Collective damage actions have already increased significantly and - not at least as a result of EU regulation - will become even more important in the coming years.
However, one challenge remains and is even gaining in relevance: the identification, quantification and proof of the damage incurred. Commercial practice has shown that obtaining information from large volumes of data and documents substantiating damages and presenting it in an evidential manner continues to be a major hurdle to the necessary substantiation of claims for damages.
Thus, it is often a long way for injured parties as well as lawyers and experts to extract the necessary data. In addition, gaps in the data basis regularly offer pleas for the defence side.
In many cases, the contents of the damage documentation are dealt with too late or not in sufficient depth. Thus, at the beginning of new damage compensation proceedings, the above-mentioned parties and, if applicable, also the litigation financiers often lack the basis for an assessment of the damage potential inherent in the individual purchases and receipts. This makes the evaluation of opportunities, risks and economic parameters difficult and unnecessarily delays decision-making processes, which in turn jeopardizes the satisfaction and commitment of the parties involved.
Success Module Documents Quick Check
With a compact document quick check, it is possible to make an initial assessment of the nature of the documents, the distribution of suppliers, documents, pages or even initial statements on the content of individual components of the invoices / documents. By means of quickly trained AI models and other tools, statements can be made about quantity structures, quality of the documents (visual, content), complexity of the layouts (long tail / fragmentation), relevance of the documents (document types), consistency of the data sources as well as possibly missing documents.
Depending on the scope of the project, it may also be necessary to process a small part of the documents with the appropriate data model in a proof of concept. This can then form the basis for mass evaluation and dedicated data extraction at a bindingly defined cost. The duration for the implementation of such a project can also be determined very precisely on these bases.
With our experience and AI-based IDP platform, we offer with Document Quick Checks partners and customers a fast, cost-effective and pragmatic solution to provide stakeholders with the required information very early in the respective process, leading to a fundamental understanding of the specific claim.
Key added values for a speedy and productive implementation are, for example, the automated recognition and grouping of layouts, the separation of batches into individual documents, the classification of document types, and the recognition of the information sought through speedy and efficient training of the AI modules.
With the help of this information, all parties involved can plan the overall project well and decide on its feasibility and chances of success. In addition, this can also lead to an early selection of the relevant documents and data and thus to a reduction of the volume to be processed.
Are you involved in the determination of damages claims?
Whether litigation financiers, experts/economists or lawyers - we support you in the use of artificial intelligence in damage claims. You can learn more about the topic here.
Conclusion: Less effort, more speed + quality
Use our mature technology and - based on many supported antitrust proceedings - our expertise to make your work easier and increase transparency in your overall proceedings. This will enable you to identify potential risks at an early stage and to achieve a solid and efficient level of coordination with all parties involved in the process right from the start.
In the first part of our series of articles, you can read about the other success components that support the assertion of claims for damages in antitrust proceedings. In the second part, we looked at the individual components of AI-based document processing.
Want to read more on the topic of AI use in antitrust and damages actions?
In the free white paper, we not only highlight the main challenges, but also present concrete practical solutions in detail.
*The white paper is written in German.