In the FDE delivery case, the official website of ChinaSoft International introduced the audit intelligence platform of an anonymous central energy enterprise, saying that the on-site team used large models for contract and business document element extraction, evidence correlation, and report drafting. The page is accompanied by customer reviews, but the customer name, specific launch date and original project documents are not disclosed. This article is based on public case studies by service providers and has not independently verified the effectiveness of the project.
A group of similar records, we need to first see how to relate them
The following is ChinaOPC’s independent analysis of data processing tasks and is not an actual audit matter for this client. Assuming that the system finds that the contract and payment records have similar amounts, they can be listed as candidate relationships for further review. Similar amounts alone cannot prove that the two documents must belong to the same business. You also need to find content such as number, object, period, etc. that can support the association.
The same business may also be split into multiple records. For example, the main contract, attachments, and follow-up documents each contain different information. When there is only one of them, it is easy to miss conditions in the generated explanation. Data sorting can present which records have been found, what each supports, and where evidence is still lacking, allowing professionals to continue checking.
When the search does not return a certain document, you should first understand the data coverage. It may be that the file does not enter the current range, or the name, scan quality, or association method may affect the search. Directly writing that the business was not found will turn the data gap into a conclusion that lacks basis.
Separate observed facts from questions to be confirmed
A useful analysis record can start by writing down the visible content of the source, and then list the relationships that need to be verified. For example, two dates are different, which is a visible phenomenon; whether the difference is reasonable and whether it affects specific matters needs to be judged based on the complete background. Models can help discover and sort out differences, but the subsequent professional judgment still needs to be the responsibility of the corresponding personnel.
When conflicts arise between materials, their respective positions and context can be retained to explain where the conflicts lie. If the system automatically selects a certain piece of material as the only basis in order to generate a smooth piece of text, the reviewer may not be able to see the original disagreement. It's often more helpful to leave a question open for inspection than to give a definitive answer too early.
When contracts, systems or regulatory provisions need to be quoted, the original text should be kept complete and accurate, and the explanation should be explained separately. The abstract can help with positioning, but the conditions, exceptions and limitations in the original text cannot disappear quietly in the translation. This article does not provide qualitative audit or legal judgment, nor does it regard AI output as the corresponding professional conclusion.
The draft report should allow the receiver to pursue further questions
The original case mentioned a draft report and a rectification list. When researching this type of application, you can observe whether each statement in the report can be traced back to the corresponding data: which content is already supported, and which is just a clue that needs further verification. The receiver should be able to supplement the question accordingly without having to second guess the basis from an entire paragraph of generated text.
If you plan to form follow-up matters, you can also write down what information you want to add, who you want to know from, and what you can't determine yet. The discovery of related records, the formation of matters to be reviewed and the completion of rectifications are different progresses and should be explained according to the actual situation. All subsequent work cannot be recorded as completed just because a draft has been generated.
When a small team researches enterprise information services, they can first select a type of repetitive organizing task with customer personnel with corresponding professional capabilities, and discuss whether the output is easy to review using a sample that has been approved for use and has removed irrelevant sensitive information. What is suitable for reference is how to connect the information and the problem. Business judgment and professional responsibility should still be clearly retained; this case does not mean that any size team can directly undertake a complete audit business.
Extended reading: How to use AI to extract contract elements while retaining the original position and How project delivery records form an evidence chain, compare the different roles of data excerpts, factual basis and work progress records.