーダーボード
-
Deep Dive Data & Forecasting
-
フィンテックにおけるAIのイントロダクション
-
ロボアドバイザーの市場規模
-
AIの消費者融資市場予測
-
AIのビジネス融資市場予測
-
AIのインシュアテック市場予測
-
AIのレグテック市場予測
-
チャットボット市場予測
OverView
Juniper’s latest AI in Fintech research highlights the ways in which the traditional financial industry is being disrupted through the use of AI (Artificial Intelligence) to deliver services in a manner that upends highly manual, cumbersome services.
Juniper’s incisive research provides unique insights into the rapidly expanding market; examining key regulatory forces across regions, service provider advantages and challenges, as well as a set of key recommendations and strategic opportunities.
The analysis covers key industry service segments, including:
-
Roboadvisors
-
Chatbots
-
Lending
-
Insurance
-
Regulatory Compliance & Fraud
This research suite includes:
-
Deep Dive Strategy & Competition (PDF)
-
5-Year Deep Dive Data & Forecasting (PDF & Excel)
-
Executive Summary & Core Findings (PDF)
-
12 months' access to harvest online data platform
-
Sector Dynamics: AI drivers, regional regulatory landscape analysis, strategic opportunities and recommendations for:
-
Roboadvisors
-
Chatbots
-
Lending
-
Insurance
-
Regulatory Compliance & Fraud
-
Interviews: Leading AI in Fintech vendors across the value chain interviewed, including:
-
Feedzai
-
Juvo
-
Kabbage
-
Kasisto
-
Mimiro
-
ZestFinance
-
Juniper Leaderboard: Key player capability and capacity assessment for 15 emerging AI in Fintech service providers.
-
AI in Fintech Disruptors & Challengers Quadrant: Analyses 15 of the emerging and innovative technology companies with the potential to disrupt key fintech markets.
-
Benchmark Industry Forecasts: Market segment forecasts for key AI in Fintech verticals, including:
-
Roboadvisors
-
Banking Chatbots
-
Consumer & Business Unsecured Lending
-
AI Insurtech
-
AI Regulatory Compliance & Fraud
-
How is the regulatory landscape expected to impact the development of AI-driven services in fintech?
-
What are the key regional forces influencing the development of the AI in Fintech market?
-
How are vendors dealing with AI challenges, such as the ‘black box’ issue?
-
What is the size of the revenue opportunity for AI in Fintech?
-
Who are the leading vendors in the AI in Fintech space and what differentiates them?
Interviewed: Feedzai, Juvo, Kabbage, Kasisto, Mimiro, ZestFinance.
Profiled: ABC Fintech, Feedzai, Habito, Kabbage, Kasisto, Lemonade, Mimiro, NetGuardians, OakNorth, Onfido, Scalable Capital, Tractable, Upstart, Wealthfront, ZestFinance.
Case Studied: Hanzo, Juvo, LendUp, Qplum,
Included in Disruptors & Challengers Quadrant: Aire, Arkera, Axyon AI, CashShield, Clinc, Dataiku, Elliptic, Featurespace, Finn AI, Pagaya Investments, Parashift, Petal, The Floow, Zesty.ai.
Mentioned: 37Games, Abacus, Acorns, Ada Support, AdNovum, Aegon, Ageas, AIG, Alibaba, Allianz, Altea Business Services, Amazon, Analyst.ai, Ant Financial, Anthem, Ascensus, ATB Financial, Atom Bank, Avaloq, BaFin (Bundesanstalt für Finanzdienstleistungsaufsicht), Baidu, Bambu, Bank of America, Banpro, Barclays, Basis AI, BBC, BehavioSec, Betterment, BGL BNP Paribas, Bitstamp, Blue Turtle Technologies, BMO, BuzzCompany.com, Cashcow, Charles Schwab, Charlie, Chase Bank, Chip, Citi Group, Cleo, Coinbase, Couchsurfing, Credorax, Cuscal, DBS, Deloitte, Direct Line Group, eBay, Egress, EMI, Etsy, European Space Agency, Experian, EY, FCA (Financial Conduct Authority), Fidelidade, First Ontario Credit Union, FirstData, Flinks, Fraugster, Fukoku Mutual Life Insurance, GIC, Goldman Sachs, Google, Green Flag, HDI, HSBC, IBM, ING, Intuit, Isbank, JPMorgan, JUMO, K2, Lending Club, Liberty Mutual, Lloyd’s of London, Lloyds Banking Group, Magnetis, MarketInvoice, MAS (Monetary Authority of Singapore), Mastercard, Microsoft, MindBridge, Mitchell, Moneythor, Multex.com, N26, NatWest, North Face, NSPCC, Nubank, Oak HC/FT, OCC (Office of the Comptroller of Currency), Ola, Orbium, Oristeba, Oxford Development Abroad, PayPal, Ping An, Plymouth Rock Assurance, Prestige Financial Services, PWC, Quantemplate, QuickBooks, RAND Corporation, Rapid Ratings International, Razer, Redfin, Renault Nissan Mitsubishi, Rubique, Sage, Sagesure Insurance Managers, Santander, SAP, Scotiabank, SEC (Securities & Exchange Commission), Sherpa, SoftBank, SpeechCycle Corp, Square, Standard Chartered, Stripe, Sunlight Financial, Swisscom, Synchronoss Technologies, Tango Card, TD Bank, Temenos, Tencent, The Student Room, Ticketmaster, T-Mobile, TruNarrative, Twitter, UberEATS, UBS, Union Pacific, UnitedHealthcare, Valantic, Venmo, Visa, Vodafone, Wag, Wells Fargo, Xero, Xiaomi, Xiaozhu, XL Catlin, Yandex, YayPay, ZestMoney, Zipcar.
Data & Interactive Forecast
Juniper’s latest AI in Fintech forecast suite includes:
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Regional splits for 8 key regions, as well as country level data splits for:
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Brazil
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Canada
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China
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Denmark
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France
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India
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Germany
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Japan
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Mexico
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Norway
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Portugal
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Spain
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Sweden
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UK
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US
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Roboadvisor forecasts, including total assets under management and revenues for platform providers.
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Banking chatbot forecasts, including total number of successful interactions, total cost savings for consumers and total cost savings for banks.
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Consumer & business unsecured AI lending forecasts, including total number of loans originated using AI, total value of AI-underwritten lending and revenues for platform providers.
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AI-powered insurtech forecasts, including total value of premiums in the motor, life, property and health segments underwritten by AI, as well as total cost savings from assessing claims with AI.
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AI-powered regtech forecasts, including the total cost savings from employed AI for KYC (Know Your Customer) checks.
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Access to the full set of forecast data of 40 tables and over 4,950 datapoints.
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Interactive Excel Scenario tool allowing users the ability to manipulate Juniper’s data for 6 different metrics.
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, India, Japan, Mexico, Norway, Portugal, Spain, Sweden, UK, USA
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Table of Contents
Table of Contents
1. Deep Dive Strategy & Competition
1. AI in Fintech: Introduction
1.1 Introduction . 7
Figure 1.1: AI Skills in Fintech . 7
Figure 1.2: Types of AI . 8
1.2 Investment Landscape . 8
Table 1.3: Selected AI in Fintech Investments, 2018-19 . 9
1.3 Investment/Start-Up Activity by Region . 10
1.3.1 North America . 10
i. Investment/Development Activity . 10
ii. Juniper’s View: Future Prospects . 10
1.3.2 Latin America . 11
i. Investment/Development Activity . 11
ii. Juniper’s View: Future Prospects . 11
Case Study: Juvo . 12
1.3.3 West Europe . 12
i. Investment/Development Activity . 12
ii. Juniper’s View: Future Prospects . 13
1.3.4 Central & East Europe . 13
i. Investment/Development Activity . 13
ii. Juniper’s View: Future Prospects . 13
1.3.5 Far East & China . 14
i. Investment/Development Activity . 14
ii. Juniper’s View: Future Prospects . 14
1.3.6 Indian Subcontinent . 14
i. Investment/Development Activity . 14
ii. Juniper’s View: Future Prospects . 15
1.3.7 Rest of Asia Pacific . 15
i. Investment/Development Activity . 15
ii. Juniper’s View: Future Prospects . 15
1.3.8 Africa & Middle East . 16
i. Investment/Development Activity . 16
ii. Juniper’s View: Future Prospects . 16
2. AI: Disruption in Fintech
2.1 Disruptive AI in Fintech ? Impact Assessment . 18
2.1.1 Summary . 18
Table 2.1: AI in Fintech Impact Assessment. 18
Table 2.2: AI in Fintech Impact Assessment Heatmap Key . 18
2.1.2 AI in Fintech Impact Assessment Methodology . 19
Table 2.3: Impact Assessment Methodology . 19
2.2 Growth Phase Analysis for AI Use in Fintech . 20
Figure 2.4: Juniper Phased Evolution Model for AI Use in Fintech . 20
2.3 AI in Fintech - Segment Analysis . 21
2.3.1 Roboadvisors . 21
i. AI Drivers . 21
Table 2.5: AI Role Classification in Roboadvisors . 21
ii. Regulatory Environment in Key Markets . 22
iii. Cost Savings . 23
iv. Current Deployment Level. 24
Case Study: Qplum . 24
v. Juniper’s View: Future Outlook . 25
Figure 2.6: Roboadvisor Assets Under Management, Hybrid vs Fully
Autonomous, 2018 . 26
2.3.2 Chatbots . 26
i. AI Drivers . 26
ii. Regulatory Environment in Key Markets . 26
iii. Cost Savings . 27
iv. Current Deployment Level. 27
v. Juniper’s View: Future Outlook . 27
Figure 2.7: Number of Successful Banking Chatbot Interactions (m), 2018 . 28
2.3.3 Lending . 29
i. AI Drivers . 29
Case Study: LendUp . 30
ii. Regulatory Environment in Key Markets . 30
iii. EU . 31
iv. Cost Savings . 31
v. Current Deployment Level . 32
Figure 2.8: EU28 Survey, Access to Finance as a Concern of SMEs, Mean Rating
Between 1-10 (10 Highest, 1 Lowest), Selected Countries . 32
vi. Juniper’s View: Future Outlook. 32
2.3.4 Insurtech . 33
Figure 2.9: AI in Insurance Applications . 34
i. AI Drivers . 34
Figure 2.10: Combined Ratio at 4 Leading US Insurers, (%), All Lines, 2013-
2017 . 35
Case Study: Hanzo . 36
ii. Regulatory Environment in Key Markets . 36
iii. Current Deployment Level . 37
iv. Juniper’s View: Future Outlook . 37
2.3.5 Regtech & Fraud . 37
i. AI Drivers . 37
ii. AI for Transaction Monitoring . 38
iii. AI Behavioural Monitoring . 39
iv. AI for AML & KYC Checks . 39
v. AI as a Regulation Compliance Tool. 40
vi. Regulatory Environment in Key Markets . 40
Figure 2.11: US Regulatory Framework . 40
Figure 2.12: Regulatory Fines Imposed by the FCA, ($m) 2014-2018 . 42
vii. Cost Savings . 42
Figure 2.13: Number of Regulations Applicable per Industry, Selected NAIC
Sectors, US, 2017 . 42
viii. Current Deployment Level . 43
ix. Juniper’s View: Future Outlook . 43
2.4 AI in Fintech: Disruptors & Challengers Quadrant . 45
2.4.1 Introduction . 45
Figure 2.14: Juniper Disruptors & Challengers Quadrant ? AI in Fintech . 45
2.4.2 Landscape Analysis . 46
i. Disruptors . 46
ii. Nascent . 46
iii. Catalysts . 47
iv. Embryonic Stakeholders . 49
3. AI in Fintech: Stakeholder Analysis & Leaderboard
3.1 Vendor Analysis & Leaderboard . 52
3.1.1 Introduction . 52
3.1.2 Stakeholder Assessment Criteria. 52
Table 3.1: AI in Fintech Player Capability Criteria . 53
Figure 3.2: AI in Fintech Platform Vendor Leaderboard . 54
Table 3.3 AI in Fintech Leaderboard Scoring . 55
3.1.3 Vendor Groupings . 56
i. Established Leaders . 56
ii. Leading Challengers . 56
iii. Disruptors & Emulators . 57
3.1.4 Limitations & Interpretation . 58
3.2 AI in Fintech Movers & Shakers . 59
3.3 Vendor Profiles . 61
3.3.1 ABC Fintech . 61
i. Corporate . 61
Table 3.4: Key Investors & Funding Rounds for ABC Fintech . 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
3.3.2 Feedzai . 62
i. Corporate . 62
Table 3.5: Feedzai Funding Rounds . 62
ii. Geographic Spread . 62
iii. Key Clients & Strategic Partnerships . 63
iv. High Level View of Offerings . 63
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 63
3.3.3 Habito . 64
i. Corporate . 64
Table 3.6: Habito Funding Rounds . 64
ii. Geographic Spread . 64
iii. Key Clients & Strategic Partnerships . 64
iv. High Level View of Offerings . 64
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 65
3.3.4 Kabbage . 65
i. Corporate . 65
ii. Geographic Spread . 66
iii. Key Clients & Strategic Partnerships . 66
iv. High Level View of Offerings . 66
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 66
3.3.5 Kasisto . 67
i. Corporate . 67
Table 3.7: Kasisto Funding Rounds . 67
ii. Geographic Spread . 67
iii. Key Clients & Strategic Partnerships . 67
iv. High Level View of Offerings . 68
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 68
3.3.6 Lemonade . 68
i. Corporate . 68
ii. Geographic Spread . 69
iii. Key Clients & Strategic Partnerships . 69
iv. High Level View of Offerings . 69
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 69
3.3.7 Mimiro . 70
i. Corporate . 70
Table 3.8: Mimiro Funding Rounds . 70
ii. Geographic Spread . 70
iii. Key Clients & Strategic Partnerships . 70
iv. High Level View of Offering . 71
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 71
3.3.8 NetGuardians . 72
i. Corporate . 72
Table 3.9: NetGuardians Funding Rounds . 72
ii. Geographic Spread . 72
iii. Key Clients & Strategic Partnerships . 72
iv. High Level View of Offerings . 72
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 73
3.3.9 OakNorth. 73
i. Corporate . 73
Table 3.10: OakNorth Funding Rounds . 73
ii. Geographic Spread . 74
iii. Key Clients & Strategic Partnerships . 74
iv. High Level View of Offerings . 74
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 74
3.3.10 Onfido . 75
i. Corporate . 75
Table 3.11: Onfido Funding Rounds . 75
ii. Geographic Spread . 75
iii. Key Clients & Strategic Partnerships . 75
iv. High Level View of Offerings . 76
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 76
3.3.11 Scalable Capital . 76
i. Corporate . 76
Table 3.12: Scalable Capital Funding Rounds . 77
ii. Geographic Spread . 77
iii. Key Clients & Strategic Partnerships . 77
iv. High Level View of Offerings . 77
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 77
3.3.12 Tractable . 78
i. Corporate . 78
Table 3.13: Tractable Funding Rounds . 78
ii. Geographic Spread . 78
iii. Key Clients & Strategic Partnerships . 78
iv. High Level View of Offerings . 78
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 79
3.3.13 Upstart . 79
i. Corporate . 79
Table 3.14: Upstart Funding Rounds . 79
ii. Geographic Spread . 80
iii. Key Clients & Strategic Partnerships . 80
iv. High Level View of Offerings . 80
Figure 3.15: Upstart Bad Debt Performance versus Selected Alternative Lenders,
By Weighted Average FICO Score . 80
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 81
3.3.14 Wealthfront . 81
i. Corporate . 81
Table 3.16: Wealthfront Funding Rounds . 81
ii. Geographic Spread . 81
iii. Key Clients & Strategic Partnerships . 82
iv. High Level View of Offerings . 82
v. Juniper’s View: Key Strengths & Strategic Development Opportunities . 82
3.3.15 ZestFinance . 83
i. Corporate . 83
Table 3.17: ZestFinance Funding Rounds . 83
ii. Geographic Spread . 83
iii. Key Clients & Strategic Partnerships . 83
iv. High Level View of Offerings . 83
v. Juniper’s View: Key Strengths & Development Opportunities . 84
2. Deep Dive Data & Forecasting
1. Introduction to AI in Fintech
1.1 Introduction . 4
Figure 1.1: AI Areas of Disruption . 4
2. Roboadvisors Market Forecasts
2.1 Introduction . 6
Table 2.1: AI Role Classification in Roboadvisors . 6
2.1.1 Methodology & Assumptions . 7
Figure 2.2: Roboadvisors Forecast Methodology . 8
2.2 Roboadvisors . 9
2.2.1 AUM (Assets Under Management) . 9
Figure & Table 2.3: Roboadvisors Assets under Management ($bn), Split by 8
Key Regions 2018-2023 . 9
2.2.2 Roboadvisor Platform Revenues . 10
Figure & Table 2.4: Roboadvisor Platform Revenues ($m), Split by 8 Key Regions
2018-2023 . 10
3. AI Consumer Lending Market Forecasts
3.1 Introduction . 12
3.2 Assumptions & Methodology . 12
Figure 3.1: Consumer Lending Forecast Methodology . 13
3.3 Consumer Lending . 14
3.3.1 Unsecured Loans Origination. 14
Figure & Table 3.2: Total Value of Unsecured Consumer Loans Originated ($m),
Split by 8 Key Regions 2018-2023 . 14
3.3.2 Platform Revenues . 15
Figure & Table 3.3: Service Provider Platform Revenues from Unsecured
Consumer Loans ($m), Split by 8 Key Regions 2018-2023 . 15
4. AI Business Lending Market Forecasts
4.1 Introduction . 17
4.2 Assumptions & Methodology . 17
Figure 4.1: Business Lending Forecast Methodology . 18
4.3 Business Lending . 19
4.3.1 Unsecured Loans Origination . 19
Figure & Table 4.2: Total Annual Machine Learning Aided Unsecured Business
Loan Value ($m), Split by 8 Key Regions 2018-2023 . 19
4.3.2 Platform Revenues . 20
Figure & Table 4.3: Annual Machine Learning Aided Unsecured Business Lending
Platform Revenues ($m), Split by 8 Key Regions 2018-2023 . 20
5. AI Insurtech Market Forecasts
5.1 Introduction . 22
5.2 Methodology & Assumptions . 22
Figure 5.1: Insurtech Forecast Methodology . 23
5.3 AI Insurtech Forecasts . 24
5.3.1 AI Premiums Generated . 24
Figure & Table 5.2: Total Value of Motor, Home, Life & Health Insurance
Premiums Underwritten by AI Underwriting Systems ($m) Split by 8 Key Regions
2018-2023 . 24
5.3.2 AI Claims Gross Cost Savings . 25
Figure & Table 5.3: Total Gross Cost Saving Assessing Motor, Home, Life &
Health Insurance Claims via AI ($m) Split by 8 Key Regions 2018-2023 . 25
Table 5.4: Total Gross Cost Saving Assessing Motor, Home, Life & Health
Insurance Claims via AI ($m) Split by Line 2018-2023 . 25
6. AI Regtech Market Forecasts
6.1 Introduction . 27
6.2 Methodology & Assumptions . 27
Figure 6.1: KYC Validation Forecast Methodology . 28
6.3 AI Regtech KYC Forecasts . 29
6.3.1 Cost Savings in Banking . 29
Figure & Table 6.2: Total Cost Saving on KYC Checks for Banking Utilising AI
Systems ($m), Split by 8 Key Regions 2018-2023 . 29
6.3.2 Cost Savings in Property Sales . 30
Figure & Table 6.3: Total Cost Saving on KYC Checks for Property Sales Utilising
AI Systems ($m), Split by 8 Key Regions 2018-2023 . 30
7. Chatbots Market Forecasts
7.1 Introduction . 32
7.2 Assumptions & Methodology . 32
Figure 7.1: Methodology for Messaging Application Chatbots . 33
Figure 7.2: Methodology for Discrete Application Chatbots . 34
Figure 7.3: Methodology for Web-based Chatbots . 35
7.3 Chatbot Banking Forecast . 36
7.3.1 Successful Chatbot Interactions . 36
Figure & Table 7.4: Number of Successful Banking Chatbot Interactions (m) Split
by 8 Key Regions 2018-2023. 36
7.3.2 Chatbot Cost Savings for Business . 37
Figure & Table 7.5: Total Banking Chatbots Cost Savings for Businesses ($m)
Split by 8 Key Regions 2018-2023 . 37
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