This course covers the role data analytics has in the identification of uncommercial transactions for later review and, if justified, investigation. It is one of the key ways in which uncommercial transactions can be identified.
Many businesses have a sense of the value that data analytics can deliver and do invest time and resources in this area. However, while data analytics targeting profitability, cash flow, business efficiency and so on are generally done well, that targeting the identification of uncommercial transactions is often less effective.
Key topics:
- ‘Data analytics’ – what is it?
- What data does an organisation need in order to perform data analytics?
- What tools are used?
- What frauds, corruption and uncommercial transactions can be detected?
- Post-transactional data analytics: a step-by-step guide
- Step 1: Analyse the business
- Step 2: Design data tests
- Step 3: Data acquisition
- Step 4: Data preparation and normalisation
- Steps 5, 6 and 7: Analyse, report and investigate
- Case study
- Challenges
- Analysis of data in real-time or near real-time