Leading Detection

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Leading Detection: Where the world’s top fraud fighters talk shop. Hosted by Matt Brady, the industry’s leading fraud recruiter and founder of Sedulo Search, this is your front-row seat to the future of fraud prevention. Join us as we talk tech and tactics with leaders from BioCatch, Sardine, SEON, Sumsub, and more. We dive into: • War Stories: Hard lessons from the front lines. • The Tech Edge: Leveraging AI to stay ahead. • The Network: Strategies to disrupt fraud together. Subscribe for weekly drops. Let’s detect, disrupt, and do better.

  1. 30 THG 3

    An Introduction to HoneyBotting

    This episode with host Matt Brady explores HoneyBotting, a defensive cybersecurity technique that uses AI decoys to combat scams and fraud. Joe Tallett, co-founder and CEO of Aviel Intelligence, shares insights on how HoneyBotting is evolving in response to the growing sophistication of scammers, the technical infrastructure involved, and the ethical considerations. Key Topics • Honeybotting as a defensive technique against scams • The evolution of social engineering and AI in fraud • Technical infrastructure for HoneyBotting and scam detection • Ethical considerations in deploying HoneyBots • The role of AI in the cybersecurity arms race Chapters 00:00 Introduction to HoneyBotting and Its Importance 03:11 The Evolution of Scamming and Cybersecurity 06:36 The Infrastructure of HoneyBotting 08:49 Methodology of HoneyBotting 10:54 Understanding Hooks in Scamming 13:02 Differentiating Between Legitimate and Illegitimate Marketing 15:13 Ethical Considerations in HoneyBotting 17:51 Utilising Intelligence to Combat Scams 19:15 The Intersection of Financial Crime and Cybersecurity 21:27 The Arms Race: AI vs. AI in Scamming 25:26 Future of Aviel Intelligence and Closing Thoughts #CyberSecurity #AIsecurity #SocialEngineering #CyberDefense #Deepfake

    27 phút

  2. 23 THG 3

    Moving fraud detection into real-time

    In this conversation, Shay Yinusa discusses the critical shift towards real-time fraud detection and the importance of leveraging technology, particularly AI and machine learning, to stay ahead of increasingly sophisticated fraudsters. The discussion covers the current state of fraud detection, the challenges faced in implementing advanced technologies, and the necessity for collaboration and information sharing within the financial crime prevention community. Shay emphasises the need for organisations to be proactive and prepared for future challenges in fraud detection. Key Takeaways • We need to rely on more technology to detect fraud. • Fraud detection has evolved from static rules to real-time monitoring. • Real-time means making decisions at the moment of the transaction. • AI and machine learning are crucial for reducing false positives. • Collaboration and information sharing are essential in financial crime prevention. • Organisations must keep up with the evolving landscape of fraud. • Technology can help analysts focus on high-risk cases. • There are challenges in implementing AI effectively. • The future of fraud detection requires proactive thinking. • We must ensure that technology is used properly to prevent fraud. Chapters 00:00 The Shift to Real-Time Fraud Detection 04:57 Understanding Real-Time Monitoring 09:15 The Role of Technology in Fraud Prevention 14:01 Challenges in Implementing AI and Machine Learning 18:46 The Future of Fraud Detection 23:22 Collaboration and Information Sharing in Financial Crime 28:06 Looking Ahead: Opportunities and Concerns #fintech #ai #cybersecurity #machinelearning #fraudprevention

    29 phút

  3. 19 THG 3

    Machine Learning is the only way to fight fraud

    In this episode, Radhika Khatod, Group Product Manager for Machine Learning at Alloy, shares insights into how machine learning is revolutionising fraud prevention in financial services. She discusses the complexities of modern fraud, the limitations of rule-based systems, and the future of AI-driven detection methods. Key Topics The complexity of modern fraud and adversarial actorsLimitations of static rule-based fraud detection systemsHow machine learning models improve accuracy and reduce false positivesThe rise of synthetic identities and deepfake scamsThe importance of explainability and trust in AI models Chapters 00:00 Introduction to Fraud and Machine Learning 01:48 The Evolution of Fraud Tactics 05:38 The Shift from Rules to Machine Learning 08:27 Challenges in Adopting Machine Learning 10:38 Understanding AI and Machine Learning Terminology 12:16 Building Trust in Machine Learning Models 14:33 The Role of AI in Fraud Analysis 18:06 The Importance of Data in Fraud Detection 19:24 Distinguishing Between Normal Fraud and Coordinated Attacks 25:48 Global Perspectives on Fraud Prevention 29:14 Fintechs vs. Traditional Banks in Fraud Prevention 31:21 Challenges in Building Fraud Prevention Tools 33:21 The Future of Fraud Detection and Prevention #ai #fraudprevention #fintech #machinelearning #frauddetection

    38 phút

  4. 23 THG 2

    Revolutionising Business Verification

    In this conversation, Matt Brady and Chaitanya Sarda delve into the complexities of Know Your Business (KYB) processes, highlighting the challenges faced in standardisation, compliance, and fraud detection. They discuss the current state of KYB, the impact of AI on the industry, and the importance of effective vendor management. The conversation also touches on the evolving landscape of fraud and compliance communities, emphasising the need for robust defences and innovative solutions in the face of increasing fraud risks. Key Takeaways KYB is a relatively new term and still evolving.There is a lack of standardisation in KYB processes across industries.The explosion of new businesses necessitates real-time KYB checks.AI can significantly enhance the efficiency of KYB processes.Onboarding fraud is a growing concern that requires immediate attention.Compliance, risk, and fraud must be managed together for effective onboarding.Cross-border KYB presents unique challenges due to varying regulations.Data quality and access are critical for effective KYB.The industry is seeing a rise in fraud detection communities and resources.AI tools can help streamline the KYB process, but should not replace human judgment. Chapters 00:00 Introduction to KYB and Its Importance 02:51 Current Challenges in KYB Processes 05:27 Standardisation and Best Practices in KYB 07:45 The Role of AI in Revolutionising KYB 10:32 Cross-Border KYB: Navigating Global Compliance 13:10 Fraud Detection and Risk Management in KYB 15:28 The Future of KYB: Technology and Trends 17:51 Building a Global KYB System 20:23 Community and Collaboration in KYB 22:55 Conclusion and Future Outlook #kyb #compliance #frauddetection #AIincompliance #businessverification #crossborderpayments #onboardingprocess #riskmanagement #vendormanagement #fintech

    32 phút

  5. 19 THG 2

    The Fusion of Cyber and Fraud

    In this conversation, Matt Brady and Andrew La Marca explore the evolving landscape of cyber fraud and the necessity of integrating cyber and fraud detection efforts. They discuss the historical separation of these fields, the impact of technology and data on fraud strategies, the importance of data governance, and the role of synthetic data in fraud prevention. The conversation also touches on the culture of data sharing among businesses, the challenges of sharing sensitive information, and the future of careers in fraud detection as technology continues to advance. Key Takeaways Fraud and cyber threats are increasingly interconnected.Organisations must shift from siloed approaches to integrated strategies.The rise of technology has changed the landscape of fraud detection.Data governance is crucial for effective fraud prevention.Synthetic data can enhance model training and fraud detection.Sharing data among businesses can improve overall fraud prevention efforts.The culture around data sharing is evolving but still faces challenges.Career paths in fraud detection are changing with technological advancements.AI is becoming a critical tool in identifying fraud patterns.Continuous learning and adaptation are essential in the fight against fraud. Chapters 00:00 The Fusion of Cyber and Fraud 02:38 Understanding the Historical Separation 05:14 The Role of Technology in Fraud Detection 07:35 The Impact of Data on Fraud Strategies 10:08 Governance and Data Integrity 12:34 The Importance of Synthetic Data 14:55 Data Sharing Culture in Business 17:41 The Challenges of Peer-to-Peer Sharing 20:12 Career Development in Fraud Prevention 22:36 Future Trends in Fraud and Cybersecurity #CyberFraud #DataSharing #SyntheticData #FraudDetection #TechnologyInFraud #AIInFraud #Cybersecurity #FraudPrevention #DataGovernance

    35 phút

  6. 16 THG 2

    Orchestrating Fraud Detection

    In this conversation, Matt Brady and Dustin Eaton delve into the complexities of orchestrating fraud detection. They discuss the evolution from siloed point solutions to a more integrated approach that leverages data and AI. The conversation highlights the importance of understanding customer journeys, the challenges of building effective fraud detection systems, and the need for continuous learning and adaptation in the face of evolving fraud tactics. They also touch on regulatory perspectives regarding AI and the future of fraud prevention strategies. Key Takeaways Orchestration in fraud detection allows for a holistic view of customer risk.Point solutions are critical but should not be the only focus.Data quality is essential for effective fraud detection.Fraud does not recognise organisational boundaries, necessitating integrated defences.AI can enhance fraud detection, but requires proper governance and oversight.Building systems in large banks is often slowed by bureaucracy and technical debt.Understanding customer behavior is key to identifying fraud patterns.The fraud detection market is crowded, leading to potential consolidation.Continuous learning and adaptation are crucial in the fraud industry.Strategic investments in fraud prevention can reduce costs and improve efficiency. Chapters 00:00 Introduction to Orchestrating Fraud Detection 02:04 Understanding Point Solutions in Fraud Detection 05:05 The Importance of Data in Fraud Prevention 08:44 Challenges in Building Internal Fraud Systems 11:32 The Evolution from Point Solutions to Comprehensive Solutions 14:14 Navigating the Vendor Landscape in Fraud Detection 17:23 The Future of Fraud Detection Tools 20:13 The Intersection of Fraud and Cybersecurity 23:49 The Role of AI in Fraud Detection 28:20 Regulatory Perspectives on AI in Fraud Prevention 33:09 Strategic Investments in Fraud Prevention 37:42 Final Thoughts and Industry Insights #FraudDetection #FraudPrevention #Cybersecurity #FinTech #AIinFraud #FinancialTechnology #RegulatoryCompliance #DataChallenges #Orchestration #IndustryInsights #FraudTech #PointSolutions #AI #InfoSec #DigitalBanking

    42 phút

  7. 12 THG 2

    Unveiling Merchant Fraud

    In this conversation, Yuliya Kazakevich discusses the growing issue of merchant fraud, its evolution over the years, and the role of AI in detecting and preventing fraud. She emphasises the importance of continuous monitoring and the need for collaboration and data sharing within the industry to combat fraud effectively. The conversation also touches on regulatory challenges, the rising costs of fraud prevention, and the future of risk and compliance in a rapidly changing landscape. Key Takeaways Merchant fraud is often overlooked compared to consumer fraud.AI technologies have made it easier for fraudsters to operate.Continuous monitoring is essential for identifying fraudulent activities.Collusion among fraudsters is becoming more common.Data sharing between companies is crucial for effective fraud detection.Regulatory mandates may be necessary to improve data sharing.The cost of fighting fraud is increasing as fraudsters become more sophisticated.AI can enhance fraud detection but requires proper governance.The future of risk and compliance will involve more complex decision-making.Companies need to adapt to the evolving landscape of fraud and compliance. Chapters 00:00 Introduction to Merchant Fraud 02:34 The Evolution of Merchant Fraud 05:08 AI in Fraud Detection 07:28 Continuous Monitoring of Merchants 10:06 Collusion and Teamwork in Fraud 12:25 The Role of AI in Risk and Compliance 15:04 Challenges in Detecting Merchant Fraud 17:38 Data Sharing and Collaboration in Fraud Prevention 19:53 The Cost of Fighting Fraud 22:05 The Future of Risk and Compliance Teams 24:38 Conclusion and Future Events #MerchantFraud #AIInFraudDetection #ContinuousMonitoring #FraudCollusion #RiskManagement #DataSharing #RegulatoryChallenges #FraudPrevention #Fintech #Compliance

    33 phút

  8. 8 THG 2

    How fraud is becoming more sophisticated

    In this conversation, Julia Andreeva discusses the evolution of modern fraud, highlighting the increasing sophistication of fraud techniques, particularly with the rise of AI. She explains how fraudsters are now using AI to create synthetic identities and adapt their tactics in real-time, making it more challenging for traditional fraud prevention methods to keep up. The discussion also covers the importance of continuous risk assessment in fraud prevention, emphasising that verification should not be a one-time process but an ongoing evaluation of user behaviour. Finally, the conversation touches on the potential future of fraud, including the industrialisation of fraud techniques and the need for organisations to adapt their defences accordingly. Key Takeaways Fraud has evolved to become more sophisticated and abstract.AI is enabling fraudsters to create synthetic identities.The barrier to entry for committing fraud is decreasing.Fraudsters are manipulating telemetry and behaviour to evade detection.Continuous risk assessment is essential for effective fraud prevention.Traditional document checks are no longer sufficient on their own.AI fraud agents can learn and adapt their tactics in real-time.The industrialisation of fraud is a realistic worst-case scenario.Organisations need to merge fraud prevention and compliance teams.AI can be used defensively to enhance fraud detection capabilities. Chapters 00:00 The Evolution of Modern Fraud 03:09 AI's Role in Fraud Sophistication 06:12 Understanding Telemetry and Behaviour in Fraud 09:17 The Rise of Synthetic Identities 12:10 AI Fraud Agents: A New Threat 15:08 Continuous Risk Assessment in Fraud Prevention 18:14 The Multi-Layered Approach to Fraud Prevention 21:14 The Importance of Post-Onboarding Monitoring 24:05 The Future of Fraud: Risks and Adaptations 26:53 The Role of AI in Defence Strategies 30:00 Identifying Technical Blind Spots in Fraud Prevention 33:13 The Worst-Case Scenario for Fraud #fraud #AI #identitytheft #fraudprevention #cybersecurity #digitalidentity #frauddetection #riskassessment #syntheticidentity #fraudtrends

    40 phút
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Giới Thiệu

Leading Detection: Where the world’s top fraud fighters talk shop. Hosted by Matt Brady, the industry’s leading fraud recruiter and founder of Sedulo Search, this is your front-row seat to the future of fraud prevention. Join us as we talk tech and tactics with leaders from BioCatch, Sardine, SEON, Sumsub, and more. We dive into: • War Stories: Hard lessons from the front lines. • The Tech Edge: Leveraging AI to stay ahead. • The Network: Strategies to disrupt fraud together. Subscribe for weekly drops. Let’s detect, disrupt, and do better.

Thông Tin

  • Nhà sáng tạo
    Sedulo Search
  • Năm hoạt động
    2025 - 2026
  • Tập
    24
  • Xếp hạng
    Sạch
  • Bản quyền
    © Sedulo Search
  • Trang web chương trình
    Leading Detection