• Andreas Wiesner, Director |
  • Christian Krämer, Expert |

The smart combination of individual data models and further automation can generate considerable efficiency, quality and consistency gains in TPD generation. In the process, even an unnecessary part of internal reconciliations can be reduced.

Introduction – Challenges in common practice

In our blogs “Practical automation of IC transactions for TPD” and “Automation and analytics examples for TPD financials” we have covered specific topics of automation for TPD. However, Multinational Groups do not only face increasing compliance requirements regarding intercompany transactions and financials, because the TPD consists of many more components. 

Key aspects to consider when creating automated documents, especially with regard to the automation of the process in general and the standardization of templates, are explained in our blog "Automated TP Documentation" (see link below).

The main focus of this blog is on the processing of information, which is very time-consuming, recurring and involves a high level of internal communication, which is often very tedious. In addition, the information is often interlinked, which requires further internal agreements and approvals.

Practical building blocks of a smart, fully-fledged and combined TPD automation

By smartly combining individual data models and automations, you can achieve the highest gains in efficiency, quality and consistency for the generation of TPDs. Here are the eight typical building blocks of the TPD that can be smartly connected with each other:

  1. The information request list is a significant part of the TPD preparation process and often influences which text modules are shown in the final report, how and where. The degree of interaction with other information sources is very high. However, the typical degree of automation of information processing is very low. A structured information gathering process and request list template are very helpful for smart combined automation.
  2. The processing of intercompany transactions is typically very rule-based and can therefore be automated effectively. The level of interaction is medium. The time saving and increased quality and consistency is a decisive factor for automation.
  3. The preparation of financials and PLIs (P&L and balance sheet) are a significant part of the TPD and have a high degree of interaction, although their automation is often inexplicably low. The manual preparation of information and the high degree of interaction make the financials a time-consuming factor in TPD preparation.
  4. Benchmarking studies, which are an integral part of the TPD, can be integrated very well into the fully automated TPD process. The interaction with the transactions, but especially with the financials, is very high. The correct wording plays a decisive role in the verification of the at-arm's-length principle. There are also links to the service level agreements, which can be used to generate text modules automatically.
  5. FTE/HC data is also part of the smart, fully-fledged solution. The information is often collected centrally. With clear rules, FTEs/HCs can be consistently assigned to the corresponding functions. Also, the wording for (cross-boarder) reporting lines can be generated individually and automatically for the TPD.
  6. General market data and additional OECD requirements such as the top 5 customers or competitors can also be included in the smart automation. The degree of interaction is rather low, but the time savings are given when data is available.
  7. An overview of intercompany service level agreements or overviews of intercompany loans and their specifics have a medium level of interaction, but a high time-saving effect if the information is collected centrally. Here, quality checks in connection with other information are the most relevant.

Typical topics, questions and quality features that are clarified with it

Truly smart automation takes quality and consistency checks into account throughout the process. Any special cases should be flagged automatically. Typical points that can be clarified with such a model are the following:

  1. Have all affected text elements within the TPD been taken into account and updated?
  2. Have specific wordings that are interdependent been adjusted?
  3. Are the intercompany transaction data and financials shown correctly and does the at-arm's-length test fit?
  4. Have inconsistencies and quality deficiencies that were not otherwise very clear been highlighted?



The typical benefites for the automation of the above building blocks and combination of them are:

  1. Process acceleration through automation
  2. Efficiency increase in terms of time and resources used
  3. Automated assembling and reconciling of interactive information
  4. Reduction of errors through smart and interactive building blocks incl. consistent quality checks
  5. Clear transparency and full traceability of processed data and information
  6. Reduction of unnecessary internal communication regarding manual reconciliation processes for interacting data and information

Specific and individually dependent text modules within the TPD can be generated automatically with such a smart approach. In connection with a clearly structured TPD template, the entity-specific information can then be incorporated. At the push of a button, not only the information processing but also the TPD generation takes place.

Get started with your own case

In order to start, you need to identify the required input data and information. Secondly, elaborate the steps to get from input to the desired output required for TPD. And finally, define clear rules and logics that can be applied repetitively year by year for an automated, smart and combined data and information processing.