Finance & Accounting

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• Case Studies
  • Stock Market Trading
  • Banking
  • Improper Payments
• Backtesting
• Deepindex.org list
• Touchless Invoice Processing with AutoVouch
• Facial Recognition in Banking – Current Applications | Niccolo Mejia
• AI in Accounting: How Artificial Intelligence & Machine Learning Technology Has Changed the Industry | Faith Kubicki
• FINRA Technology | Dmytro Dolgopolov
• AI and ML in Financial Services Compliance Management: Use Cases for the Regulators
• Hitachi's H big data analysis engine; determine correlations, which can inform business decisions, forecasting, fraud detection, pricing | Bernard Marr - Forbes
• AI Startups in Auto Lending – 2 Well-Funded Examples | Niccolo Mejia - Emero
  • Zest ZAML - the only way to get your ML credit models from the lab to production. Reduce losses. Increase approvals. Fast.
  • Lendbuzz offers loans directly to consumers
• Areas where AI can contribute to compliance efficiency and effectiveness. | Pinchas These include:
  • NLP solutions can ‘read’ documents and perform a range of tasks including extracting metadata, identifying entities that are referred to, and ‘understanding’ the intent or purpose of specific parts of the document.
  • Know Your Customer Process – AI’s ability to analyze the vast amount of data and find patterns can create a more streamlined KYC process. By using algorithmic machine learning models, firms can generate risk profiles of individuals in just minutes.
  • Money Laundering Detection – Using AI, firms can evaluate monitoring reports, news items, and regulatory alerts, and further analyze those that indicate the highest risk exposures.
  • Rogue Employee Detection -AI can be used to identify employees that create fake accounts by tracking multiple accounts using the same email or IP address.
  • Trade Monitoring – Through AI, regulatory bodies can learn traders’ personalities and behavior which increase the precision of identifying suspicious trading.