Finance function transformation and digitalization
We apply current leading practices in financial management and internal control to your company’s close, collections, payments, treasury and planning processes, and we sustain them with digitalization, automation and artificial intelligence agents.
Request a screening at no costThe screening takes thirty minutes, carries no cost and is led by a CFO with more than fifteen years in the role.
Finance processes and artificial intelligence, at the same table
DBNG brings finance process expertise and the technology that digitalizes those processes together in a single team.
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Finance processes: close, collections, payments, treasury, planning and performance management, under the direction of a CFO with more than fifteen years in the role.
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DBNG Digital: the data, analytics and artificial intelligence division, which digitalizes and integrates the business systems the company already uses, automates processes and deploys AI agents that work within those systems.
Automation is implemented on processes that have been redesigned first: each workflow is organized and documented before technology is introduced, which prevents current inefficiencies from being carried into the system.
From the close to treasury: 30 process failures ranked by their impact on cash and margin
Each approach is indicative: the diagnostic determines what can be implemented in each company, with what scope and in what sequence, according to its processes, its systems and its priorities.
Select the situations that apply to your company with “Include in the screening”: the conversation starts from them.
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The monthly close takes more than ten business days because reconciliations, accruals and adjustments are processed manually after the cutoff.
- Impact
- Management information arrives two to three weeks after month-end, and the accounting team absorbs overtime every period.
- Proposed approach
- The close is managed with a calendar and assigned owners, and reconciliations, accruals and recurring entries are prepared automatically. An AI agent flags unusual items so that review concentrates where the risk lies, and the accounting team approves each entry and the close.
- Metric
- Business days until management information is issued.
- Process
- Digitalization
- Automation
- AI agents
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Bank reconciliation requires a high volume of manual work, transaction by transaction, in spreadsheets or in the ERP itself.
- Impact
- It consumes a significant share of the team’s hours, material items remain open for weeks and the reconciliation determines the length of the close.
- Proposed approach
- Bank reconciliation becomes a continuous process: matching items are reconciled by rules, and an AI agent proposes the classification of the remaining items based on prior resolutions. The team concentrates on exceptions and approves each reconciliation.
- Metric
- Percentage of items reconciled automatically and aging of open items.
- Process
- Digitalization
- Automation
- AI agents
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Vendor invoices arrive by email, on paper and as PDF files, and are entered manually into the system.
- Impact
- Maintaining vendor accounts takes hours of manual work, with payments applied to the wrong invoices, taxes and withholdings calculated at outdated rates, and discrepancies that surface only when the vendor raises a claim.
- Proposed approach
- Vendor invoices enter through a single digital workflow, with taxes and withholdings calculated against the current official rate tables. An AI agent reads each document and proposes its coding, which keeps every vendor account current. The designated approver approves each invoice before it is posted.
- Metric
- Hours spent maintaining vendor accounts, unapplied items and vendor claims.
- Process
- Digitalization
- Automation
- AI agents
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Customer receipts are applied manually from bank statements, electronic payments and tax withholding certificates, and unidentified receipts accumulate.
- Impact
- Customer accounts no longer reflect each customer’s actual balance, debts already settled are pursued for collection and the tax withheld by customers is not claimed on time.
- Proposed approach
- Cash application becomes a daily process: rules propose the application of each receipt, and an AI agent reads the withholding certificates and proposes their accounting treatment, which keeps each customer balance current. The team approves each batch before it is posted.
- Metric
- Percentage of receipts applied the same day and unapplied cash balance.
- Digitalization
- Automation
- AI agents
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The cash position is consolidated manually, bank by bank, and is not available in time for payment and investment decisions.
- Impact
- Decisions on payments and on the investment of surplus cash are made with outdated balances, and the treasurer spends hours preparing the report, time that is unavailable for analysis.
- Proposed approach
- The cash position across all banks, currencies and entities is consolidated every morning in a single dashboard. An AI agent classifies transactions and flags variances against forecast, and the treasurer devotes that time to payment and investment decisions based on current balances.
- Metric
- Time of day the cash position is available and weekly hours of preparation.
- Digitalization
- Automation
- AI agents
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The cash forecast depends on multiple sources that are compiled manually, and part of the future cash flows is left out of the projection.
- Impact
- Payment and financing decisions rest on an incomplete projection, and funding shortfalls appear without warning and are financed on whatever terms are available at that moment.
- Proposed approach
- The thirteen-week forecast automatically integrates all sources of information, covering both recorded and projected flows. A machine learning model estimates each customer’s probable payment date, and treasury validates the assumptions and decides on financing.
- Metric
- Four-week cash forecast error.
- Process
- Automation
- AI agents
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The management report is prepared manually, by copying data from the ERP into spreadsheets and presentations, and reaches executive leadership weeks after the close.
- Impact
- The team spends days compiling information, with little time left for analysis, and variances are corrected a month late.
- Proposed approach
- The reporting cycle is automated end to end: reports, presentations to executive leadership and dashboards are generated at the close from a single data model. An AI agent drafts the variance analysis, and finance leadership approves the report before it is distributed.
- Metric
- Days between month-end and delivery of the report to executive leadership.
- Digitalization
- Automation
- AI agents
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The close does not integrate the balance sheet, the income statement and the cash flow statement, and the change in cash is rebuilt manually.
- Impact
- Inconsistencies among the statements are detected late or not at all, and executive leadership decides without an integrated view of earnings, financial position and cash generation.
- Proposed approach
- The close automatically produces the three integrated statements, reconciled with one another and with the bridge from net income to cash. An AI agent explains the main changes in cash (operating, investing and financing), and finance leadership reviews that analysis before presenting it to executive leadership.
- Metric
- Days to issue the three integrated statements and reconciliation differences among them.
- Process
- Automation
- AI agents
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Invoices are issued days after delivery, in billing batches prepared manually.
- Impact
- Each day between delivery and invoice is an additional day of financing extended to the customer, which adds to days sales outstanding (DSO) and absorbs working capital.
- Proposed approach
- The invoice is prepared on the day of delivery, and the company stops financing the customer for the days that billing currently takes. An AI agent checks each invoice against the purchase order and the customer’s requirements, and the billing owner approves each batch before it is issued.
- Metric
- Days between delivery and invoice, and days sales outstanding (DSO).
- Process
- Digitalization
- Automation
- AI agents
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Collections are managed through manual calls and emails, with no defined sequence and no record of payment commitments.
- Impact
- Overdue receivables grow without a recorded cause, cash inflows cannot be projected and the allowance for doubtful accounts is adjusted late.
- Proposed approach
- Collections follow a defined sequence by customer segment, with every payment commitment recorded. An AI agent prioritizes the portfolio and prepares each contact, so that the collections owner can devote time to the highest-risk accounts. The collections owner reviews and sends each communication.
- Metric
- Receivables more than 60 and 90 days past due and percentage of payment commitments kept.
- Process
- Automation
- AI agents
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Credit limits are not integrated into the sales process, and orders from delinquent customers are released without control.
- Impact
- Credit exposure grows without authorization, and bad-debt losses are recognized when they can no longer be avoided.
- Proposed approach
- Credit limits are integrated into the sales process: the system blocks orders from customers that are past due or over their limit, and each exception requires a recorded approval. A machine learning model proposes periodic updates to the limits, and finance leadership approves them.
- Metric
- Orders released despite past-due balances or exceeded limits, and bad-debt losses.
- Process
- Digitalization
- Automation
- AI agents
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Matching among purchase order, receipt and invoice is performed manually, or not at all.
- Impact
- The company pays prices that differ from those agreed or pays for quantities never received, and the loss is detected late or not at all.
- Proposed approach
- No invoice is released for payment unless it matches its purchase order and its receipt, within the tolerances the company sets. An AI agent gathers the evidence for each discrepancy and proposes a resolution. The designated owner decides, and payments are released under the company’s signature authority.
- Metric
- Percentage of invoices that pass the automated match and amount recovered from discrepancies.
- Process
- Automation
- AI agents
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Purchases are approved by email or on paper, and the purchase order is issued once the spend is already committed.
- Impact
- Budget control operates after the spend, and there is no auditable record of who authorized each disbursement.
- Proposed approach
- Each expenditure is approved before it is committed, in a digital workflow with authorization levels by amount and by cost center. An AI agent checks each request against the budget and the agreed terms, and the designated approver decides before the purchase order is issued.
- Metric
- Percentage of spend with a prior purchase order.
- Process
- Digitalization
- Automation
- AI agents
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The payment proposal is prepared manually each week and does not follow a treasury policy.
- Impact
- Cash is disbursed earlier than necessary, and the company finances its vendors’ working capital without compensation.
- Proposed approach
- Payments follow a treasury policy: the system prepares the weekly proposal according to due dates and available cash, and an AI agent tests it against that policy. Cash is disbursed on the date agreed with each vendor, and the company releases each proposal under its signature authority.
- Metric
- Days payable outstanding (DPO) and early payments without a recorded decision.
- Process
- Automation
- AI agents
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The same person sets up the vendor, records its invoice and releases the payment.
- Impact
- The company is exposed to errors and fraud that are difficult to detect: organizations lose approximately 5% of their annual revenue to occupational fraud (ACFE 2024).
- Proposed approach
- Wherever possible, vendor setup, invoice recording and payment are assigned to different people; where the structure does not allow it, mitigating controls are applied, with an AI agent that flags conflicts and out-of-pattern transactions. The internal control owner decides on the actions.
- Metric
- Open segregation-of-duties conflicts.
- Process
- Digitalization
- AI agents
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Changes to bank details and urgent payment requests are accepted by email, without verification through an independent channel.
- Impact
- The company is exposed to impersonation fraud, which is becoming increasingly sophisticated through the use of artificial intelligence.
- Proposed approach
- No change to bank details and no high-value payment is executed without verification through an independent channel and a second approver. An AI agent analyzes each request for signs of impersonation and holds suspicious transactions until the responsible owner confirms them.
- Metric
- Bank detail changes and urgent payments verified through a second channel.
- Process
- Automation
- AI agents
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Recurring entries and closing adjustments are calculated in spreadsheets and entered manually into the system.
- Impact
- The same errors recur at every close, and process knowledge is concentrated in a few people, which creates a business continuity risk.
- Proposed approach
- The logic of critical spreadsheets moves into the system and no longer depends on a few people, and recurring entries are prepared automatically at each close. An AI agent flags entries that deviate from prior periods, and the accounting team approves each batch before it is posted.
- Metric
- Manual entries per close and critical spreadsheets outside the system.
- Process
- Digitalization
- Automation
- AI agents
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Errors originating in purchasing, logistics and sales are detected and corrected manually only at the accounting close.
- Impact
- Finance absorbs the rework under deadline pressure, and reported margins are restated after publication.
- Proposed approach
- Errors are corrected at their source, with validations and mandatory master data at the point of entry in purchasing, logistics and sales. An AI agent classifies each close’s adjustments by root cause and by area, and finance leadership decides which controls to strengthen.
- Metric
- Number and amount of adjusting entries per close, by root cause.
- Process
- Digitalization
- Automation
- AI agents
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Costs are recorded on the date of the vendor invoice, which may fall in a later period than the receipt of the goods or services, and are assigned to the wrong period.
- Impact
- Gross margin and monthly results fluctuate because of cut-off differences unrelated to operating performance, and pricing and spending decisions rest on distorted figures.
- Proposed approach
- Each cost is recognized in the period in which it is incurred: goods are recorded upon receipt, with or without a purchase order, and services received are accrued at the close. An AI agent estimates recurring charges not yet invoiced, and the accounting team approves the entry before it is posted.
- Metric
- Amount of costs recognized outside the period in which they were incurred.
- Process
- Automation
- AI agents
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Taxes withheld by customers and other withholding agents are recorded manually and are not reconciled against what those agents report to the national and local tax authorities.
- Impact
- Tax credits are lost and the company pays more tax than it owes, or it claims withholdings that the agent never reported, and the difference remains exposed in a tax audit.
- Proposed approach
- The withholdings reported by the withholding agents are captured every month and reconciled against the accounting records and the tax returns, so that none goes unclaimed. An AI agent explains each difference, and the tax owner approves the adjustments.
- Metric
- Tax reconciliation differences and unclaimed withholdings.
- Process
- Automation
- AI agents
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Profitability by customer, product and channel is calculated manually once a year, with year-end closing data.
- Impact
- Prices, discounts and commercial terms are set without knowing each customer’s contribution, and customers with negative margins are retained without review.
- Proposed approach
- Contribution margin by customer, product and channel is updated at each month-end close, including the cost to serve each customer. An AI agent identifies cases of margin erosion and proposes their causes, and executive leadership decides prices, discounts and terms with that information.
- Metric
- Contribution margin by customer and product, available at each month-end close.
- Process
- Automation
- AI agents
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The budget is consolidated across dozens of spreadsheets that circulate by email, and the process extends over several months.
- Impact
- The team spends much of the year consolidating versions, linking errors are frequent and the approved budget is outdated before execution begins.
- Proposed approach
- The budget is built on a single platform, with a driver-based model, version control and automatic consolidation. An AI agent proposes the first version of each line from the historical series, and each owner adjusts and approves it.
- Metric
- Weeks in the budget cycle and versions exchanged.
- Process
- Digitalization
- Automation
- AI agents
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The earnings forecast is updated manually once or twice a year, and the variance against plan is recognized only in the fourth quarter.
- Impact
- No room remains to correct course, and second-half decisions are made on an outdated forecast.
- Proposed approach
- The earnings forecast becomes a rolling forecast updated every month over a twelve- to eighteen-month horizon, so that variances are detected while there is still room to correct course. A machine learning model generates the statistical baseline, and executive leadership approves the final version.
- Metric
- Bias and percentage error of the three-month forecast.
- Process
- Automation
- AI agents
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The planning team spends most of the month gathering and reconciling data from different systems.
- Impact
- Variance analysis and recommendations to executive leadership are set aside, and variances are explained when there is no longer room to correct them.
- Proposed approach
- The planning team works on data already integrated and reconciled in a single model. An AI agent prepares a draft of the price, volume, mix and cost variance analysis, and the team validates it and devotes its time to analysis and recommendation.
- Metric
- Percentage of team time devoted to analysis.
- Digitalization
- Automation
- AI agents
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Each department calculates its metrics in its own spreadsheets, and different versions of the same figure circulate.
- Impact
- Executive meetings begin by establishing which figure is correct, and decisions are deferred until a validated figure is available.
- Proposed approach
- Each metric has a single definition, a single source and an owner, and the entire company consults the same figure on a shared dashboard. An AI agent answers questions about the metrics and explains their changes, and the owner of each metric validates its definition when the business changes.
- Metric
- Metrics with a single definition and an assigned owner.
- Process
- Digitalization
- Automation
- AI agents
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Invoices are rejected or placed on hold for lack of a purchase order, a receiving number or the correct addressee.
- Impact
- Overdue receivables include invoices left unpaid because of administrative defects that are detected only during collection.
- Proposed approach
- No invoice is issued without the customer’s payment requirements: the purchase order, the receiving number and the addressee are validated before issuance. An AI agent classifies the reason for each disputed invoice and proposes the correction, which the team approves.
- Metric
- Percentage of invoices rejected or disputed, by cause.
- Process
- Digitalization
- Automation
- AI agents
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Payroll and payroll taxes are reconciled manually against the general ledger and the payroll tax filings.
- Impact
- Differences among payroll, journal entries and filings are detected late, with interest charges and labor and social security exposures.
- Proposed approach
- Payroll, the general ledger and the payroll tax filings are reconciled every month under defined rules, so that differences are detected before they generate interest or exposures. An AI agent explains those that exceed the tolerance, and the payroll owner approves the entry and resolves each difference.
- Metric
- Monthly reconciliation differences in payroll and payroll taxes.
- Process
- Automation
- AI agents
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Differences between physical inventory and the inventory system are detected only at the annual count, and shortages are charged to cost at the close.
- Impact
- Monthly results are overstated because they exclude shortages, shrinkage and breakage, and the accumulated adjustment for the year is concentrated at the year-end close, when it can no longer be explained.
- Proposed approach
- Shortages are charged to cost in the month in which they are detected: cycle counts by criticality are digitized and integrated with the accounting records. An AI agent analyzes recurring differences by warehouse and by item, and the inventory owner approves each adjustment.
- Metric
- Inventory differences per count and cost adjustments at the close.
- Process
- Digitalization
- Automation
- AI agents
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Duplicate payments and unused recurring services go undetected because no one systematically compares what is invoiced with what is contracted.
- Impact
- Funds are disbursed without consideration received, and services that are no longer used remain in place.
- Proposed approach
- Each payment is checked for duplicates by vendor, amount and document, and an AI agent compares each recurring invoice with its contract. Invoices that do not match are held until the responsible owner decides, and each contract and subscription has an assigned owner.
- Metric
- Duplicates detected before payment and recurring spend without an assigned owner.
- Process
- Digitalization
- Automation
- AI agents
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Bank accounts, their signatories and their access rights are not reviewed periodically, and low-activity accounts remain without oversight.
- Impact
- Every active access right held by a person who should no longer have it is an exposure, and idle balances generate bank fees with no return.
- Proposed approach
- Each bank account, each signatory and each access right has an assigned owner. An AI agent periodically cross-checks signatories and access rights against the active employee roster and issues alerts on activity in dormant accounts, and the treasury owner resolves each alert.
- Metric
- Active accounts, signatories reviewed and idle balances.
- Process
- Automation
- AI agents
No situations match this combination. Please try a different filter.
In thirty minutes we review with you the situations with the greatest impact on your finance function, and the priorities are summarized in a one-page document, together with the metrics worth tracking.
Request a screening at no costDecisions remain with your company
No agent executes a transaction without the approval of a person on your team. The role of the agents is limited to preparing the analysis and proposing each action; executing a payment, a journal entry, a change to customer or vendor data, a credit limit, or a communication to the board, to banks or to third parties always requires that approval. Automated tasks, such as sending payment reminders or blocking orders from delinquent customers, operate under rules that your company approves in writing before they are activated. If your company decides to automate a recurring payment, its execution is carried out by a fixed rule approved in writing, with a limit per transaction and per day; an agent never decides a payment. Each agent operates under its own user account with restricted permissions, does not use the personal tax credentials of any individual, and every one of its actions is logged. The time that automation frees up is reallocated to analysis and decision-making.
How we work
- 01
Screening at no cost
A thirty-minute conversation and an initial review of basic data. The result is summarized on one page, with the prioritized situations and the metrics worth tracking.
- 02
Diagnostic
At the depth you choose, Executive Snapshot or Blueprint, we assess the finance cycle: processes, systems and data, working capital, performance management and the structure of the function. The diagnostic remains yours, whether or not you continue with us.
- 03
Design and implementation
We redesign the processes, digitize what is currently recorded on paper or in spreadsheets, automate repetitive tasks and introduce artificial intelligence agents under the rules and approvals your company defines.
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Ongoing support
After implementation, we sustain the periodic review of the processes and the improvement of what has been implemented, within the agreed scope, with external financial leadership if your company needs it. Each month we compare every metric with the starting point.
Start with a screening at no cost
In thirty minutes we review with you the situations with the greatest impact on your finance function, and the priorities are documented on one page, together with the metrics worth tracking.
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