범죄에 대항하는 협업 : 데이터 공유 활용으로 보다 스마트한 부정 감지를 실현

This IDC Perspective explores the critical role of data sharing in combating financial fraud, emphasizing its transformative potential in early detection, broader insights, and operational efficiency. By leveraging collaborative data-sharing practices, financial institutions can address complex fraud schemes that span multiple organizations, such as synthetic identity fraud, account takeovers, and money laundering.This document highlights the benefits of shared intelligence, including enhanced machine learning models and cost savings, while addressing challenges such as privacy concerns, data quality, and stakeholder trust. It also outlines practical solutions including adopting interoperability standards, implementing secure data exchange platforms, and fostering collaborative ecosystems to strengthen fraud defenses.For technology buyers, the document provides actionable guidance on assessing risks, adopting automation, selecting appropriate technologies, and measuring ROI to maximize the impact of data-sharing initiatives. By addressing these aspects, the document underscores how financial institutions can unlock the full potential of collaborative fraud detection and prevention strategies."The future of fraud prevention lies in collaboration," says Sam Abadir, research director, IDC Financial Insights for Risk, Financial Crime, and Compliance. "By embracing secure data-sharing frameworks including vendor-provided software solutions and leveraging advanced analytics, financial institutions can shift from reactive to proactive strategies, enabling faster detection, stronger defenses, and a more unified fight against evolving threats."

Executive Snapshot

Situation Overview

• Introduction
  • The Role of Data Sharing in Fraud Detection
  • Benefits of Data Sharing for Fraud Detection
    • Early Detection and Prevention
    • Broader Insights
    • Enhanced Machine Learning Models
    • Cost Savings and Operational Efficiency
  • Challenges in Data Sharing for Fraud Detection
    • Challenges Abound
    • Privacy Concerns and Legal Constraints
    • Data Quality and Standardization
    • Trust Among Stakeholders
• Solutions to Data Sharing Challenges
  • Strong and Scalable Reporting
  • Regulatory Compliance Strategies
  • Interoperability Standards
  • Secure Data Exchange Platforms
  • Collaborative Ecosystems
• The Future of Data Sharing to Fight Fraud

Advice for the Technology Buyer

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• Related Research
• Synopsis