Finance leaders at a growing financial services group were stuck between two pressures: leadership and investors wanted fresher numbers and scenario answers, while compliance demanded fewer errors and a defensible audit trail. Spreadsheets and rule-based monitoring produced false alarms, manual closes ate a week each month, and tax and regulatory opportunities were easy to miss. We delivered an AI-assisted planning and compliance layer integrated with accounting, CRM, billing, and banking feeds—automating reconciliation and reporting while keeping expert review in the loop for material decisions.
The close process took nearly a week every month. Analysts spent dozens of hours on categorization, reconciliation, and report assembly instead of advising the business. Forecasts were annual artifacts outdated within a quarter. Compliance tooling flagged so many false positives that teams ignored alerts until something real slipped through—or spent nights on manual reviews. Tax credits and regulatory filings depended on quarterly scavenger hunts through records. Investors and boards increasingly asked for scenario answers the team could not produce without rebuilding models from scratch.
We followed the pattern that works in regulated finance: automate the repeatable, escalate the ambiguous. With FP&A and compliance leads we prioritized flows where speed and accuracy both matter—close, cash and revenue forecasting, and monitoring. Each automation shipped with golden scenarios, approval gates, and logging so auditors could reconstruct any system-assisted decision. Pilots ran on one business unit before portfolio expansion, matching how the organization already managed risk.
Connected data pipelines pull live feeds from banks, billing, CRM, and the general ledger into a unified financial view. Machine learning handles transaction categorization, reconciliation, and anomaly surfacing; natural-language interfaces let leaders ask for runway, variance, or board-ready summaries without exporting to slides. Forecasting uses current performance, seasonality, and selected market signals so teams can re-forecast quarterly—or faster—instead of waiting for a static annual model. Scenario modeling tests hiring, rate, and demand shifts without rebuilding spreadsheets. Compliance monitoring prioritizes high-risk patterns and documents rationale, cutting noise from legacy rule engines. Experts review and approve material outputs before they reach investors, regulators, or the board.
Four AI-assisted capabilities—each with clear human sign-off where judgment or regulation requires it.
Matches transactions, flags exceptions, and prepares close packages—targeting an 80% reduction in manual bookkeeping effort and close cycles measured in hours instead of days when data quality allows.
Updates revenue, expense, and cash projections as CRM and billing data change—supporting quarterly or rolling forecasts and board-ready narratives backed by traceable inputs.
Runs best-, base-, and stress-case models on hiring, pricing, and market assumptions so teams answer “what if” in minutes—not weeks of spreadsheet rework.
Scans records for regulatory risk and overlooked credits, reduces false-positive fatigue from rule-only systems, and routes edge cases to specialists with evidence attached.
How we combined automation with the oversight financial regulators and investors expect.
Integrate banks, billing, CRM, and GL early so forecasts and monitoring reflect what is happening now.
Measure close duration, error rates, and forecast freshness—the outcomes boards and auditors care about.
Stress hiring, rates, and demand before decisions harden—especially in volatile rate environments.
Automation drafts and prioritizes; people approve filings, investor communications, and policy exceptions.
Model version, inputs, rationale, and approver captured so compliance can reconstruct the path.
“We did not hire AI to replace judgment—we hired it to give our people time to use it. Closes are faster, forecasts are current, and compliance actually trusts the alerts again.”
We will tailor a roadmap to your constraints, compliance posture, and platform landscape.
