The board meeting is in four days and the CFO still doesn't have final numbers.
The budget-vs-actual report shows last month's actuals because this month hasn't been reconciled yet. Someone is copying figures from the ERP into a consolidation spreadsheet, adjusting intercompany eliminations by hand, and hoping the formulas didn't break when a new cost centre was added.
Three days of the close go to assembling the pack. None of it is analysis. It is data plumbing that software should handle.
The finance team should be reading the numbers, not building them.
Finance teams at $10M-$200M businesses spend more time on data assembly than on analysis. The management accounts take three days because someone is manually pulling trial balances from the ERP, copying them into the consolidation spreadsheet, adjusting for intercompany sales, converting currencies by hand, and reconciling the result to the bank statements.
The problem custom financial software replaces is well documented: decades of research into operational spreadsheets by Raymond Panko has repeatedly found that the large majority contain at least one error, which is a precarious foundation for finance and reporting that has to be trusted.
RaftLabs has been shipping production software since 2015 for clients including Vodafone, T-Mobile, Aldi, Nike, Cisco, and Lockheed Martin, rated 4.9/5 by clients on Clutch. GDPR, SOC 2, PCI DSS, and financial data residency requirements are scoped in week 1, not retrofitted before launch. Role-based access control and full audit trails are standard on every build.
Custom financial software replaces the manual assembly steps with automated data pipelines, applies your mapping rules and consolidation logic programmatically, and delivers the output on a schedule. The finance team does the work that requires judgment: reviewing variances, approving exceptions, making the call on the numbers. Not building the spreadsheet.
This page covers the planning-and-consolidation layer specifically, the systems a CFO's office plans and reports with. Two related layers sit next to it:
- Financial software (this page)
- FP&A, budgeting, multi-entity consolidation, and treasury: the planning layer a finance team builds forecasts and board packs from.
- Financial reporting software
- What comes out the other end once the numbers are consolidated: board pack formatting, statutory and regulatory reporting, KPI dashboards. See [financial reporting software](/services/accounting-financial-software).
- Accounting automation
- The transactional layer underneath both: AP automation, bank reconciliation, and month-end close task sequencing. See [accounting automation](/services/accounting-automation).
Anaplan, Workday Adaptive Planning, Pigment, Vena, Planful, and OneStream are real, capable platforms, and for a standard reporting structure they're usually the right call. The problem shows up when your entity hierarchy, chart of accounts, or consolidation logic doesn't map cleanly to how the platform models a business: implementation drags past the demo's promise, and the finance team ends up needing a dedicated internal admin with scripting skills just to keep the platform running. That pattern shows up consistently in how finance teams describe these tools in practice: "It takes quite a bit of internal and IT know-how to set up" is a common description of Workday Adaptive Planning's implementation, and one FP&A manager reported still doing "a manual upload into Planful every month" because the ERP integration never closed the last mile.
Custom pays off specifically when the mapping logic between your general ledger and your management reporting structure is complex enough that a platform's standard dimensions can't hold it without workarounds. It doesn't pay off when your requirements are standard, we say so before you commit to anything.
What an unverifiable number costs when nobody can trace it back
What happens when a finance system's numbers can't be independently checked
- 900+
- people prosecuted on the word of a single accounting system's output
- UK Post Office Horizon scandal, 1999-2015
- 236
- of those prosecutions ended in imprisonment
- UK Post Office Horizon scandal
- £1B+
- in compensation reported, against original settlement figures far lower
- UK Post Office Horizon scandal, ongoing
The UK Post Office's Horizon accounting system, built by Fujitsu and rolled out from 1999, contained software bugs that generated false accounting shortfalls at branches nationwide. Reports indicate Fujitsu was aware of bugs as early as 1999 but did not disclose them. Between 1999 and 2015, more than 900 subpostmasters were prosecuted based on Horizon's figures, with 236 imprisoned, in what has been widely reported as one of the UK's widest miscarriages of justice. Compensation is now reported to exceed £1 billion, against a 2019 group settlement that totaled £58 million, most of which claimants lost to legal costs. The lesson isn't about Fujitsu's specific bug. It's that a system whose numbers can't be independently traced back to their source will get trusted over the people who actually know the business, until it's proven catastrophically wrong. A financial system without a real audit trail, mapping logic documented and version-controlled rather than living in someone's head, is the same risk at a smaller scale.
- Bought the enterprise FP&A platform on the strength of the demo
- Signed a 6-12 month, $150K-$500K+/year contract, then discovered implementation needs a dedicated internal admin with scripting skills the finance team doesn't have, still doing partial manual workarounds 18 months later.
- Kept extending the master spreadsheet
- Added another tab, another VLOOKUP, another manual reconciliation step every time the business added an entity or cost centre, until the person who built it is the only one who can maintain it.
- Bolted a BI dashboard onto the same manual numbers
- Built a Power BI or Tableau layer on top of the same manually-assembled figures, which looks like progress but doesn't remove the three days of manual assembly the dashboard still depends on.
- Assumed custom meant expensive and never got it scoped
- Stayed on the manual process for years assuming the alternative was either a six-figure SaaS contract or an open-ended bespoke build, without ever getting an actual quote for the specific gap.
This pays off when month-end is a recurring process, not a one-off.
Everything on the left should already be true for your operation. Even one thing on the right, and an off-the-shelf FP&A platform is the smarter first step.
A fit01A finance team at a $10M-$200M business losing three days every month-end to manual data assembly across spreadsheets that don't agree.
02Multiple entities or ERP instances to consolidate, with mapping logic that lives in one person's spreadsheet.
03An ERP already in place (SAP, Oracle ERP Cloud, NetSuite, Dynamics 365, Xero, or QuickBooks) that your reporting needs to read from.
Not a fitStandard requirements that a SaaS FP&A platform like Anaplan, Adaptive, or Pigment already fits cleanly.
No ERP or system of record yet, so there is no reliable data source to build on.
A one-off report rather than a recurring month-end process worth automating.
What we build
What we build
01FP&A and budgeting platforms
Multi-entity budget models with driver-based forecasting, scenario analysis, rolling forecasts, and version management in one system, replacing the Excel model that breaks when someone adds a cost centre. Budget entry and approval workflows route to the right owner, and every forecast is stored with a timestamp and owner so the board sees the past and current views in one place.
02Management accounts automation
Management accounts delivered on a schedule without anyone assembling them. The system pulls from your ERP and bank feeds, applies your mapping rules, calculates the P&L, balance sheet, and cash flow, and formats the pack to your template, so finance reviews variances and approves rather than building the numbers by hand. Mapping rules are version-controlled and historical packs are stored, so an auditor gets the approved pack.
03Financial consolidation
Multi-entity consolidation under IFRS and US GAAP with intercompany eliminations, currency translation, and minority interest calculations, replacing the month-end spreadsheet that takes 2-3 days every cycle. Trial balances pull from each ERP instance, elimination rules and correct-rate currency translation apply automatically, and intercompany mismatches are flagged before the run and logged for the auditor.
04Treasury and cash management
Cash flow forecasting, bank connectivity over SWIFT and open banking APIs, cash positioning, FX exposure tracking, and payment approval workflows in one system. A 13-week rolling forecast pulls from receivables, payables, and payroll and updates as collections land, the positioning dashboard shows consolidated cash across all accounts and entities in real time, and payment batches route to the correct signatories with a full approval trail.
05Financial reporting and analytics
Self-service financial reporting with drill-through from the summary P&L to the underlying transactions. Business unit heads see their entity, the CFO sees group P&L, cash position, and key ratios in one dashboard, and scheduled delivery sends the weekly flash, monthly summary, and quarterly board pack automatically. If you use Power BI, Tableau, or Looker, the data model we build acts as the semantic layer with agreed metric definitions.
06ERP and data integration
Connecting financial software to your ERP and accounting systems, NetSuite, Oracle ERP Cloud, SAP S/4HANA, Dynamics 365, Xero, and QuickBooks, with incremental extraction, so reports reflect today's numbers, not yesterday's batch. Every integration includes documented mapping from your chart of accounts to your management reporting structure, and businesses running different ERPs across entities get a single extraction layer that normalises the data before reporting reads it.
Finance team spending more time building the pack than reading it?
Tell us your current month-end process and what it costs in hours and errors. We will scope a system that delivers the numbers automatically and gives your team time back.
How it works
From scope to shipped
Every project follows the same four phases. Scope is locked and price is fixed before development starts.
- Week 1
01Discovery and data audit
We map your current month-end process, your data sources, and your reporting structure. You leave week 1 with a documented data flow, a written scope, and a fixed-price quote. No development starts without your sign-off.
- Weeks 2-3
02Data model and design
We design the general ledger mapping, the entity hierarchy, and the reporting data model before writing a line of production code. Mapping decisions made here cost ten times less than the same decisions made in week 8.
- Weeks 4-12
03Build, integrate, and QA
Working software at a staging URL by the end of sprint one. Bi-weekly demos with your finance team. QA runs in parallel with every sprint, not as a phase at the end. ERP integrations are tested against your live data.
- Weeks 10-16
04Parallel run and go-live
Your finance team runs the new system alongside the existing process for 2-3 month-end cycles to validate the numbers. We do not switch over until the system produces the same output as the manual process three months in a row.
We'll say this plainly: RaftLabs doesn't yet have a published case study for a dedicated FP&A, consolidation, or management-accounts build. The closest proof sits in adjacent finance systems. We shipped a payments platform for a UAE FinTech operator that passed a 2025 PCI DSS audit, running two processors behind a roughly 40-table domain model across about 59 releases. We built InvestIQ, an investment-research tool that pulls IPO, buyback, and OFS data from the NSE and BSE into one reconciled view. Neither is an FP&A build, but both are regulated, ledger-heavy financial systems where a wrong number has consequences.
What carries across from that work is the discipline finance-ops software depends on, proven on delivery since 2015: documented mapping logic instead of a formula chain nobody else can read, a parallel run before any system goes live, and an audit trail behind every number. That discipline, not a single case study, is what actually decides whether a finance system gets trusted.
What clients say
What our clients say
Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.
Charles E.
USAEntrepreneur at Aggie Technologies
“All of the sprints were completed on schedule and on budget. We highly recommend RaftLabs!
A financial system runs under audit from day one. We've shipped these controls on real, regulated builds, including a payments platform that passed a 2025 PCI DSS audit. Getting the data security wrong is costly: a breach in the financial sector averages $6.08M (IBM Cost of a Data Breach Report, 2024). Here is the regime we design for, and what each one actually demands.
- PCI DSS
- If the system touches cardholder data, scope is the first question: what stores, processes, or transmits card numbers, and how to shrink that surface. We tokenize at the processor and keep card data out of the application database entirely. Our UAE payments build passed a 2025 PCI DSS audit on exactly that model.
- SOC 2
- The trust-services criteria your enterprise customers' security teams ask about: security, availability, and confidentiality. We build the access controls, change logs, and encryption baselines a SOC 2 Type II audit tests, so the evidence exists before the auditor asks for it.
- KYC and AML
- Where the software onboards accounts or moves money, identity verification and transaction monitoring are not optional. We integrate KYC providers and encode the sanctions-screening and suspicious-activity rules your compliance team defines, with every decision logged.
- Payment rails and reconciliation
- Treasury and payment flows run over SWIFT, open banking, and card processors, each with its own settlement timing and failure modes. We reconcile each movement back to the bank statement and flag the breaks, so the ledger and the bank agree without anyone chasing a mismatch by hand.
- Double-entry integrity
- Consolidation and management accounts sit on a double-entry ledger. Debits equal credits, eliminations net to zero, and every posting traces to a source. We enforce that in the data model, not in a spreadsheet formula a new cost centre can silently break.
- Data residency and encryption
- UK and EU financial data stays in the configured region. Encryption at rest and in transit is a baseline, not an upsell, and residency is designed for the auditors and regulators your business answers to.
- How is this different from just buying Anaplan, Adaptive, or Pigment?
- Off-the-shelf platforms are built for the general case, and they're often the right call. Custom pays off specifically when your entity hierarchy or GL-to-management-reporting mapping doesn't fit the platform's standard dimensions without workarounds. We tell you which one fits before you commit to building anything.
- Won't you just tell me custom is the answer, because that's what you sell?
- No. The QualifierBand above this section exists specifically to talk you out of a custom build if a configured SaaS platform already fits. We scope the actual mapping complexity before recommending either path.
- Our reporting structure and entity hierarchy are a mess. Won't that make custom worse, not better?
- The design phase exists to untangle that before a line of production code is written, mapping the GL to your reporting structure, documenting elimination rules, resolving ambiguity with the people who own each number. A messy structure is exactly why the mapping logic needs to live in a documented, version-controlled system instead of one person's spreadsheet.
- How do I know the numbers this thing produces are right, and that an auditor will accept them?
- Every mapping rule, elimination journal, and approval action is logged with a timestamp, user identity, and the previous value, the record an auditor asks for when a number changes. We don't switch over from your existing process until the new system produces the same output as your manual process for three consecutive month-ends.
- I don't have a dedicated finance-systems person. Who maintains this after you leave?
- Mapping logic is documented and version-controlled specifically so it doesn't require the one person who built it. You get full source code and documentation at handover, built to be maintained by any competent team, not just us.
What actually decides whether a finance-ops build holds up
Rarely the pitch. Always the difference between a system finance trusts and one more spreadsheet in disguise.
- 01
What documented GL-to-management-mapping logic actually means
The rules that translate general ledger codes into your management reporting structure, written down, versioned, and owned, instead of living in a formula chain only one person can read.
- 02
What a parallel run actually catches
Running the new system alongside the existing process for two to three month-end cycles surfaces the edge case, the cost centre nobody remembered to map, before it reaches the board pack, not after.
- 03
What an auditor asks for that a spreadsheet can't produce
A timestamped, user-attributed log of every edit, elimination, and approval, not a spreadsheet where "why did this number change" gets answered from memory.
- 04
Why AI gets scoped after the data layer, not before it
Variance commentary and anomaly detection are only as good as the mapping logic underneath them. AI on unreliable data produces confidently wrong answers, so the foundation comes first.
Where you land in these ranges depends on scope, not negotiation:
- Management accounts automation, $35,000-$55,000
- Single entity, one ERP integration: trial balance extraction, GL mapping, and the P&L, balance sheet, and cash flow on a schedule.
- FP&A platform, $40,000-$65,000
- Budget entry, driver-based forecasting, scenario analysis, and budget-vs-actuals reporting for a single entity.
- Treasury and cash management, $45,000-$80,000
- Cash flow forecasting, bank connectivity, and FX exposure tracking.
- Multi-entity consolidation, $60,000-$95,000
- Two to five ERP sources, intercompany eliminations, and currency translation under IFRS or US GAAP.
- Full finance suite, $90,000-$120,000
- FP&A, management reporting, consolidation, and treasury integration for a mid-size multi-entity business.
What it costs
Custom financial software, starting at $35,000.
We assess your current process, data sources, and reporting requirements, then lock the cost in writing before development starts.
Starts at $35,000Delivered in 10-16 weeks. A focused single-entity scope starts here; a full multi-entity finance suite builds out from that foundation as your reporting complexity grows.
When a SaaS FP&A platform fits your requirements, we tell you to buy it. Custom pays off when your reporting structure does not map cleanly to the standard model.
No hourly billing
Once we scope your first phase, that price is locked in writing. No hourly billing, no change fees buried in the invoice.
Parallel run
Your finance team runs the new system alongside the existing process for two to three month-end cycles. We do not switch over until it produces the same numbers as your manual process three months in a row.
