Data Analytics Advisory
How can Tricor Axcelasia support your organization and what data analytics services do we offer?
- Support the structure of the data analytics program and framework that utilizes data as a strategic asset
- Provide approaches and training to upskill auditors and clients with non-analytic backgrounds
- Develop customized and advanced analytics models and best methods to extract, collect, cleanse, transform, integrate, load, store, share and present data and confirm it remains reliable, compliant, and secure in the process
- Implement a continuous monitoring solution, approach and bespoke test rules and algorithms to help identify hidden red flags, more meaningful audit sample selection and control gaps
What strategic advantages can Tricor Axcelasia offer and what capabilities can we help you build?
- Deliver high quality data analytics efficiencies through proven methodology, test rules and algorithms
- Identify control weaknesses and process loopholes that may be uncovered by retrospective audits
- Help the organization understand the GRC data landscape by developing a results-driven data analytics and data visualization strategy, program and tools
What is Tricor Axcelasia’s value proposition?
- Our experienced advisors possess deep industry knowledge and have developed innovative methodology, approach, tools and capabilities for Data & Analytics enabling Internal Audit and continuous compliance monitoring projects for clients
- A highly interactive approach to engage all stakeholders
- Senior-level professional involvement in engaging business managers
5-step roadmap to help transform GRC into a data-led function
Step 1: Start small
Start with a small project. This will be beneficial, because the cost and the required data volume will be low and turnaround time is shorter. Have an interactive dashboard format output and clear, actionable recommendations.
Step 2: Focus on prevalent risks and issues
Pick an area that poses inherent risk and issues. Be crystal clear of what needs to be achieved. For example, some questions that need to be addressed include:
- Have payments been made to government officials?
- Have any facilitation payments been made?
- Are all employee expenses legitimate?
- Are employees and third parties colluding to circumvent controls?
- Are there any fictitious employees / vendors?
- Are they any undisclosed conflicts of interest?
- Are vendors committing fraud?
- Where should the focus be on costly audits and monitoring?
Step 3: Start with readily-available data
Begin with whatever data is available right now. Extracting, transforming, loading, cleansing and running analytic test rules on data sets is a simple operation for experienced data scientists or professional service providers, which may take a shorter period than you might anticipate.
Step 4: Identify and validate red flags
Identify red flags, rule out false positives, engage with the key stakeholders early, including peers and up the chain of command. Presenting the results to stakeholders will provide tangible evidence of analytics’ potential, and high-level ROIs.
Step 5: Continuous improvement along the way
Moving from a static and retrospective monitoring approach to a dynamic and predictive data-led compliance function does not happen overnight. It requires thoughtful planning, diligent execution and continuous improvement on the data analytics algorithm along the way until it reaches the intended maturity level of data analytics capability.