Phase 2 - Future finance demonstration

Continuous Accounting and Close Engine

Move from monthly close activity to continuous accounting: recognition closer to underlying activity, embedded daily controls, rules-based automation, and month-end as confirmation, not creation.

Business problem: Controllers discover issues too late because journals, reconciliations, intercompany, controls, and evidence are validated late in the cycle rather than as operational activity occurs. Open JSON contract Back to foundations

● Live close-impact runtime · ValueEventRecord-backed

Impact events: 4 Reportable value: $8,413,750 Measured: $8,200,000 Avg confidence: 88% Case: CASE-ACCRUAL-8200

Impact	Value	Runtime basis	Provenance
Financial exposure controlled	$8,200,000	Aggregated from accepted-service amount and controller-attested accrual ValueEventRecord rows	◆ Computed
Manual effort avoided	50 hours	Derived from the human_effort_augmentation ValueEventRecord calculation_outputs for evidence-search and journal-prep effort.	○ Illustrative
Close delay reduced	0.7 day	Derived from the productivity_improvement ValueEventRecord calculation_outputs for critical-path delay movement.	○ Illustrative
Control improvement	$120,000	Aggregated from SOX-evidence / policy-pinning ValueEventRecord rows	◆ Computed

Computed from close-impact ValueEventRecord rows (organic runtime rows); effort/delay metrics are ledger-derived from each row's calculation_outputs.

Runtime Hardening Proof

Execution evidence from Enterprise Decision Runtime service

This panel is generated from runtime service functions on each request: event correlation, policy simulation, learning metrics, agent guardrails, decision trace, and audit package export. It closes the view-vs-system gap by showing the platform executing, not only describing architecture.

7registered agents

5registered policies

1correlated signal(s) from 3 events

$450.0Kpolicy simulation amount

100.0%human acceptance over 2785610 decided executions (90d)

5825088decision memory records

BLOCKbad-data guardrail result

route_to_human_supervisoragent failure fallback

Live event correlation

SignalPriorityImpactEvent IDs

sig-2efe089ec8P1$1.4Mevt-001, evt-002, evt-003

Policy + guardrail hardening

Control	Runtime value
Policy	human-approval-policy
Prior threshold	$50.0K
Simulated threshold	$100.0K
Outcome	escalate
Approval volume change	-18%
Guardrail failures	missing_evidence, low_source_confidence, writeback_requires_human_approval
Hallucination guard	evidence_required_before_recommendation

Replay + audit export

Artifact	Value
Audit package	audit-97ab17991395
Integrity hash	c80fd1aea51cec3d76a8d2e6346938acd1938531f544f8f3f7fd3917f1d6c98c
Regulatory export ready	True
Trace steps	10
Runtime chain	Signal -> Context -> Ontology -> Policy -> Evidence -> Decision -> Governance -> Action -> Replay -> Learning

Runtime APIs

Endpoint
/api/finance-foundations/runtime-proof
/api/finance-foundations/continuous-close-engine/runtime-proof
/api/iaf/enterprise-decision-runtime/learning-metrics
/api/iaf/enterprise-decision-runtime/agent-guardrails
/api/iaf/enterprise-decision-runtime/policy-simulation
/api/iaf/enterprise-decision-runtime/event-correlation

Hardening stance: agents fail closed to human supervision on missing evidence, low source confidence, or write-back attempts. Learning is measured, replay-backed, and cannot change policy or autonomy without approval.

Open Enterprise Decision Runtime Open runtime proof JSON

North Star runtime outcome

Financial recognition, controls, journals, reconciliations, and evidence are continuously formed so close becomes confirmation rather than creation.

Core components

Component	Capability
Close Readiness Scoring	0-100 score across journals, reconciliations, intercompany, accruals, controls, exceptions, and evidence.
Continuous Accounting Principles	Recognition-at-event, embedded exception-based controls, rules-based automation, and month-end confirmation are explicit runtime dimensions.
Daily Accrual Service	Detects missing accruals, late costs, estimate drift, and evidence gaps throughout the month.
Daily Reconciliation Service	Runs subledger vs GL, IC vs IC, cash vs bank, and BlackLine matching checks continuously.
Journal Validation Service	Checks policy, materiality, risk, SoD, evidence, and source lineage before posting or approval.
Continuous Controls Service	Executes preventative and detective controls daily and stores evidence during processing.
Exception Detection	Missing journals, unmatched balances, late submissions, reconciliation gaps, and evidence gaps.
Close Forecasting	Predicted close date, confidence, blocker drivers, and critical path.
Controller Command Center	Readiness, blockers, predictions, actions, owners, and replay.
Continuous Close Timeline	Current close state, future risk, and intervention effect.

Success metrics

Metric	Target
Close effort reduction	50% target
Close acceleration	30% target
Predictive accuracy	80% target

FP&A deck alignment

Target operating-model theme
Continuous Accounting
Recognition moves closer to the underlying activity
Exception-based controls
Rules-based automation
Month-end becomes confirmation, not creation
Month-end becomes validation
Daily actuals
Automated reconciliations
Embedded Controls

Agent family

Agent	Purpose
Close Readiness Agent	Computes readiness and critical path.
Reconciliation Agent	Detects reconciliation gaps and aged breaks.
Journal Completion Agent	Finds missing, unusual, or unsupported journals.
Intercompany Agent	Detects mismatches and paired-entry issues.

CFO Continuous Close Command Center

The foundation engine backs the validation command center: Close Readiness, Balance Sheet confidence, P&L confidence, Cash Flow confidence, Open Exceptions, and Expected Variance are formed from financial events, reconciliations, accruals, provisions, controls, evidence, and certification state.

Close Readiness

Weighted readiness across journals, reconciliations, intercompany, accruals, controls, exceptions, and evidence.

Expected Variance

Forecasted difference between current financial position and expected month-end outcome.

Controller certification

Certify / do not certify state based on open exceptions, policy violations, evidence gaps, and unresolved variances.

Finance Digital Twin

Actuals plus deterministic accruals plus probabilistic estimates produce a replayable current financial position.

Workiva reporting evidence readiness

Continuous Close prepares Workiva-style statutory and reporting evidence continuously, not after month-end. Journal, reconciliation, intercompany, close-task, approval, and ICFR evidence are linked to controller review and replay before close sign-off.

Workiva package

Reporting evidence pack, commentary, certification, and control owner status.

Controller gate

Material journals and judgment items require controller approve / reject / escalate.

Audit evidence

Source records, policy result, BlackLine state, approval trail, and replay ID.

Close readiness

Workiva readiness contributes to close risk and CFO confidence score.

Proof links

Surface	Route
Hybrid Finance Simulator	Open
Continuous Close Intelligence	Open
Close Readiness Mission	Open
R2R Mission	Open
Replay Center	Open

API contract

Endpoint
/api/finance-foundations/continuous-close-engine
/ui/continuous-close-intelligence
/ui/close-readiness-mission

Validation questions

Question
What is close readiness now?
Which events moved recognition closer to underlying activity?
Which exception-based controls are active today?
Which journals or reconciliations are blocking readiness?
What happens if a late journal is injected?
Can the readiness change be replayed?