According to the ACFE, construction fraud is the fourth highest median losses by industry. Forensic accounting allows business owners to engage with a professional to quantity the losses and determine who benefited. In this session, we will talk about cases that Ms. Landau has investigated as well the missing link to the fraud triangle.
NICOLE LANDAU
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Nicole helps Construction company owners & Contractors improve profits, streamline back office processes and control costs by providing industry-specific risk management practices.Â
Nicole focus ONLY on serving Construction and Contractor clients, meaning she’s plugged into the latest industry trends, software and solutions, ensuring you stay ahead of the curve and get the best ROI possible when it comes to your accounting function.
CLAIRE WORLEDGE
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Claire spent 10 years working for Deloitte, managing the data analytics team. In 2010, she created Aufinia. Aufinia has worked for 50 different companies that use SAP over the years.Â
Claire is a Certified Information Systems Auditor (CISA), Certified Fraud Examiner (CFE) and Certified ACL Data Analyst (ACDA). Aufinia is a global OEM partner with QLIK and also a Galvanize reseller partner for Vietnam and China. Claire has a Masters in IT from University College London, as well as a Bachelors in Biochemistry.Â
“Thanks for all the amazing content in the webclasses. We have learned quite a lot and this is helping the team to get going with SAP data analytics, as well as challenging our consulting vendors!”
Celia, Head of Internal Audit
How do the Big 4 firms do data analytics?
What does the IIA, ISA, ACFE and ISACA say about data analytics?
What risks should be avoided when using data analytics in internal audit?
How can we train our auditors so that they can successfully use data analytics in their work?
What are the most obvious fraud schemes that data analysts need to be aware of?
What do “normal“Â auditors and data analysts need to understand to make an efficient team?
Which data do you need to extract from SAP and how should it be interpreted?
How can we leverage data to see risks in the entity and better prepare the audit?