Case study

Automating 285 Fields: From Manual Entry to Production Workflow

A document and data workflow replaced repetitive manual entry with extraction, validation and review controls.

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Current state

285 fields, retyped by hand.

A financial-services business operating under regulatory supervision was preparing client documentation by reading values out of one system and typing them into another.

The work was not difficult. It was long, repetitive and unforgiving. Across the document set, 285 separate fields had to be populated correctly, each one read from a source record and entered by hand into a form.

Every one of those fields was a place where a person could transpose two digits. Most of the time they did not. The problem with most of the time is that in a regulated context, the exceptions are the only part anyone examines.

Waste

The cost was concentration, not time.

The hours mattered, but they were not the real expense.

Manual transcription at this volume demands sustained attention on work that offers no intellectual reward. It is precisely the shape of task human beings are worst at: long, uniform, and punishing of a momentary lapse. Skilled people were spending their attention on accuracy of copying rather than on judgement.

The second cost was that checking was as expensive as doing. Verifying 285 hand-entered fields is itself a long manual task, so in practice checking was partial, which meant confidence in the output was lower than anyone wanted to admit.

Future state

The machine types. The person signs.

The process was stabilised and written down before anything was built, which is the step that decides whether the rest survives.

Values are now read from the source systems, validated against explicit rules, and used to populate the documentation automatically. Where a value is missing, ambiguous or fails a rule, the workflow stops and surfaces it rather than proceeding with a guess.

A person still reviews and signs. That was a deliberate design decision rather than a limitation: in a supervised environment, the ability to show that a human approved the output, and to reconstruct what the system was given and what it decided, is worth more than the seconds the approval costs.

Every run leaves an audit trail whether or not anyone ever asks for it.

ROI

The gain is error elimination, not hours.

Hours saved are the easy number. The one that matters is the class of error that no longer occurs.

285

fields moved off manual entry

108/108

controls passing

100%

human approval before signature

Transcription errors from manual copying are now structurally impossible rather than merely rare, because no human hand copies a value between systems. The remaining risk sits in the source data and in the rules, both of which are explicit, inspectable and testable, which is a far better place for risk to live than in someone's concentration at the end of a long afternoon.

The reason this worked is unglamorous: the process was stabilised and standardised before it was automated. Had it been automated first, the result would have been the same inconsistencies produced faster and with nobody watching.

See back-office automation →

Common questions

Straight answers.

Does the system make any decisions on its own?

It applies explicit rules and stops when something fails one. It does not exercise judgement, and a person approves before anything is signed. The machine does the typing and the checking; the person does the deciding.

What happens when a value is missing or looks wrong?

The workflow halts on that item and surfaces it for a person rather than proceeding with a best guess. A workflow that never stops is not careful, it is just confident, and in a regulated context those are very different things.

Is this specific to financial services?

The pattern is not. Any process where values are read from one system and typed into another has the same shape and the same failure mode. Regulated environments simply make the cost of an error more visible.

Start with the workflow

See what can be automated.

Tell Astra where work slows down. We will map the system, its controls and the right human hand-offs.

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