Tax Data Analytics Helps Automaker Reduce ... amazonaws com
Tax Data Analytics Helps Automaker Reduce Risk The sheer volume of data in the business systems of an American multinational corporation is almost beyond imagination. What’s easy to imagine is the value it holds for that corporation, if meaning can be mined from its many splintered pieces. One such corporation – a Fortune 50 automaker – wasn’t capitalizing on a massive amount of tax data, until it turned to KPMG Ignition to help extract value from volume. The challenge Data holds an incredibly important place in today’s tax function. It is being brought to the forefront in discussions regarding transfer pricing, VAT/GST, trade and customs, global mobility, and more. More than ever, data provides the tax function a platform to optimize day-to-day operations, improve tax planning, enhance risk management, and create new enterprise value. A U.S. corporation which designs, manufactures and distributes vehicles and vehicle parts globally was missing this opportunity. While the automaker’s enterprise resource planning, tax decision, and other transactional and financial collected “big data,” it didn’t have the knowledge or capability to extract the data, uncover anomalies and trends, digest it and make sense of it, and use the insights gained to drive better business decisions.
The automaker didn’t know how to deal with the volume of tax data available. The approach KPMG was already providing tax services to the automaker, but it recognized the company could gain even greater value by turning previously untapped tax data into business insights. KPMG Ignition, along with KPMG’s Tax Data Analytics team, was brought in to use its proprietary tools and deep expertise to perform robust analytics on the corporation’s tax data, through a five-step process: 1. Data investigation: Using its deep subject matter knowledge of the tax domain as well as the data analytics space, the team conducted preliminary analyses on the client’s systems and data and provided suggestions on the datasets to extract, boiling it down to only the “right” data – i.e. the most valuable data the company needed to focus on.
KPMG Ignition
2. D ata extraction: Working with the IT group, the team extracted volumes and volumes of the client’s data – data from across its disparate systems and stored in a wide variety of formats – and uploaded it to KPMG servers. 3. Data blending and modeling: To cope with the variety of unstructured and structured data extracted, the team processed the data and transformed it into a useable format, which was then loaded it into a central data repository for analysis.
4. Data analytics: Based on its knowledge of the automaker’s systems and business needs, KPMG’s data scientists analyzed the historical data, pinpointing important trends. 5. Data visualization: The team created maps and charts using powerful visualization tools to unveil patterns and share key findings back with the automaker in a meaningful way. KPMG Ignition’s Tax Data Analytics team performed robust analytics on the automaker’s tax data using a 5-step process.
The results KPMG Ignition’s Tax Data Analytics team found anomalies in the data, due to improperly configured tax decision engines, that revealed that the automaker was miscalculating its tax liability, causing it to pay too much in some jurisdictions and too little in other jurisdictions. From a risk management perspective, this error exposed the corporation to possible non-compliance with regulatory rules and opened it up to investigation or punitive action by authorities. Operationally, it was clear this was a process and technology problem that would continue to happen if not immediately corrected, further increasing the company’s risk exposure. The company sought KPMG’s help to implement corrective actions on its tax decision systems and processes, correcting the short-term compliance problem and improving the company’s risk management profile for the future.
KPMG Ignition’s Tax Data Analytics team discovered errors in how the automaker configured its tax decision engines. By fixing the problem, the automaker reduced its risk exposure.
Data & Analytics at KPMG Client Infrastructure
Other ERPs & Data Sources
KPMG Extracted Files Extracted Files Extracted Files
SFTP
Extracted Files Extracted Files Extracted Files
Analytics
alteryx Database Transactional & Master Data
ETLProcess
DaRT Extraction Process
ABAP
Rafiq Jalal Director, Tax Transformation and Technology KPMG Ignition Denver [email protected] 720-573-7029
© 2015 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. Printed in the U.S.A. The KPMG name, logo, and “cutting through complexity” are registered trademarks or trademarks of KPMG International. NDPPS 369026
The automaker didn’t know how to deal with the volume of tax data available. The approach KPMG was already providing tax services to the automaker, but it recognized the company could gain even greater value by turning previously untapped tax data into business insights. KPMG Ignition, along with KPMG’s Tax Data Analytics team, was brought in to use its proprietary tools and deep expertise to perform robust analytics on the corporation’s tax data, through a five-step process: 1. Data investigation: Using its deep subject matter knowledge of the tax domain as well as the data analytics space, the team conducted preliminary analyses on the client’s systems and data and provided suggestions on the datasets to extract, boiling it down to only the “right” data – i.e. the most valuable data the company needed to focus on.
KPMG Ignition
2. D ata extraction: Working with the IT group, the team extracted volumes and volumes of the client’s data – data from across its disparate systems and stored in a wide variety of formats – and uploaded it to KPMG servers. 3. Data blending and modeling: To cope with the variety of unstructured and structured data extracted, the team processed the data and transformed it into a useable format, which was then loaded it into a central data repository for analysis.
4. Data analytics: Based on its knowledge of the automaker’s systems and business needs, KPMG’s data scientists analyzed the historical data, pinpointing important trends. 5. Data visualization: The team created maps and charts using powerful visualization tools to unveil patterns and share key findings back with the automaker in a meaningful way. KPMG Ignition’s Tax Data Analytics team performed robust analytics on the automaker’s tax data using a 5-step process.
The results KPMG Ignition’s Tax Data Analytics team found anomalies in the data, due to improperly configured tax decision engines, that revealed that the automaker was miscalculating its tax liability, causing it to pay too much in some jurisdictions and too little in other jurisdictions. From a risk management perspective, this error exposed the corporation to possible non-compliance with regulatory rules and opened it up to investigation or punitive action by authorities. Operationally, it was clear this was a process and technology problem that would continue to happen if not immediately corrected, further increasing the company’s risk exposure. The company sought KPMG’s help to implement corrective actions on its tax decision systems and processes, correcting the short-term compliance problem and improving the company’s risk management profile for the future.
KPMG Ignition’s Tax Data Analytics team discovered errors in how the automaker configured its tax decision engines. By fixing the problem, the automaker reduced its risk exposure.
Data & Analytics at KPMG Client Infrastructure
Other ERPs & Data Sources
KPMG Extracted Files Extracted Files Extracted Files
SFTP
Extracted Files Extracted Files Extracted Files
Analytics
alteryx Database Transactional & Master Data
ETLProcess
DaRT Extraction Process
ABAP
Rafiq Jalal Director, Tax Transformation and Technology KPMG Ignition Denver [email protected] 720-573-7029
© 2015 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. Printed in the U.S.A. The KPMG name, logo, and “cutting through complexity” are registered trademarks or trademarks of KPMG International. NDPPS 369026
