An error in a client report is not just an operational problem – it is a reputational event which causes the client to question what else might have been wrong in their reporting and snuck through the quality check.
For regulated firms, it can trigger a regulatory notification obligation. And correcting it – reaching all affected clients, issuing revised documents, logging the incident – is time-consuming and can be expensive.
Understanding where reporting errors come from is the first step to reducing them.
Where most errors come from
Data entry and manual assembly. The saying “there’s no good reporting without good data” is very true. The single largest source of errors in most reporting processes is the step where data is manually transferred from one system to another – from a portfolio management system to a spreadsheet, from a spreadsheet to a template, from an email attachment to a report. Every manual step brings with it the risk of error and / or delay. The format of the data too, is equally important. Being able to provide data files in a consistent and correct format, using agreed naming conventions, date formats etc. are all important to reducing errors and delays.
Performance and attribution calculation errors. Performance calculations involve multiple variables: gross or net returns, the correct benchmark series, the correct start and end dates, correct valuations and flows, the correct currency and so on. When these are computed manually the risk of systematic errors is high.
Even where the returns are undertaken by a specialist performance and attribution system, the room for error still exists. The importance of exact values, timings, weights, and aggregations, and the precision of the calculation are all absolutely key to avoiding errors. Typically, these returns are available after the more standard validation data is available. Having a system that can continue to process and workflow the rest of the report, whilst the performance and attribution are completed and validated, is helpful to achieving the agreed despatch dates.
Version control failures. A legacy process where multiple people may work on different parts of the same report, without a single controlled version, can regularly produce reports where the commentary references a performance figure that was subsequently amended, or where a prior cycle’s data has not been fully updated. More modern systems create a single version of the report that all contributors can access, and where values or returns are to be inserted into text or commentary, these are automated and not undertaken manually.
Template configuration errors. When templates are updated – for regulatory changes, rebrands, general evolution and improvement of the reports, or client-specific requests – changes that are not applied consistently across all relevant templates create a class of error that may not be caught by standard QA checks. Having a single or small number of templates eases this risk considerably.
Commentary inconsistencies. Commentary that refers to portfolio positions that no longer exist, or that quotes a performance figure that does not match the data in the report, creates both factual errors and credibility problems. Modern reporting systems allow for this type of data to be automatically updated, without manual entry.
Why error rates do not improve with good intentions
Firms that respond to a reporting error by asking teams to be more careful next time rarely see a sustained reduction in errors. The problem is not usually lack of care – it is a process that is structurally prone to error. Asking people to be more careful within a fragile process produces a temporary improvement followed by a return to baseline error rate.
Structural fixes that work
Automate data assembly and ingestion. Removing the manual transfer of data from one system to another removes the early source of data errors. A reporting platform with direct connections to your data sources should produce figures that match your portfolio system every time, without human intervention. An automated API works very well for data ingestion.
Flexible data and content delivery. Allow for the core report to be created, validated and flow through the workflow process while the more complex and time-consuming elements are created and checked – written commentary and performance attribution. Allow these elements to flow into the report ahead of the final checks without delaying the whole report.
Standardise calculation precision logic and display. Throughout the report define the level of precision and display. Whether large numbers are millions, thousands, or actual numbers, and define the number of decimal places displayed for values and percentages.
Implement automated QA checks. Range checks (is this figure within defined bounds, or averages of previous values etc.?), comparative checks (how does this compare with the prior period?), and completeness checks (are all required fields populated?) can be automated and run before any human review of the report. They may not catch every error, but they catch enough to materially reduce the review burden towards zero. Add more automated checks as your experience with the system and process grows.
Create a single controlled version. All production work should happen within a single platform, with a clear automated audit trail. If commentary, data and template work are happening in separate systems and assembled at the end, version control errors will continue.
Don’t make last minute changes. Carry them forward to the next reporting period and implement them there. Don’t try to rush them into the current report. It’ll likely go wrong and something may be missed.
Measuring progress
Track your error rate formally: how many errors per cycle, at what stage they were caught (before or after client distribution), and what type of error they were. Most firms that do this are surprised at both the actual rate and the patterns it reveals. The data is also essential for demonstrating to regulators and clients that you are managing the risk seriously.
Frequently asked questions
Do I have to notify the regulator if an error reaches a client?
It depends on the nature and materiality of the error. Minor errors with no financial impact may not require formal notification, but firms are generally expected to maintain records of client communication errors and may need to notify clients directly. Material errors – incorrect performance figures, incorrect charges disclosure, incorrect or missing risk statements or footnotes – typically require proactive client notification and may require regulatory notification. Always assess against your firm’s regulatory obligations and consult compliance.
What is an acceptable error rate in client reporting?
Leading reporting functions target zero errors reaching clients – meaning all errors are eradicated in the upstream process or caught and corrected before distribution. Any recurring error rate, however small it appears, indicates a process problem that warrants systematic investigation rather than acceptance as normal.
Should we run a root cause analysis every time an error occurs?
Yes, for any error identified. The immediate fix addresses the specific instance; the root cause analysis addresses whether the process is likely to produce the same error again. Without the latter, error correction is a recurring rather than a declining activity.