The Accuracy Dilemma

As an Asset Manager, what comes to mind when you think about regulatory reporting?  

When the next regulatory update requires adjustments to your reporting procedures, are you confident in your current capabilities, or are you struggling to keep up with past updates? If you find yourself in the latter category, rest assured, you’re not alone, but finding yourself in this situation time and time again isn’t sustainable and can expose you and your organisation to considerable risk. 

Regardless of your situation, it’s essential to consider what constitutes good and accurate reporting. For common European templates like the EMT, EPT, and EET, FinDatEx provides guidance on the following types of data: 

• mandatory,  
• conditional, and  
• optional data.  

Regular updates to these template versions reflect evolving market practices, make corrections and clarify any ambiguities that have arisen in practice, as seen recently with the PRIIPs KIDs Transaction Costs. 

Wouldn’t it be helpful to have guidance to check your file’s content before finalising and issuing it to the market, ensuring consistency, accuracy, and data integrity? 

For years, we’ve been assisting the industry with online validators that provide instant feedback on various data standards, such as FinDatEx, openfunds, and Document Metadata. When standards are updated, our regulatory data specialists apply their extensive experience to translate regulations into tangible data validation rules. 

In cases of ambiguity, you face a dilemma: apply relaxed rules and risk poor data quality, or adhere strictly to guidelines and risk being seen as too rigid. Our experience shows that starting with strict adherence to industry standards is the best approach.  

Here’s why: 

Expert Recommendations

Industry working groups, including FE fundinfo, have meticulously developed these guidelines to help the industry stay compliant. 

Market Adaptation

Over time, market adoption will reveal if requirements are too rigid, leading to necessary adjustments in the templates. 

Data Management Principles

It’s easier to relax validation rules over time than to tighten them, which would require extensive data cleansing. 

There is a need to anticipate reactions from both, information senders and recipients. Senders may struggle initially but will learn to meet the standards, ultimately delivering more complete and accurate data. Recipients can in turn trust the high quality of the validated data they receive. 

A win-win for all.