CapabilityFinance & Risk Management
AI-Native Finance & Risk Management
See profit and cash clearlySpot exceptions sooner
Revenue is growing, so why isn't profit keeping pace? Which receivables need attention, and which payment needs another check? ActelosAI connects finance data, business knowledge and AI to help teams explain performance, prepare cash plans and ground important decisions in evidence.
AI-Native use case preview
Example question
Revenue is up, so why isn't profit keeping pace
Align sales, costs and expenses. Use reproducible models to separate volume, price, mix and cost effects, while AI gathers business evidence and flags variances worth investigating.
Analysis preparation time · Unexplained variances
Example question
Where could a cash shortfall emerge in the coming weeks
Connect receivables, payables and cash plans, then compare receipt and payment scenarios using agreed assumptions. AI explains potential gaps and lists the collections and spending that need confirmation.
Cash forecast error · Shortfall warning lead time
Example question
What needs another check before this payment
Check invoices, payment records and payee details for potential duplicates and mismatches, with links to the source records. For sensitive materials, explore local, read-only review with FAW.
Total exception review effort · Evidence traceability
Business value
Measure AI's value in finance outcomes
From AI-assisted reconciliation and collection priorities to internal audit preparation, track changes in repetitive work, cash conversion and review efficiency.
Reduce reconciliation effort
−80%
Time spent on a specific bank reconciliation task
Use AI to help organize and compare data, giving teams more time to explain differences and review exceptions.
Reference note
Accelerate collections
−20 days
Days sales outstanding (DSO)
Combine AI prioritization, cash application and coordinated follow-up to focus attention on the issues holding back collections.
Reference note
Speed up risk preparation
≈−20%
Time spent in the internal audit planning phase
Let AI retrieve relevant material from current policies, templates and procedures, reducing repeated searches and preparation rework.
Reference note
Figures come from specific cases and studies and are for reference only. Actual results vary with business and data conditions.
AI use cases
Six ways to bring finance closer to the business
From explaining profit and managing cash to reconciling differences and finding exceptions. These are AI-Native applications we can design and validate around your business, data and existing systems.
Connect profit changes to business drivers
Which products, customers or channels are changing profit
Break down revenue, cost and contribution changes on a consistent basis, separating price, volume, mix and expense effects. AI links orders and business records to draft explanations with sources and questions for review.
- Connected data
- Revenue by product, customer and channel; cost and expense details; budgets and business records
- What it enables
- Profit variance analysis, contribution comparisons and draft explanations
- Business analysis preparation time ↓
- Unexplained variances ↓
Keep forecasts in step with the business
Orders and costs have changed, so what should change in next quarter's plan
Bring order, price, cost and capacity assumptions into rolling forecast models and compare scenarios. AI explains version changes, sensitive drivers and missing evidence to support discussions between finance and the business.
- Connected data
- Actual results, open orders, business drivers, budget versions and scenario assumptions
- What it enables
- Rolling forecasts, scenario comparisons and explanations of assumption changes
- Forecast error on a consistent basis ↓
- Scenario preparation time ↓
Focus collection efforts where they matter most
Which receivables need attention today
Use aging, payment behavior, disputes and payment promises to prepare priorities. AI brings together customer communications, open issues and draft messages to help teams understand why payments are late.
- Connected data
- Receivable details, receipts and cash application records, payment promises, disputes and communications
- What it enables
- Collection worklists, dispute summaries and draft communications
- Days sales outstanding ↓
- Past-due receivables share ↓
See cash gaps before funds get tight
In which week could delayed receipts or extra purchasing affect cash
Connect receipts, payments, inventory investment and funding plans by time and entity, then compare scenarios in cash models. AI explains potential gaps, their impact and assumptions to confirm, preparing options for discussion.
- Connected data
- Available funds, receivables and payables, purchasing and spending plans, inventory and funding arrangements
- What it enables
- Cash forecasts, shortfall alerts and receipt and payment scenarios
- Cash shortfall warning lead time ↑
- Cash forecast error at the same horizon ↓
Trace close discrepancies to their source faster
Why don't the general ledger, subledgers and business records agree
Align periods, entities and currencies, then reconcile balances and details using rules. AI suggests matches, organizes unmatched items and possible explanations, and locates source records for finance to investigate.
- Connected data
- General ledger and subledgers, bank or business records, mapping rules and adjustment records
- What it enables
- Reconciliation differences, supporting evidence and proposed adjustments for confirmation
- Total reconciliation and review effort ↓
- Unresolved difference amounts ↓
Connect payment concerns to source evidence
Where are the potential duplicates, amount differences and payee mismatches
Use review rules to flag potential exceptions while AI organizes documents, key fields and open questions. For sensitive materials, explore local, read-only review with FAW, with business users confirming, rejecting or adding context.
- Connected data
- Invoices, payment records, payee details, internal rules and authorized purchasing documents
- What it enables
- Potential exception lists, source evidence and human review records
- Total exception review effort ↓
- Time from detection to confirmation ↓
Arrows show intended improvement directions. Set targets against your business baseline while checking accuracy and review effort. Agreed rules and models perform calculations; AI helps organize evidence and explanations. Authorized owners decide accounting treatments, budgets, payments and risk exceptions.
FAW · Local AI solution
Work with sensitive finance data in an agreed environment
Forge Agent Workstation (FAW) is our proposed local AI solution for finance and risk teams. We are exploring invoice and payment exception review, combining suitable local models, business rules and applications to connect findings to source records for people to assess.
Forge Agent Workstation
Proposed solution · Initial use case awaiting validation
Authorized business records
Invoices, payment records and agreed review rules
Rule checks and AI assistance
Locate differences, organize evidence and identify open questions
Human review and judgment
Confirm, reject or add context, retaining the basis for review
Intended business outputs
- Potential exceptions linked to review rules
- Traceable source records and calculation details
- Human review reports including unresolved questions
Data & metrics
Trace the numbers and measure the improvement
Connect financial definitions, business records and evidence. Track speed alongside calculation accuracy, forecast bias and human review effort.
Business and financial definitions
Align entities, periods, currencies, products and customers. Separate actuals, budgets and forecasts, retaining versions of cost allocations and assumptions.
Explain profit changes in business terms and give forecasts a verifiable starting point
Source traceability · Unexplained variances · Forecast error and bias · Analysis preparation time
Collections and cash events
Connect invoices, cash application, due dates, payment promises and actual receipts and payments. Retain disputes and plan changes, and flag information that needs updating.
Understand collection obstacles and identify gaps in cash plans sooner
DSO · Past-due receivables share · Cash forecast error · Shortfall warning lead time
Exceptions and review evidence
Retain review rules, source files, fields and human decisions. Distinguish potential exceptions from confirmed issues and cases with insufficient information.
Reduce document back-and-forth and focus review on concerns supported by evidence
Evidence traceability · False positives and missed exceptions · Amount verification accuracy · Total review effort
Solutions & support
Bring professional judgment and AI together
Financial definitions and business review
Agree calculation definitions, data assumptions and review requirements with your finance and business owners. AI organizes evidence and explanations; people with the relevant expertise and authority make professional judgments.
Discuss your use caseLocal capabilities with FAW
For use cases requiring local processing, explore suitable models, rules and applications with FAW. Choose the environment around business and data needs; not every finance use case requires new equipment.
Explore the FAW local solutionBefore we begin
Set the boundaries of a finance AI review
Finance & Risk Management supports analysis and exception review. The engagement should distinguish source records, calculations, AI explanations and the decisions reserved for finance owners.
What should be agreed before finance data is used
Agree the data scope, access permissions, calculation definitions, operating environment and reviewer. Local operation with FAW is an option to assess for the client environment, not a blanket security or compliance certification. Keep sensitive records out of the initial enquiry and arrange any access separately.
What does an exception finding establish
It identifies something to investigate, not confirmed fraud, an audit opinion or authority to make a payment. Review the underlying records and reproducible calculations, record unresolved gaps and retain human approval. Measure review effort and evidence traceability separately from any financial outcome.
Start with the number you most want to understand
Is profit hard to explain, cash slow to arrive, or reconciliation and exception review taking too much time? Let's choose one problem and identify the metrics and AI use cases worth improving.
Actelos Delta supports use case discovery, capability building and team adoption.
How we work together