Overview:
Automation and machine learning is used in fraud detection to suggest rules relevant to the business after analyzing your business data fraud cases. Fraud detection can automatically deploy fraud detection software. Software can be used to automatically accept user actions deemed low risk and blocked those labeled as high-risk. Some automations are based on static rules while more sophisticated tools can score risk and deploy dynamic automation.
Why you should Attend:
Finance, accounting, operational, compliance and legal professionals.
Areas Covered in the Session:
Who Will Benefit:
Lynn Fountain has over 45 years of experience spanning public accounting, corporate accounting and consulting. 20 years of her experience has been working in the areas of internal and external auditing and risk management. She is a subject matter expert in multiple fields including internal audit, ethics, fraud evaluations, Sarbanes-Oxley, enterprise risk management, governance, financial management and compliance. Lynn has held two Chief Audit Executive (CAE) positions for international companies. In one of her roles as CAE, she assisted in the investigation of a multi-million-dollar fraud scheme perpetrated by a vendor that spanned 7 years and implicated 20 employees. The fraud was formally investigation by the FBI and resulted in 5 indictments estimating a $13M fraud loss.
Ms. Fountain obtained her BSBA from Pittsburg State University and her MBA from Washburn University in Kansas. She has her CPA, CGMA, CRMA credentials.