Prudential regulatory reporting by MIFIDPRU investment firms – data quality review

Good and poor practice Published: 26/11/2025 Last updated: 26/11/2025

Our findings on the data quality of prudential regulatory reporting of MIFIDPRU investment firms. Including our expectations, good practice and areas for improvement.

1. Who this will interest

Our findings are relevant to FCA solo-regulated investment firms or groups in scope of the Investment Firms Prudential Regime (IFPR) and the MIFIDPRU sourcebook.

2. Executive summary

In our strategy 2025-2030, we set out our priorities for the next 5 years. A key focus for us is to become a smarter, data-led regulator. We want to be more cost effective and proportionate in how we collect and use firms’ data.

We are the prudential regulator for 36,000 firms. Timely, accurate and consistent prudential data helps us assess firms’ financial resilience. This allows us to prioritise our supervisory interventions, resulting in reduced harm to consumers and the wider market. We also combine prudential data with data on other key risk indicators to better understand firms and potential risks to consumers.

Poor quality data makes it harder for us to identify firms with weak financial resilience. It can mean we are not able to identify significant risks in a timely way. It can also indicate weak systems and controls at firms and can lead to poor consumer outcomes.

In January 2022, we introduced the IFPR to streamline and simplify prudential requirements for investment firms. In 2023, we provided industry feedback which included our concerns on the data quality of MIFIDPRU regulatory reporting.

In this most recent review, we found that most firms understand their reporting requirements – around 60% of firms passed all our data quality tests. We also saw good practice in reporting across time periods and cross-validation across returns.

However, we identified areas of improvement for firms:

  • Inconsistent reporting across multiple data sources.
  • Inaccurate implementation of reporting guidance.
  • Incorrect reporting of type of investment firm.
  • Incorrect reporting units and data entry issues.

3. What you need to do

Compare our findings to your firm’s arrangements to see if you meet our expectations. This will help you identify where you may need to improve your controls around regulatory reporting. It will also help you make sure your firm aligns with the relevant reporting provisions in MIFIDPRU 9 Annex 2.

We are not setting new reporting requirements or guidance. Our findings aim to help firms better understand our existing expectations, identify any issues and make improvements.
 

4. What we did

Our scope was MIFIDPRU regulatory returns submitted via RegData. We reviewed returns for the reporting periods from January 2024 through to March 2025, covering approximately 3,800 firms. In total we carried out 323,000 tests.

We tested firms’ data to see if:

  • It is consistent with the guidance in the MIFIDPRU prudential sourcebook.
  • It is broadly consistent with comparable data from alternative sources.
  • Changes in the value of data points over time fall within a credible range.

5. Findings

We found that most firms understand their reporting requirements within their prudential sourcebook. Around 60% of firms submitted data that passed nearly all our tests.

We found 30% of firms were making progress towards consistent and good quality reporting. While these firms had misreported at points, the issues were not persistent or systematic.

Around 10% of firms were not meeting their reporting requirements. We found that most of their submissions had recurring reporting errors. This shows fundamental weaknesses in those firms’ regulatory reporting systems and controls.

5.1. Areas of good practice

Consistent reporting across time periods

We compared quarterly data against the previous period, assessing plausibility and consistency of approach. We did not test every single data element. But we found a consistent approach by around 90% of firms.

Cross-validation across returns

Non-small and non-interconnected (Non-SNI) firms must report K-factor requirements in the MIF001 regulatory return. Those are quantitative indicators used to measure investment firms’ potential harm to customers, the market, and itself. This determines firms’ minimum capital requirements. The K-factor requirements are derived from firms’ submissions of the MIF003 regulatory return.

We found that 85% of K-factor requirements firms reported in MIF001 were accurately derived from MIF003 figures for the same period. This is encouraging. Misreporting K-factor requirements could result in firms incorrectly assessing the levels of capital they need to hold to meet their requirements. It can also give us a misleading view of a firm’s SNI versus non-SNI classification. 

5.2. Areas for improvement

Inconsistent reporting across multiple data sources

MIF007 requires firms to report on their Internal Capital Adequacy and Risk Assessment (ICARA) processes. We regularly find values in firms’ MIF007 regulatory returns that differ substantially from their ICARA documents.

It is not uncommon for some data to change. In particular, after the ICARA document is reviewed and approved by the firms’ governing bodies. But the data should be broadly consistent for the same period – unless there have been significant changes to firms’ business models.

Inaccurate implementation of guidance

We identified inconsistent implementation of the reporting guidance and requirements. One of the most common issues was in reporting the Own Funds Threshold Requirement (OFTR) in MIF001, and how this compares with the Own Funds Requirement (OFR) or the Transitional Own Funds Requirement (where applicable). Twenty percent of firms were reporting values that did not comply with the available guidance.

The OFTR amount should not be less than the OFR or the Transitional Own Funds Requirements (where applicable). In turn, OFR must be the higher of the Permanent Minimum Requirement (PMR), Fixed Overhead Requirement (FOR) and K-Factor Requirement. Calculating the OFTR correctly ensures firms are sighted on the level of capital they need to cover the risks associated with its activities and to facilitate an orderly wind-down where necessary. Incorrect calculation of this could result in firm failure and harm to consumers.

Firms should check their reporting to make sure their figures are plausible and in line with the guidance in MIFIDPRU 9.

Incorrect reporting of type of investment firm

Firms’ SNI or non-SNI status affects, but is not limited to, their regulatory reporting requirements.

We found firms leaving key fields blank in MIF001, particularly for the K-Factor Requirement. Firms meeting the threshold(s) as a non-SNI firm must calculate their K-Factor Requirement as part of their OFR. Leaving critical fields blank could mean a firm is incorrectly calculating its risk. This would give an inaccurate view of its capital adequacy.

Firms should read MIFIDPRU 1.2 to determine their SNI or non-SNI status and complete the appropriate fields as in the guidance in MIFIDPRU 9.

Incorrect reporting units and data entry issues

We saw firms reporting figures in the wrong units, often with extreme and implausible shifts in values between the different reporting periods. The patterns we saw indicate data issues in most cases.

We also saw some firms submitting identical data across multiple reporting periods. This suggests no change throughout the year, especially in MIF001 and MIF002. While this may be plausible, the strong likelihood is that firms have not updated the data before submitting it.

We also saw inconsistencies between annual (MIF007) and quarterly submissions. This was particularly the case for different units being used between different regulatory returns. All monetary figures reported in MIFIDPRU regulatory returns should be reported in Sterling and in 000s.

6. Next steps

We will begin emailing data quality notifications to firms. These notifications will highlight when a submission has data that fails at least one of our tests. The notifications will include the specific data points that have potential data quality issues. We are also exploring whether systems-level validation or field-specific ‘pop up’ guidance can be added to RegData.

We will share further detailed examples of the data quality issues we have seen in a future IFPR Newsletter. This is a regular policy update we share with firms. If you would like to be added to its distribution list, email [email protected] with the subject line 'Sign up'.