This conference explores how FinTech analytics is transforming traditional credit scoring and lending processes by integrating alternative data sources such as social media, transaction histories, and behavioral data. It focuses on advanced machine learning models and AI to enhance credit risk assessment, improve financial inclusion, and optimize lending decisions while managing compliance and ethical considerations. Discussions include data integration, model transparency, regulatory frameworks, and case studies demonstrating successful FinTech innovations.
Structure and Sessions (Who Does What):
Organizing Committee: Plans the agenda, selects speakers, and manages event logistics.
Keynote Speakers: Industry leaders, FinTech innovators, and data scientists share insights and breakthroughs.
Session Chairs: Moderate sessions, manage Q&A, and foster interactive engagement.
Presenters: Researchers, practitioners, and technology experts present papers, case studies, and emerging trends.
Participants: Engage actively in discussions, workshops, and networking.
Technical Review Committee: Ensures quality and relevance of abstracts and papers.
Participate and Contribute (Who Benefits):
FinTech Professionals and Data Scientists: Gain knowledge of cutting-edge credit scoring models and data sources.
Lending Institutions and Risk Managers: Learn innovative approaches for risk assessment and portfolio management.
Regulatory and Compliance Officers: Understand evolving frameworks governing alternative data use in lending.
Academics and Researchers: Present and publish research on FinTech analytics.
Investors and Consultants: Explore trends shaping the future of credit scoring and lending.
Benefits:
Certificate of Participation awarded upon feedback submission.
Commemorative momento recognizing active involvement.
Abstracts and selected papers published in Scopus, CrossRef, Web of Science (WoS), Elsevier, and SCI-indexed journals.
Abstract Topics / Call for Papers (CFP) Tracks:
Alternative Data Sources for Credit Scoring
Machine Learning and AI in Lending Decisions
Financial Inclusion through FinTech Innovations
Model Explainability and Transparency
Regulatory Compliance and Ethical Considerations
Risk Management and Portfolio Optimization
Case Studies of Successful FinTech Lending Models
Impact of Behavioral and Social Data Analytics
Fraud Detection and Credit Risk Mitigation
Future Trends in FinTech Credit Analytics
Registration:
Online registration open to FinTech professionals, data scientists, regulators, researchers, and students.
Clear submission guidelines and deadlines provided.
Access to live sessions, recordings, materials, certification, and publication opportunities.
Detailed Program Grid (2 Half Days, 9 AM to 1 PM)
Time
Day 1
Day 2
09:00 – 09:15
Opening Ceremony & Welcome Address
Recap of Day 1 & Opening Keynote
09:15 – 10:00
Keynote Session I: Innovations in Alternative Data for Credit Scoring
Keynote Session III: AI and Explainable Lending Models
10:00 – 10:45
Technical Session I: Machine Learning for Risk Assessment
Technical Session III: Regulatory and Ethical Frameworks
10:45 – 11:00
Q&A and Networking Break
Q&A and Networking Break
11:00 – 11:45
Technical Session II: Behavioral Data and Financial Inclusion
Panel Discussion: Challenges and Opportunities in FinTech Lending
11:45 – 12:30
Abstract Presentations and Case Studies
Technical Session IV: Future Directions in FinTech Analytics
12:30 – 13:00
Participant Feedback and Closing Remarks
Closing Ceremony & Certificate Distribution
This conference offers the latest insights into reshaping credit scoring and lending with alternative analytics data, complemented by certification and peer-reviewed publishing options.
