Automating Aggregate Value Benchmarking

Tracking, monitoring and auditing your critical metrics by automating aggregate value #benchmarking.

A critical initial step in #auditing of #financialreport is to compare financial indicators to a baseline group or standard classified #indices . This is important for auditors to gauge whether the client company is generally operating or churning results within the expectation of its peer companies or showing unusual behaviour. This approach is also common in #statistical and #economics summary & comparative analysis, examples of benchmarks are #ftse100 and Nasdaq #nasdaq100 indices.

Often, lack of automation meant practitioners are forced to apply only a couple of grouping or class values instead of sequentially comparing indicators to various aggregates which provide different scenarios or decision hungry information. Further, it is difficult to assess comparatives when an entity is not listed on the #stockexchange nor required by regulation to publish audited financial reports.

A suggested approach to generating credible benchmarks is to produce statistical aggregate such as #mean or #median values for the related class of the entity. Example, generate aggregate values for all Banks in the 6032 class of companies in the #ISICcode and compare the values and their trends to that of the entity. This can be done in a multiple of ways;

Compare Entity value to all companies in the class code

Compare to the domiciled country

Compare to values of certain fiscal year or

Compare to the aggregate of the entity in question.

There are a huge number of options available to develop and generate credible and consistent benchmarks.

MDY Analytics?designs, develops and deploys data science analytics and machine learning solutions, for more information check?https://mdyanalytics.com/?or email [email protected] MDY Analytics