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Case study for FMCG clients

Automating finance, receivables and HR for FMCG clients

For FMCG companies we have automated more than ten finance, credit and HR processes. Ten of them are described here, each the same way: what the problem was, what we did and what the client gained. Client details are anonymised for confidentiality.

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Client

FMCG companies; client details anonymised

Scope

10 processes described: finance and receivables, procurement and payments, treasury, HR

Technology

UiPath, SAP, ServiceNow; robots run in 24/7 mode

Service

Process automation: RPA and AI agents

Processes in this case studyAutomated VAT settlements Automated bank-balance reconciliation Bank-statement monitoring & cash application Fast, consistent credit decisions Smooth payment-term changes Collections cases routed to the right person instantly Faster release of blocked orders Automated P2P query handling Employee data mass update Automated new-hire onboarding

Finance and tax

Automated VAT settlements

No more manually re-typing data between systems and VAT forms.

Challenge

Monthly VAT settlements across many countries meant hours of tedious copying of data into spreadsheets and forms. At that scale, mistakes and late filings are almost inevitable.

What we did

We deployed a “digital worker” that pulls the data itself, prepares calculations per the client’s rules, fills in VAT returns and verifies counterparties, then archives the documents and prepares tax payments for one-click approval.

Results

Returns ready to file with no manual work
Fewer errors and costly corrections
On-time filing and audit peace of mind
Easy to scale to more countries and entities
Shorter VAT close
Lower risk of tax penalties
A relieved finance team

Solutions in the library: E‑invoicing (KSeF) submission and status reconciliation, E‑invoices validated and submitted, mandates absorbed.

Automated bank-balance reconciliation

Balances always in sync between systems, discrepancies caught at once.

Challenge

Manually comparing balances between two banking systems was time-consuming, and discrepancies surfaced too late.

What we did

A robot automatically compares balances for every account and, if there is a difference, raises a ticket and points to the person or team responsible for resolving it.

Results

Automatic balance-consistency checks
Early detection of differences
Fewer financial discrepancies
Audit readiness
Higher financial-data accuracy
Lower audit risk
Shorter reconciliation time

Solutions in the library: Account reconciliations and journals that close themselves, Intercompany balances that agree before the group close.

Bank-statement monitoring & cash application

Missing statements caught proactively, smooth cash application.

Challenge

Missing or delayed bank statements could stall cash application and distort the liquidity picture, and were usually spotted too late.

What we did

A robot analyses reports from the banking system, tells real gaps from non-working days and, when a statement should already be available, automatically raises a ticket and routes it to the right person.

Results

Proactive gap detection
Faster problem resolution
Continuity of cash application
Fewer stoppages in finance processes
Faster cash application (DSO)
Better cash-flow visibility
Lower operational risk

Solutions in the library: The daily cash position without the 7 a.m. spreadsheet, Account reconciliations and journals that close themselves.

Receivables and credit

Fast, consistent credit decisions

Streamlined credit-limit management, supporting sales without adding risk.

Challenge

Requests for a current credit limit and applications to increase or decrease it required manual gathering of financial data and waited a long time for a decision.

What we did

A robot automatically retrieves up-to-date client and history data, enriches the case and passes it for decision, handling both simple enquiries and limit-change applications.

Results

Faster credit decisions
Stronger sales support without added risk
Automated financial-data retrieval
Uniform rules across all markets
Faster client onboarding and revenue
Bad-debt risk under control
Shorter credit-decision time

Solutions in the library: Counterparty screening: sanctions, VAT status, registers, Order-to-cash process mining: where the cash gets stuck. Related: Order-to-Cash control tower.

Smooth payment-term changes

Customer requests for new payment terms handled quickly and in full control.

Challenge

Handling requests to change payment terms required manual data gathering and chasing approvals.

What we did

A robot enriches the case with all the data needed and drives it through the approval process per the client’s rules, all the way to a decision and closure.

Results

Faster request handling
Better customer experience and flexibility
Less manual work
Better control over cash flow
Better terms management (DSO)
Higher customer satisfaction
Predictable cash flow

Solutions in the library: Order-to-cash process mining: where the cash gets stuck, Invoices chased before they turn difficult.

Collections cases routed to the right person instantly

Receivables cases reach the right owner instantly, no manual sorting.

Challenge

Receivables cases had to be assigned by hand to the right people across regions. That delayed the start of collections and caused mistakes.

What we did

A robot recognises who a case concerns and automatically routes it to the right collections owner or regional team, instantly and around the clock.

Results

No more manual case sorting
A faster start to collections
Fewer misroutes and rework
One consistent process across countries
Faster cash collection (DSO)
Higher team productivity
Shorter case handling time

Solutions in the library: Order-to-cash process mining: where the cash gets stuck, Invoices chased before they turn difficult. Related: The receivables agent: cash comes back sooner.

Faster release of blocked orders

Valid orders move faster, so the company earns faster.

Challenge

Orders blocked by credit control waited for manual review. Every hour of delay meant postponed sales and revenue.

What we did

Every few minutes a robot detects blocked orders, gathers the needed information, runs pre-checks and starts the approval process per the client’s rules, then releases the order once a decision is made.

Results

Faster release of valid orders
Less manual data checking
A standardised approval path
Fewer lost revenues from delays
Faster revenue realisation
Shorter cycle time
Better credit-risk control

Solutions in the library: Customer orders from PDFs and emails straight into the ERP, Three-way match exceptions resolved before the payment run. Related: Order-to-Cash control tower.

Procurement and payments

Automated P2P query handling

Invoice copies, statuses and statements delivered instantly, around the clock.

Challenge

Teams and suppliers flooded the finance team with repetitive requests: invoice copies, payment status, account statements. That tied up people and created backlogs.

What we did

A robot receives the query, finds the needed document or information and sends the answer back to the user, automatically and without interruption, 24/7.

Results

Instant answers to common queries
An end to repetitive manual work
A service available 24/7
Smaller backlog in finance teams
Higher productivity
Lower cost per query
Happier users and suppliers

Solutions in the library: The AP mailbox sorted every hour, payment questions answered, Vendor master changes with bank-account fraud control. Related: Invoice disputes without escalation.

Employee data mass update

Hundreds of data changes done quickly, safely and error-free.

Challenge

Bulk changes to employee data in the HR system are a tedious, sensitive task where mistakes come easily.

What we did

A robot picks up the request with the change file, verifies its scope (excluding management), prepares the data and performs the bulk update, then reports the result back to HR.

Results

Fast, safe bulk updates
No manual data-entry errors
Control over sensitive data
Full audit trail and reporting
Higher HR productivity
Better data quality
Compliance and fewer corrections

Solutions in the library: Payroll inputs consolidated and checked before the run, Employees change their own address, name and bank details.

Automated new-hire onboarding

New hires ready to work sooner, less paperwork for HR.

Challenge

Creating and updating new-hire records required manual file processing and many steps across systems.

What we did

A robot retrieves and securely processes data from the payroll system, archives it and creates or updates the employee in the HR system, from new hire, through changes, to offboarding.

Results

Automated onboarding data flow
Faster activation of employees in systems
HR freed from admin work
Secure data processing
Shorter time-to-onboard
Better employee experience
Lower HR operating costs

Solutions in the library: Joiner, mover, leaver: access on day one, revoked same day, Day one ready: accounts, access and kit from one HR trigger. Related: The HR agent on Teams.

Agents and scenarios

The same processes with an AI agent

Scenarios are illustrative models with a calculation, described on an example company. They show what an AI agent on Microsoft Teams changes in the processes of this case study.

ScenarioOrder-to-Cash control tower

Faster revenue realisation, lower DSO, full auditability of every decision.

See the scenario ScenarioInvoice disputes without escalation

Resolutions in hours, fewer “peace-of-mind” write-offs, better supplier relationships.

See the scenario ScenarioThe HR agent on Teams

A one-second answer instead of days; HR wins back time for recruiting and development.

See the scenario AI agentThe receivables agent: cash comes back sooner

It prioritises, writes, escalates and proposes decisions. You just approve.

See the agent

References and details of these projects are shared during the proposal process.

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