One of the most time-consuming parts of financial consolidation

isn't producing reports, it's preparing the data so those

reports can be trusted. Every close, new local

general ledger accounts appear that haven't been mapped to the group chart of

accounts. Someone has to identify those accounts,

research how similar accounts were mapped previously, make a

recommendation, and then import those mappings before

consolidation can continue. That's exactly what the local account

mapping agent automates for you. Here, we're looking

at a local account mapping workflow.

Instead of manually reviewing hundreds or even

thousands of local accounts, the controller simply

launches the board controller agent.

The agent begins by reviewing the current reporting context,

confirming the entity, scenario, and reporting period

so it knows exactly which accounts need attention first.

Before making any recommendations, the agent confirms the

scope of work. This is an important governance step.

Rather than making assumptions, the controller agent verifies

exactly which reporting context it should analyze before

proceeding. Once confirmed, the analysis

begins automatically. Traditionally, this

process is entirely manual. A finance user would

export the mapping tables, compare them against

unmapped accounts, search prior reporting periods,

review similar entities, and determine whether an existing

mapping could be reused. Depending on the volume of

new accounts, this can consume hours during the close process.

Instead, the board controller agent performs those same

investigative steps automatically for you.

It identifies every unmapped account,

validates that list matches what's currently shown in the

application itself, and begins researching historical

mappings across previous periods and similar

scenarios. As the analysis is completed here, the

board controller agent explains exactly what it found.

First, it validates the list of those unmapped local accounts.

Next, you can see that it's checking whether those same local

accounts have already been mapped elsewhere in

previous months or in different planning scenarios.

Historical mappings become one of the strongest indicators for a

recommended group account. Rather than producing a black box

answer, the board controller agent shows reasoning as

it builds those recommendations for you.

If the available evidence is strong, it will recommend a mapping.

If the confidence is lower, the board controller agent clearly

tells the user here where additional review is needed.

That type of transparency allows controllers to remain in

control for the final accounting decisions they're making

during a financial consolidation and close process.

Once the analysis is complete, you can see here that the board

controller agent produces a finished mapping table.

Instead of researching every single account individually,

finance now reviews a curated set of

recommendations. The user can quickly validate the

suggestions, paying particular attention to any

items where the board controller agent has indicated lower

confidence. The agent accelerates the work, but

the controller always makes the final approval.

Once approved, the recommendations flow directly

into the existing smart import process.

The generated mapping table is now copied into the

smart import template and uploaded back into the planning

application itself. No new workflow, no new

governance model. The board controller agent

accelerates the work that's already part of your

financial close process. For controllers, this

value is straightforward. Instead of spending valuable close

time researching repetitive account mappings, finance

teams receive intelligent recommendations based on

historical accounting decisions.

The result is a faster close, less manual

work, more consistent mappings across reporting periods,

and complete visibility into how every recommendation was

made. The board controller agent handling local account

mapping doesn't replace finance judgment.

It amplifies it, allowing finance professionals to spend

less time searching for answers and more time ensuring

financial accuracy.