The Reconciliation Gap: Why Financial Close Remains a Human Problem in a Technology Age
The financial close is one of the most consequential processes a finance function runs. It is also, in most mid-market firms, one of the least well-supported. Decades of investment in front-office technology, risk systems, and regulatory infrastructure have left the close largely unchanged: a concentrated burst of manual effort, applied under pressure, by people who know the stakes and are working with tools that do not match them.
A 2026 study by Sixthfin and Odoxa, surveying 800 financial decision-makers across mid-sized and large UK companies, offers one of the most detailed pictures yet of how finance teams actually experience the financial close. The findings are striking. They do not reveal something unknown so much as quantify the scale of what practitioners have quietly lived with for years.
3–5 days lost per month-endcycle to manual reconciliation
97% of CFOs rely on ERP systemsfor account analysis
25% of firms complete accountanalysis with no IT tools at all
37% not very confident in thereliability of their figures
These figures carry particular weight in banking, insurance, and wealth and asset management sectors, where the consequences of reconciliation error extend well beyond an awkward board conversation. Regulatory capital calculations depend on accurate alignment between the subledger and the general ledger. NAV reporting requires precisely reconciled unit, cash, and valuation positions. CASS compliance demands demonstrable control over client money. In these contexts, a five-day manual close is not merely inefficient. It is a structural risk.
"Only 42% of CFOs consider that the management of the financial close in their company is very satisfactory." (Sixthfin / Odoxa, 2026)
The Infrastructure Mismatch
There is a tempting narrative that the reconciliation problem is simply one of under-investment, as though firms just need to buy a better tool. The reality is more nuanced and, in some ways, more challenging.
The Spreadsheet Trap
Many mid-market financial services firms are still running critical reconciliation processes on annual GL extracts and VLOOKUP-based workbooks. Shared files with no version control. Single-person ownership creates acute operational fragility when that person leaves or falls ill. Error rates that compound silently across entities.
The research confirms this is not a legacy of small firms alone. More than a quarter of companies complete account analysis and reconciliation without any collaborative tooling. The spreadsheet is not a stepping-stone. For many teams, it is the destination. And that destination has no audit trail.
The ERP Illusion
For firms that have graduated beyond spreadsheets, the ERP is typically the next step. SAP. Oracle. The major platforms offer reconciliation modules, and most CFOs point to them as their primary tooling.
But the research reveals a disconnect. The complexity of financial close is driven not by any single technical limitation but by a combination of factors: late collection of information from multiple sources, reliance on key individuals, difficulty aligning financial and operational data, and the persistent challenge of coordinating across entities with different GL structures. ERP modules were not built to solve these problems. They were built to record transactions. That is a fundamentally different task.
The result is a category of reconciliation challenges: intercompany matching across subsidiary structures, suspense account clearing, and portfolio-level three- and four-way reconciliation. These sit in the gap between what ERP can do and what enterprise platforms cost. Mid-market firms find themselves priced out of the latter and underserved by the former.
The Enterprise Platform Gap
The leading specialist reconciliation platforms, the names well known to treasury and finance technology teams, are extraordinarily capable. They are also sized and priced for institutions with nine-figure technology budgets and 12 to 18-month implementation timelines. For a mid-market insurer, a regional wealth manager, or a banking group operating across Southern African markets, these platforms are not a realistic option.
This gap is not new. What has changed is its cost. Settlement cycle compression under T+1 regimes is increasing daily break volumes. FCA scrutiny of CASS compliance has intensified. IFRS reporting requirements demand reconciliation evidence that manual processes cannot reliably produce at scale.
"The complexity of the close is driven by human and organisational factors: late collection of information, reliance on key individuals, and multiple files." (Sixthfin / Odoxa, 2026)
What AI Can and Cannot Do
It would be easy, and misleading, to position artificial intelligence as the solution to the reconciliation problem. The research is instructive here. More than 75% of CFOs say they use AI as a closing tool, whether for improving data reliability, detecting anomalies, or automating repetitive and time-consuming tasks. The appetite is real.
But appetite is not an outcome. AI works exceptionally well at specific, well-defined tasks within a structured data environment: pattern-based transaction matching, anomaly flagging against known rules, and exception classification where the categories are clear. These capabilities genuinely accelerate certain parts of the reconciliation workflow.
Where AI struggles, or more precisely where organisations struggle when deploying AI, is in the messiness that precedes clean data. A matching algorithm cannot reconcile positions that have not been correctly normalised across multiple GL structures. A natural language interface cannot surface breaks that are buried in a shared workbook with no consistent schema. Intelligent automation requires intelligent infrastructure to run on.
The accountant of the future will need to be analytically fluent
The research identifies a clear professional implication: the dominant skill requirement for tomorrow's finance professional is analytical thinking combined with the ability to adapt to and leverage new technologies. This is not about coding. It is about the capacity to interrogate data, challenge outputs, and maintain professional scepticism even when, especially when, automation produces a clean result. That professional evolution cannot happen if the team is spending five days a month manually reconciling subledger balances in Excel.
The Human Cost
Numbers often obscure what they represent. Behind the statistic that the financial close has a significant impact on the workload of 97% of accounting teams is a more specific reality: experienced finance professionals spending their highest-pressure periods doing work that offers no opportunity for judgment, insight, or strategic contribution.
The research is unusually candid about this. The sources of stress during close include deadline pressure, incomplete or unreliable information, lack of automation, and dependence on colleagues who may themselves be overwhelmed. The emotional labour is not incidental. It is structural. It is baked into a process architecture that has not fundamentally changed in decades.
Resignations accelerate this fragility. When a senior reconciliation analyst leaves, they take with them the institutional knowledge encoded in their spreadsheets and undocumented matching logic. The process does not just slow down. It stops.
For CFOs seeking to retain talent and build resilient teams, this is not a peripheral concern. The research finds that only 42% of financial decision-makers are highly satisfied with their organisation's financial close process. That dissatisfaction flows in both directions: from leadership frustrated by the opacity and risk of manual processes, and from teams exhausted by the gap between what they are capable of and what they are asked to spend their time doing.
A More Efficient Path to Close
The path forward for mid-market financial services firms is not a single technology decision. It is a process re-architecture, one that addresses the full chain from data ingestion through exception resolution and regulatory evidence.
Several principles tend to characterise organisations that have meaningfully improved their close performance:
Start at the data layer: The most common root cause of reconciliation delay is not the matching logic. It is the data arriving late, in inconsistent formats, from systems that were never designed to communicate with each other. Any meaningful improvement begins with reliable, automated ingestion and normalisation across all relevant sources: ERP, core banking, custody platforms, fund administrators, and LOB systems.
Design for exception, not for volume: The goal of automation is not to eliminate human involvement in reconciliation. It is to ensure that human involvement is applied where it adds value: reviewing genuine exceptions, investigating unusual patterns, exercising professional judgement on ambiguous breaks. A well-designed reconciliation workflow routes clear matches automatically and surfaces true exceptions with the context needed to resolve them quickly.
Build the audit trail in, not on: Regulatory evidence for CASS, Solvency II, and IFRS should not be an afterthought assembled from email chains and spreadsheet tabs at reporting time. It should be a natural output of the reconciliation process itself: automated GL postings with complete financial lineage, segregation of duties enforced by workflow, and exception resolution documented in real time.
Right-size the solution: The mid-market does not need enterprise platform complexity. It needs a robust, proven reconciliation capability that integrates with existing systems, deploys without 18-month timelines, and can be maintained without permanent IT dependency. The technology exists. The challenge is finding implementations that are genuinely built for the scale and budget of mid-market financial services, not enterprise tools with features removed.
Conclusion
The Odoxa research is a useful mirror for an industry that has often treated reconciliation as an operational inconvenience rather than a strategic risk. The data suggest that the status quo is not just inefficient. It is fragile, costly in human terms, and increasingly misaligned with the regulatory and competitive environment in which mid-market financial services firms operate.
The question for CFOs is not whether to modernise the reconciliation function. The compression of settlement cycles, the intensification of regulatory scrutiny, and the professional expectations of the next generation of finance talent have already answered that question. The relevant question is how to do it in a way that is proportionate, sustainable, and genuinely fit for purpose.
The firms that will lead on financial close in the next decade are not those with the largest technology budgets. They are those who understand the reconciliation problem clearly enough to solve it precisely.
That clarity starts with an honest assessment of where manual processes are creating risk, where automation would unlock genuine capacity, and where the right partner can bridge the gap between what enterprise platforms offer and what mid-market firms actually need.
About Digiata
Digiata is a financial technology partner with 25 years of experience in financial services transformation. Headquartered across Johannesburg, Cape Town, and London, Digiata designs and delivers reconciliation, close, and data automation solutions for banks, insurers, and wealth and asset managers. Our Full Chain Reconciliation capability is purpose-built for mid-market financial services firms seeking enterprise-grade reliability without enterprise-scale cost and complexity.
