A few days ago I posted that we had accomplished our goal of making the audit reports available for large accelerated filers on a timely basis. I promised in that post to describe how to use those audit reports with our application. In this post I describe those steps.
First you have to access the audit reports. This is accomplished by submitting a request file with the CIK, YEAR and PF of the source document (in this case the 10-K). Since the requirement to disclose CAM only applies to large accelerated filers with FYE ending after 6/30/2019 it could be tricky. Here is a link to the latest model request file which lists the CIKs of all registrants who meet the criteria and who have released a 10-K since the implementation date (CAM_REQUEST_LINK). For more direct instruction on how to download the actual audit report please review this blog post. For this post I will begin assuming you have already downloaded the audit reports. If you need those instructions – visit this post.
When you have finished downloading the audit reports they will be stored in the directory you specified in the ExtractionPreprocessed user interface. Each audit report is an independent document and is named CIK-RDATE-CDATE-F##-22.htm. Where the CIK is the Central Index Key of the issuer. The RDATE is the date the 10-K filing was made available on EDGAR. The CDATE is the balance sheet date. The two digits following F are the last two digits of the original filing accession number and the 22 represents our internal text artifact number for the audit reports.
If you want to review these documents individually – select the SmartBrowser feature on our software and navigate to select the directory that has these artifacts. The SmartBrowser will load the list of files and provide a list of the CIKs that are present in the left panel. You can select any individual CIK to review that document or begin at that particular point to move forward.
However, if you would rather use the full features of our platform with these opinions you need to index them. To prepare for indexing you need to create a new directory on your computer where the audit reports can be saved and the index can be created. In this example I am creating a new directory in F:\myTemp\DEMO_CAM_INDEX. Once the directory has been created select Create Index from the Indexing item on the menu bar
When the Create Index panel loads simply select the directory that has the original audit reports as the Source Files Directory to Index. Select the directory you created for the destination as the Destination Directory and then select the Create Index button.
The indexing process will begin – there will be some messaging as the indexing progresses – including the file that is being processed and at the steps when the index has to pause to save the partial indexes. When complete the application will report Indexing Complete.
When you hit the Close button the application focus will switch back to the main component. However the active Index Library will switch from the library you were using to the directEDGAR_Custom library. Your newly created index will be the last index in the list of custom indexes.
Select the index and start searching – you can now use all of the features of our application that are applicable. For instance – suppose we want to identify all audit reports that mention revenue recognition: a great initial search would be “revenue recognition”
As you notice in the screenshot – we have not injected any of our standard meta-data into the audit reports yet – that is why the company name is not yet displayed in the search panel. We will make the code changes so this happens automatically in the next two weeks. When that is done we will re-do these initial audit reports so the name is visible in the search panel and is reported in the Summary or Context extractions you might run.
To give you a quick example of using our platforms broader feature set with these artifacts I will quickly walk you through the process of extracting and normalizing the auditor tenure. I know that tenure is generally reported with language similar to We have served as the company’s auditor since YYYY. To find that language I am just searching for auditor since. However, before I do that I am going to adjust the span of the ContextExtraction to five words – I want to minimize the noise in the output. From the File menu select Options. . .
From the Options panel – Context is the first item. Select Item and then replace the current value with the number 5 and make sure the Words radio button is selected.
Once you have adjusted the span – hit the OK button and then from the Normalization menu item select ContextNormalization. There are three parameters to specify. First, since we are working with the search results displayed in the application select the radio button next to Current Results. You also need to specify an output directory – two files will be created and saved in the directory that you specify/select. Finally you need to describe the nature of the normalization.
In this case we need the number that follows the string auditor since and we want to save it in a column with the heading tenure in the results. When you have specified the parameters hit the Okay button. When the application closes the ContextNormalization panel there will be two new files in the folder that you specified.
The FileToProcess.csv has the context from the search – the file with the date-timestamp appended has the results after the context has been normalized.
As you can see in the image above – the auditor tenure has been normalized from the context and is reported in the column cleverly labeled tenure.
We are in the midst of revamping our audit fee data and will be adding tenure as a field to that data (as well as the auditor name). We will also work on linking the fee data with the audit reports so stay tuned for more updates.
