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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/103593
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dc.contributor.advisor謝源弘zh_TW
dc.contributor.advisorYuan Horng Hsiehen
dc.contributor.author葉啟民zh_TW
dc.contributor.authorJohn Kevin Sun Goen
dc.date.accessioned2026-08-18T17:07:49Z-
dc.date.available2026-08-19-
dc.date.copyright2026-08-18-
dc.date.issued2026-
dc.date.submitted2026-07-27 00:00:00-
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/103593-
dc.description.abstract菲律賓金融包容性的擴展速度已超越金融健康的改善速度。儘管銀行帳戶持有率持續提升,許多在職菲律賓人仍處於財務脆弱的狀態,信用資料有限,且未能充分獲得正式金融體系所提供的信貸服務。本商業計畫提出並評估 Stashwise,一個由人工智慧(AI)驅動的雙邊金融科技平台。Stashwise 整合現金流追蹤、行為輔導及「金融健康評分」(Financial Health Score),並透過取得使用者同意後蒐集之行為型補充金融資料,協助金融機構服務信用資料不足(thin-file)的消費者。本商業計畫旨在評估 Stashwise 於菲律賓市場的商業吸引力、營運可行性及策略防禦能力。
為驗證本商業計畫的市場假設與可行性,本計畫採用混合研究方法,透過結構式問卷調查(n = 124)蒐集資料,受訪者來源包括協助式實地訪談、線上問卷,以及海外菲律賓勞工(Overseas Filipino Workers, OFWs)管道。此外,本計畫亦針對一家專門服務信用資料不足客群的金融科技放款機構,訪談兩位機構代表,並進行半結構式訪談。問卷資料採用描述性分析及分群分析,訪談資料則透過主題分析進行詮釋,並與消費者調查結果進行比較。
市場驗證結果顯示,受訪者對 Stashwise 所提供的功能具有興趣,並對經使用者同意後進行資料共享持開放態度;然而,信任與詐騙疑慮仍是影響採用意願的重要障礙。機構訪談結果顯示,針對信用資料不足客群的信用評估,可能依賴有限的資料來源,且未能充分反映非正式收入。透過「探索驅動規劃」(Discovery-Driven Planning)方法進行財務規劃,預估 Stashwise 將於第四年達成營運損益兩平,並分階段籌集 230 萬美元資金。
綜合市場驗證、機構訪談及財務分析結果,本商業計畫認為 Stashwise 具備商業可行性。然而,其成功高度取決於執行能力、使用者信任的建立,以及與金融機構合作關係的發展。Stashwise 旨在連結個人的金融行為與取得金融服務的機會,進而促進菲律賓金融包容性及金融健康的發展。
zh_TW
dc.description.abstractFinancial inclusion in the Philippines has expanded faster than financial health. Although account ownership has increased, many working Filipinos remain financially fragile, thinly documented, and underserved by formal credit systems. This paper develops and evaluates a business plan for Stashwise, a two-sided AI-driven fintech platform combining cash-flow tracking, behavioral coaching, and a Financial Health Score with a consent-based, behavior-informed supplementary signal for financial institutions serving thin-file consumers. The study asks whether Stashwise is commercially attractive, operationally feasible, and strategically defensible in the Philippine context. A mixed-methods approach was used. A structured consumer survey (n=124) was administered through assisted in-person outreach, online distribution, and Overseas Filipino Worker (OFW) channels. This was complemented by two semi-structured interviews with informants from a fintech lender operating in the thin-file segment. Survey data were analyzed descriptively and by segment, while interview findings were thematically interpreted and compared with consumer evidence. Respondents showed interest in Stashwise’s features and openness to consent-based data sharing, although trust and fraud concerns remain central adoption barriers. Institutional interviews suggest that thin-file underwriting may rely on limited inputs and insufficiently recognize informal income. Using Discovery-Driven Planning, the financial plan projects operating break-even in year four with USD 2.3 million in staged funding. The business plan concludes that Stashwise is commercially plausible but execution and trust-dependent, linking financial behavior to financial access.en
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dc.description.tableofcontentsTable of Contents
Acknowledgment i
中文摘要 ii
Abstract iii
Table of Contents iv
List of Tables viii
List of Abbreviations ix
1. Introduction 1
1.1 Overview of the Business 1
1.2 Mission Statement 3
1.3 Vision Statement 3
2. Business Description 4
2.1 Core Business Concept 4
2.1.1 Business Model Canvas 5
2.1.2 Pain and Gain Value Proposition Design 8
2.1.2.1 Filipino Consumers 9
2.1.2.2 Regulated Financial Institutions 10
2.1.3 Platform Business with Cross-Subsidization 10
2.2 Target Market 13
2.2.1 Paycheck-to-Paycheck Local Professionals 14
2.2.2 Overseas Filipino Workers (OFWs) 14
2.2.3 Regulated Financial Institutions 16
2.3 Strategic Vision 16
2.4 Business Objectives 17
2.5 Key Performance Indicators (KPIs) 21
2.5.1 KPI Prioritization by Stage 23
3. Description of Key Services and Features 25
3.1 Consumer Application: Stashwise App 25
3.1.1 Cash Flow Tracking and Financial Visibility 25
3.1.2 Financial Health Score 27
3.1.3 AI-Powered Behavioral Coaching and Nudges 28
3.1.4 Gamification and Retention Features 29
3.1.5 Financial Product Marketplace 31
3.2 B2B Data and API Services: Stashwise for Financial Institutions 31
3.2.1 Supplementary Underwriting Signal and API 32
3.2.2 Signal Components and Partner Use Cases 34
3.2.3 Score Construction and Comparison with Traditional and Alternative Credit Soring 35
3.2.4 Risk Segmentation Reports and Later-Stage Marketplace Options 38
3.3 Business Model 39
3.4 Technology Stack 39
3.5 AI-Supported Intelligence Layer 41
3.5.1 Role of AI in Stashwise 41
3.5.2 Core AI-Supported Modules 41
3.5.3 Coordination, Permissions, and Institutional Boundaries 42
3.5.4 Responsible AI Principles 43
4. Market Analysis 45
4.1 Research Preparation 45
4.1.1 Research Objectives 45
4.1.2 Data Collection Methods 46
4.1.3 Consumer Survey (Quantitative) 46
4.1.4 Institutional Stakeholder Interviews (Qualitative) 47
4.2 Result Analysis 48
4.2.1 Consumer Survey 48
4.2.1.1 Prevalence of Financial Fragility Across Respondents 48
4.2.1.2 Informal and Reactive Financial Management Practices 49
4.2.1.3 Weak Credit Visibility and Limited Financial Self-Understanding 50
4.2.1.4 User Readiness for Digital Adoption and Consent-Based Data Sharing 51
4.2.1.5 Trust, Privacy, and Adoption Constraints 52
4.2.1.6 Validation of MVP Feature Priorities 53
4.2.1.7 Distinct Financial Behaviors Among OFW Respondents 54
4.2.2 Institutional Stakeholders 56
4.3 Macro Analysis 59
4.3.1 PESTLE 59
4.3.2 Porter’s Five Forces 62
4.4 Micro Analysis 64
4.4.1 Resources and Capabilities 64
4.4.2 Porter’s Generic Strategy 64
4.5 Competitor Analysis 65
4.5.1 Competitive Landscape Overview 65
4.5.2 Competitor Profiles and Positioning Matrix 66
4.5.3 Competitive Positioning and Differentiation 67
4.6 SWOT Analysis 70
4.7 TAM, SAM, SOM, Early Adopters, and Institutional Serviceable Partners 71
4.7.1 Total Addressable Market (TAM) 71
4.7.2 Serviceable Available Market (SAM) 72
4.7.3 Serviceable Obtainable Market (SOM) 72
4.7.4 Early Adopters 73
4.7.5 Institutional Serviceable Partner Universe 74
5. Organization and Management Strategy 76
5.1 Organizational Structure 76
5.1.1 Core Team 76
5.1.2 Future Expansion 78
5.2 Leadership and Management Philosophy 79
5.2.1 Behavioral-First Decision Making 80
5.2.2 Lean and Agile Management 80
5.2.3 Regulatory Engagement Mindset 80
5.2.4 Cultural Fluency as a Core Competency 81
6. Marketing and Sales Strategy 82
6.1 Target Market 82
6.2 Marketing Channels 83
6.2.1 Paid and Organic Social Media 83
6.2.2 Partnership Channels 84
6.2.3 Retention Channels 85
6.3 Consumer Acquisition Strategy 85
6.4 Institutional Partnership Acquisition Strategy 86
6.5 Revenue Model and Pricing Strategy 87
7. Financial Plan 88
7.1 Approach for Financial Planning 88
7.2 Key Financial Assumptions 88
7.2.1 User and Institutional Partner Growth 91
7.2.2 Headcount by Role and Phase 94
7.3 Revenue Model and Cost Structure 96
7.3.1 Revenue Model and Pricing 96
7.3.2 Cost Structure by Category 96
7.4 Five-Year Projected Income Statement 100
7.5 Burn Rate, Runway, and Milestone Trajectory 102
7.6 Indicative Valuation and Target Valuation 106
7.7 Funding Strategy and Corporate Structure 107
7.7.1 Milestone-Based Funding Strategy 107
7.7.2 Singapore Holding Company Over a Philippine Operating Entity 108
7.7.3 Philippine Operating-Entity Incorporation and the Paid-Up-Capital Consideration 110
Uncertainty and Risks 111
7.8 Market Risks 112
7.9 Operational and Execution Risks 113
7.10 Financial and Commercial Risks 115
7.11 Regulatory and Data-Governance Risk 116
7.12 Structural and Foreign Exchange Risk 118
7.13 Key Person Risk 119
7.14 Mitigation Strategies 119
7.15 Future Development Priorities 121
8. Exit Strategy 123
8.1 Strategic Acquisition 123
8.1.1 Digital Banks and E-Wallet Platforms 123
8.1.2 Credit Bureaus and Alternative Data Providers 123
8.1.3 Regional Fintech Consolidators and Lenders 124
8.2 Acqui-hire and Technology Acquisition 124
8.3 Secondary Sale and Financial Buyout 124
8.4 Initial Public Offering 125
8.5 Exit Analysis 125
9. Conclusion 126
References 129
Appendices 135
Appendix A: Qualtrics Consumer Survey 135
Appendix B: Institutional Interview Instruments and Records (PayJoy Philippines) 149
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dc.language.isoen-
dc.subject金融包容性-
dc.subject金融科技-
dc.subject信用資料不足消費者-
dc.subject替代性信用資料-
dc.subject菲律賓-
dc.subjectFinancial Inclusion-
dc.subjectFintech-
dc.subjectThin-File Consumers-
dc.subjectAlternative Credit Data-
dc.subjectPhilippines-
dc.titleAI普惠金融平台開發: 針對菲律賓信用薄檔及金融服務弱勢消費者之應用zh_TW
dc.titleBridging the Financial Access Gap: An AI-Driven Fintech Solution for Thin-File and Financially Underserved Consumers in the Philippinesen
dc.typeThesis-
dc.date.schoolyear114-2-
dc.description.degree碩士-
dc.contributor.coadvisor孔令傑zh_TW
dc.contributor.coadvisorLing-Chieh Kungen
dc.contributor.oralexamcommittee堯里昂;柯冠州zh_TW
dc.contributor.oralexamcommitteeLeon van Jaarsveldt;Kuan-Chou Koen
dc.subject.keyword金融包容性; 金融科技; 信用資料不足消費者; 替代性信用資料; 菲律賓zh_TW
dc.subject.keywordFinancial Inclusion; Fintech; Thin-File Consumers; Alternative Credit Data; Philippinesen
dc.relation.page151-
dc.identifier.doi10.6342/NTU202602457-
dc.rights.note同意授權(限校園內公開)-
dc.date.accepted2026-07-28-
dc.contributor.author-college管理學院-
dc.contributor.author-dept企業管理碩士專班-
dc.date.embargo-lift2026-08-19-
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