Rules Upon Rules Upon Rules

The Hidden Cost of Accumulated Logic in Enterprise Processing Chains

In organisations, especially in the financial sector, the integrity of reported numbers is rarely the core issue. The real challenge is understanding how those numbers came to be. Over decades, financial institutions and other complex enterprises have constructed multi-layered processing chains in which data moves from source systems to data management layers, onward to ledgers, and eventually into management reporting, planning, and forecasting tools. Along that journey, transactions encounter countless rules: adjustments, allocations, enrichments, transformations, overrides, and exceptions. Each rule may be defensible in isolation. Their accumulation, however, becomes a source of opacity.

In many medium and large financial services organisations, data processing illustrates this phenomenon vividly. Data is ingested from many origins: operational systems, product platforms, external feeds, and pushed through data management layers whose internal machinations may be only partially understood by current staff. From there, transactions are posted and subsequently redistributed downstream, where additional systems apply further business rules. Eventually, by the time the information reaches a reporting or planning platform, the organisation finds itself asking a familiar question: “I’m sure the number is right, but how did we arrive at it?”

This loss of transparency is not a sudden failure. It accumulates gradually over time. Systems that have been in operation for many years bear the marks of countless business decisions, regulatory changes, operational incidents, and tactical workarounds. Ownership of individual rules becomes blurred as people rotate out of roles. Reference data libraries expand continuously. Business groups introduce new logic at various points along the chain, sometimes formally, sometimes informally. Robotic process automation introduces yet another layer of implicit rule execution. And because each change is small, the organisation seldom confronts the macro-level complexity it is unwittingly building.

Layers built over time. Each logical, each defensible. Together, increasingly opaque.

The instinctive response is to invoke “strong data governance.” Governance is necessary but not sufficient. Governance alone cannot overcome the entropy of complex environments if the organisation lacks a set of deeper principles to anchor simplification and accountability.

Several fundamentals can help.

First, organisations must treat rule logic as a first-class asset. That means cataloguing rules explicitly, assigning clear ownership, and maintaining the catalogue with the same discipline applied to code repositories. If a rule cannot be justified, traced, or owned, it should be questioned.

Second, design for transparency. Systems should not merely apply rules; they should log them in a structured, queryable, auditable form. Data lineage should be engineered, not reconstructed after the fact.

Third, push decision-making upstream. Many downstream rules exist only because upstream systems were not capable of performing required classifications or adjustments. As modernisation progresses, organisations should resist rebuilding downstream compensating logic and instead migrate business rules to the earliest feasible point in the chain.

Fourth, adopt a simplification mindset. Rationalisation is not a one-off project; it is an ongoing discipline. Rules should expire unless refreshed. Default sunset dates force re-validation rather than silent perpetuation.

Then there is the question of how to “run the broom through the cupboard” during modernisation. Modernisation offers a rare moment to pause, examine, and simplify, but the unwinding effort is undeniably large. The only viable approach is incremental: identify value chains end-to-end, prioritise those with highest impact or highest risk, and systematically decompose the rule sets. Techniques such as rule mining, pattern detection, and lineage reconstruction can accelerate the work, but executive sponsorship and disciplined programme governance are essential.

Ultimately, the risk is not that organisations get the numbers wrong, it is that they no longer understand the journey those numbers have taken. Transparency is not merely a control requirement; it is a precondition for trust. Modernisation will not succeed if it simply re-implements decades of accumulated logic. It must also confront, and intentionally reduce, the layers of rules upon rules upon rules.

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