GITNUXSOFTWARE ADVICE
Finance Financial ServicesTop 10 Best Cashflow Forecasting Software of 2026
Ranked roundup of cashflow forecasting software for teams, with Dryrun, Kyriba, and PlanGuru compared by strengths, tradeoffs, and fit criteria.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
Dryrun is the best fit for businesses and advisors that need repeatable 13-week cash forecasting with scenario comparisons and item-level variance tracking, whereas Kyriba suits treasury teams requiring bank-linked forecasts with stronger scenario and variance discipline.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Dryrun
Item-level variance analysis shows which modeled inflows and outflows caused ending cash deviations versus actuals.
Built for fits when finance teams need repeatable 13-week forecasts with scenario comparisons and item-level variance tracking..
Kyriba
Editor pickKyriba ties forecasting inputs to automated bank-connected cash position reporting used in treasury reviews.
Built for fits when treasury teams need bank-linked forecasts with scenario and variance discipline..
PlanGuru
Editor pickDriver-based cash forecasting built from budgeting structure and scenario comparisons inside the same planning model.
Built for fits when finance teams need driver-based scenario forecasting tied to an accounting workflow..
Comparison Table
Dryrun
SMBCash flow forecasting and budget modeling tool for businesses and advisors.
Item-level variance analysis shows which modeled inflows and outflows caused ending cash deviations versus actuals.
Dryrun’s core workflow centers on importing transaction activity, mapping it to forecast items, and then rolling forward a forecast horizon for cash planning. Forecast outputs support variance analysis against actuals, so finance teams can trace which modeled items moved the projected ending cash position. Scenario modeling supports adjusting assumptions and rerunning the forecast to see impacts across multiple planning views.
A key tradeoff is that Dryrun’s forecasting accuracy depends on how consistently cash movements and payment items are mapped, since weak mappings produce noisy variance results. Dryrun fits best when finance teams need a repeatable monthly cash forecast refresh with scenario comparisons, while treasury teams also want audit-ready change tracking for forecast revisions.
- +Bank-connected inputs reduce manual effort for cash movement coverage
- +Scenario modeling supports rapid what-if reruns across assumptions
- +Variance analysis ties forecast items to actual cash movement gaps
- +Recurring forecast templates speed repeat planning cycles
- –Forecast quality drops when transaction to forecast-item mappings are inconsistent
- –Deep ERP-driven modeling may require extra data preparation outside Dryrun
- –Complex consolidation logic can demand careful setup of forecasting structures
- –Automation coverage is strongest for forecast templates, less so for ad hoc modeling
Treasury teams
Monthly cash position forecast refresh
Faster refresh with clearer variances
FP&A teams
Scenario modeling for cash assumptions
Decision-ready scenario comparisons
Show 1 more scenario
Finance operations teams
Recurring payment schedules management
Less manual schedule maintenance
Use recurring templates for accounts receivable and payable scheduling to maintain forecast consistency.
Best for: Fits when finance teams need repeatable 13-week forecasts with scenario comparisons and item-level variance tracking.
Kyriba
enterpriseEnterprise treasury and cash flow forecasting platform with real-time liquidity management.
Kyriba ties forecasting inputs to automated bank-connected cash position reporting used in treasury reviews.
Kyriba is structured for end-to-end cash visibility that begins with bank connectivity and extends through forecast outputs used in treasury decision cycles. Forecasts can be built using both bottom-up inputs and top-down adjustments, then packaged into cash position reports for review and distribution. Scenario modeling supports variance analysis against actuals and planned movement, which helps teams explain forecast deltas to stakeholders.
A common tradeoff is that Kyriba’s forecasting accuracy depends on upstream data hygiene from ERP and treasury feeds, because forecast drivers and scheduling inputs become the baseline for each rolling update. Kyriba is a strong fit when treasury teams must reconcile daily cash movements with a bank feed and then maintain forecast consistency for near-term liquidity planning and approvals.
- +Bank-connected data flows reduce manual cash position updates.
- +Scenario modeling supports variance analysis against plan and actuals.
- +Driver-based inputs support repeatable forecasts across time buckets.
- +Forecast outputs align with treasury reporting workflows.
- –Forecast quality depends on reliable upstream driver and schedule data.
- –Advanced configuration takes time for planning and treasury teams.
- –Workflows require coordination between treasury operations and planners.
- –Large scenario libraries can slow review cycles without tighter controls.
Treasury operations teams
Reconcile bank cash with forecast planning
Fewer stale cash figures
FP&A and treasury planners
Run rolling liquidity scenarios
Clear liquidity tradeoffs
Show 1 more scenario
Finance governance and controls
Maintain approval-ready planning outputs
Consistent decision documentation
Forecast runs and reporting outputs support controlled distribution for finance review cycles.
Best for: Fits when treasury teams need bank-linked forecasts with scenario and variance discipline.
PlanGuru
SMBBudgeting, forecasting, and cash flow projection software for businesses and nonprofits.
Driver-based cash forecasting built from budgeting structure and scenario comparisons inside the same planning model.
PlanGuru’s cash forecasting work centers on building time-phased projections that flow into cash flow reporting, then using scenarios to compare outcomes. The workflow emphasizes account-level inputs and planning steps that match how finance teams already think about budgeting, so cash projections can stay connected to the planning model rather than living as a separate sheet. Scenario modeling and variance analysis support review loops for monthly decision cycles, including what changed versus the prior plan.
A tradeoff appears when organizations need treasury-grade bank connectivity workflows, because PlanGuru’s cash view is strongest when assumptions and accounting mappings are the primary inputs. PlanGuru fits teams that run frequent rolling forecast updates from internal data and want governance around approved assumptions. It is also a practical choice for businesses consolidating department plans into a bottom-up cash view and then testing alternatives for working capital timing.
- +Scenario modeling connects cash outcomes to account-level budgeting assumptions
- +Variance analysis supports repeatable plan versus actual review cycles
- +Forecast structure mirrors finance planning workflows and consolidation
- +Driver-based forecasting improves timing sensitivity beyond static schedules
- –Bank connectivity depth is limited compared with treasury management systems
- –Account-mapping effort increases when assumptions are not already normalized
Finance planning teams
Monthly cash forecast scenario planning
Faster decision cycles on cash needs
Controller and accounting teams
Account-linked projection model
Consistent plan-to-report mapping
Show 1 more scenario
FP&A teams
Working capital timing analysis
Clearer liquidity impact of changes
Adjust drivers for receivables and payables timing to see impacts on projected cash positions.
Best for: Fits when finance teams need driver-based scenario forecasting tied to an accounting workflow.
Cashflow Frog
SMBCash flow forecasting and reporting add-on for QuickBooks and Xero.
Scenario modeling that recalculates outcomes from driver and template changes without rebuilding the forecast structure.
Cashflow Frog brings cashflow forecasting into a spreadsheet-like workflow with driver-based planning and recurring templates for bottom-up rollups. Forecasts can pull cash position inputs from external bank feeds and maintain a rolling view of receipts, payments, debt service, and buffers.
Scenario modeling and variance reporting support direct method and indirect method outputs from the same underlying forecast logic. Admin controls center on workspace governance for shared planning models and controlled access to scenario outcomes.
- +Driver-based forecasting supports repeatable templates for recurring cash flows
- +Scenario modeling links changes to forecast outcomes for faster what-if analysis
- +Bank feed ingestion reduces manual entry for cash position inputs
- +Variance analysis highlights gaps between forecast and actuals at planning horizons
- –Deep ERP mapping often requires extra configuration work for clean driver inputs
- –Large multi-entity consolidations can feel constrained versus treasury suites
Best for: Fits when finance teams want driver-based rolling forecasts with scenario comparisons and lightweight governance.
Float
SMBDedicated cash flow forecasting software integrating with Xero, QuickBooks, and Sage.
Forecast scenario runs update from the same mapped input structure, making variance comparisons consistent across revisions.
Float imports cash transactions and account balances to build forecast timelines used for day-by-day visibility into cash at bank and future liquidity. Forecasting is driven by a configuration of accounts, rules, and assumptions that supports direct method and indirect method views within the same workspace.
Scenario modeling and variance analysis are handled through resimulation of the forecast inputs and comparison against actuals and baseline runs. Automation is centered on importing bank data and mapping it into forecast-relevant categories for rolling updates.
- +Strong forecast timelines tied to mapped accounts and transaction categories
- +Scenario runs preserve a baseline so changes can be compared in variance views
- +Configuration-driven inputs reduce manual spreadsheet rework for recurring updates
- +Bank feed data can be mapped into forecast logic for faster refresh cycles
- –Advanced ERP connector coverage depends on the available integration paths
- –Role management and audit log depth can feel limited for large treasury governance
- –Complex multi-entity consolidation workflows require careful setup discipline
- –Modeling of covenant tracking and debt service schedules is less granular than specialist tools
Best for: Fits when treasury teams need configurable cash forecasting with repeatable scenario and variance workflows.
Trovata
enterpriseAutomated cash flow forecasting and treasury management using open banking APIs.
Forecast variance analysis that attributes differences back to driver inputs, not only end cash totals.
Trovata targets finance teams that need driver-based forecasting tied to bank and accounting data, not just spreadsheet-style scenarios. It focuses on cash planning with configurable logic for working capital drivers, cash position reporting, and rolling views used for operational decisions.
Integration depends on connecting ERP and banking data sources so cash movements can flow into forecast models with automation hooks. The tool’s distinct angle is how it structures forecast inputs around forecast drivers and reconciles them against cash reality for faster variance analysis cycles.
- +Driver-based forecast configuration reduces reliance on manual cash entry
- +Automated variance analysis links forecast deltas to underlying driver movements
- +Bank and accounting integrations feed cash position inputs for planning
- +Rolling forecast support supports ongoing planning and re-forecast cadence
- –Scenario modeling requires disciplined input governance to avoid inconsistent assumptions
- –Complex multi-entity setups can demand careful mapping between sources and forecast logic
Best for: Fits when finance teams run driver-based cash planning and need tighter forecast-to-cash reconciliation than spreadsheets provide.
Fathom
SMBFinancial reporting, analysis, and cash flow forecasting platform.
Scenario modeling built around forecast drivers, with side-by-side outputs that make assumption impacts measurable.
Fathom focuses on cashflow forecasting through a structured workflow for building and maintaining forecast models tied to real operating inputs. The system supports driver-style assumptions and repeatable period updates, then produces cash position outputs suitable for rolling review cycles.
Scenario modeling is used to compare planned versus alternative assumptions and to quantify forecast movement over time. Admin controls center on project-based access and oversight of model changes.
- +Driver-based assumptions make forecast changes easier to trace
- +Scenario comparisons show variance between planned and alternative cases
- +Model updates support recurring forecasting cycles without full rebuilds
- +Project access controls help keep shared models organized
- –Bank feed support is limited versus treasury systems with direct connectivity
- –Complex entity structures may need careful model design up front
- –Automation through API integrations appears narrower than pure fintech treasuries
- –Audit trail depth for cell-level edits is not as granular as expected
Best for: Fits when finance teams need repeatable driver modeling and scenario comparisons with controlled collaboration.
Spotlight Reporting
SMBFinancial reporting and forecasting suite including multi-currency cash flow projections.
Cash position forecasting built around reconciliation to imported bank balance inputs for tighter variance review.
Spotlight Reporting focuses on cashflow forecasting built around structured bank and finance data, then turns that data into a rolling view of expected cash movement. The workflow emphasizes driver-based planning and consolidation of inputs into a cash position report that supports day-by-day planning and variance review.
Reporting also supports bank connectivity workflows used for importing cash balances so forecasts can be reconciled against what actually hits the bank. Teams use it to run scenario modeling for liquidity planning and to track movement across accounts tied to forecasts.
- +Forecast outputs are organized around cash position reporting and reconciliation workflows
- +Driver-based planning helps map operational inputs into cash timing
- +Scenario modeling supports alternate assumptions for liquidity outcomes
- +Bank import workflows reduce manual rekeying of starting cash balances
- –Scenario complexity can increase model maintenance effort when assumptions change often
- –Bank connectivity coverage depends on supported import formats and file layouts
Best for: Fits when finance teams need rolling cash forecasts tied to bank imports and scenario runs.
Agicap
SMBCash flow management and forecasting platform for European and international SMBs.
Driver-based forecasting engine built around configurable liquidity assumptions for scenario comparisons.
Agicap builds driver-based cash forecasting that turns bank cash positions and payment schedules into a rolling view of expected liquidity. It supports scenario modeling with configurable assumptions for receipts, disbursements, and cash constraints so teams can test outcomes across planning horizons.
Bank connectivity and cash position reporting feed the forecast loop, which helps keep variance analysis grounded in actual movements. The main differentiator is operational planning depth for treasury workflows, not just charting forecasts.
- +Driver-based forecasting that ties cash outcomes to adjustable assumptions
- +Scenario modeling supports multiple planning cases from one forecast base
- +Direct bank feed keeps cash at bank aligned with forecasts
- +Variance analysis highlights forecast vs actual deviations by period
- –Setup requires disciplined mapping of cash drivers to payment sources
- –Advanced governance controls feel lighter than enterprise treasury suites
- –Complex consolidation across legal entities can take more configuration time
- –Some ERP connector scenarios depend on clean source master data
Best for: Fits when treasury teams need a rolling forecast with scenario testing and variance control from bank-linked cash data.
Jirav
SMBFP&A and cash flow forecasting platform integrating accounting and payroll data.
Templates that standardize driver inputs and keep scenario runs consistent across forecast iterations.
Jirav targets finance teams that need a spreadsheet-like cash forecasting workflow with tighter controls than manual 13-week rolling spreadsheets. It builds forecasts from driver-based assumptions and consolidates outputs into cash position reporting, with variance analysis to track plan versus actuals.
The tool also supports bank data inputs for cash visibility and helps automate recurring forecast updates instead of rerunning models from scratch. Governance features focus on consistent templates, workbook structure, and controlled edits across forecast cycles.
- +Driver-based forecasting reduces manual rebuilds of 13-week cash scenarios
- +Variance views connect forecast changes to cash position movement
- +Controlled templates help keep multi-user forecast inputs consistent
- +Recurring forecast cycles reduce repeated spreadsheet recalculation work
- –Bank connectivity depth depends on the specific bank file format workflow
- –Advanced treasury workflows like liquidity gap analysis require extra model setup
- –Scenario modeling is constrained by the underlying template structure
- –Automation coverage can feel light compared with treasury management system integration
Best for: Fits when mid-market teams want controlled, driver-based cash forecasts with repeatable cycles.
Conclusion
After evaluating 10 finance financial services, Dryrun stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right cashflow forecasting software
Cashflow forecasting software turns expected inflows and outflows into a rolling view of cash at bank for planning and treasury reviews, with scenario modeling that reruns forecasts from changed assumptions. This guide covers Dryrun, Kyriba, PlanGuru, plus Cashflow Frog, Float, Trovata, Fathom, Spotlight Reporting, Agicap, and Jirav.
The reviewed tools differ most in how they connect inputs to modeled cash timing, how they attribute variances to drivers or item-level causes, and how they handle bank-connected cash position reporting. Dryrun leads on item-level variance analysis, Kyriba focuses on bank-linked cash position reporting tied to forecasting inputs, and PlanGuru emphasizes driver-based forecasting built inside the budgeting workflow.
Cashflow Forecasting Software for Rolling 13-Week Forecasts, Scenario Modeling, and Forecast-to-Cash Variance Discipline
Cashflow forecasting software builds cash projections from mapped drivers, templates, and budgeting structure so teams can run repeatable forecast iterations and compare outcomes across scenarios. Many implementations include variance analysis that links plan versus actuals back to the underlying modeled inflows and outflows, with Dryrun highlighting item-level variance tracking for ending cash deviations.
Tool choices often hinge on integration depth and automation surface, such as whether forecasting inputs are refreshed from bank-connected cash position reporting or whether inputs depend on driver and schedule data from upstream systems. Kyriba ties forecasting inputs to automated bank-connected cash position reporting used in treasury reviews, while PlanGuru connects scenario modeling to account-level budgeting assumptions within its planning model.
Cashflow forecasting criteria that change planning outcomes
Cashflow forecasting software succeeds when it converts mapped inflows and outflows into repeatable forecast iterations and keeps forecast changes explainable. These capabilities matter more than UI comfort because teams must reconcile forecast-to-cash differences in treasury and finance reviews.
The biggest differentiators are how each tool attributes variance to underlying drivers or modeled items, how it refreshes inputs from bank-connected workflows, and how scenario runs stay consistent across revisions. Dryrun, Kyriba, and PlanGuru illustrate three distinct paths to that control.
Variance attribution granularity
Dryrun pinpoints modeled inflows and outflows that caused ending cash deviations versus actuals. Kyriba focuses on scenario and variance discipline tied to bank-connected cash position reporting.
Scenario modeling mechanics for forecast reruns
Cashflow Frog recalculates outcomes from driver and template changes without rebuilding forecast structure. Float preserves a baseline and then runs scenario comparisons off the same mapped input structure.
Driver-based configuration tied to planning assumptions
PlanGuru builds driver-based cash forecasting from budgeting structure and keeps scenario comparisons inside its planning model. Trovata configures driver-based forecasts and then automates variance analysis back to driver movements.
Bank-connected cash position refresh and reconciliation workflow fit
Kyriba ties forecasting inputs to automated bank-connected cash position reporting used in treasury reviews. Spotlight Reporting organizes cash position forecasting around reconciliation to imported bank balance inputs for tighter variance review.
Multi-entity and mapping workload tolerance
Agicap supports driver-based rolling forecasts but needs disciplined mapping of cash drivers to payment sources. Fathom can require careful model design up front when complex entity structures are involved.
A decision path for forecasting control, data freshness, and variance explainability
The right cashflow forecasting software depends on where the system gets truth for timing and how it explains forecast deltas. Teams that rely on bank-verified cash positions usually prioritize bank-connected workflows, while teams that rely on budgeting assumptions usually prioritize driver-based modeling.
The decision should start with variance ownership and then move to input refresh and governance friction. Dryrun and Kyriba show two different end targets, and PlanGuru and Cashflow Frog show two different modeling philosophies.
Choose the variance story the business must act on
Select Dryrun if ending cash deviations must be traced to specific modeled inflows and outflows that drove the variance versus actuals. Select Kyriba if variance discipline is tied to bank-linked cash position reporting that supports treasury review cycles.
Pick the scenario workflow that matches how assumptions change
Choose Cashflow Frog when driver and template changes should trigger scenario recalculation without rebuilding the forecast structure. Choose Float when scenario runs must preserve a baseline so revisions compare cleanly in variance views.
Decide whether forecasting starts from budgeting structure or driver configuration
Choose PlanGuru when driver-based cash forecasting must connect directly to account-level budgeting assumptions inside the same planning workflow. Choose Trovata when driver-based configuration must feed automated variance analysis that attributes forecast deltas to driver movements.
Match input refresh to treasury operations and reconciliation habits
Choose Kyriba when bank-connected cash position reporting is already the system used for treasury reviews and forecasting inputs must stay aligned to it. Choose Spotlight Reporting when imported bank balance inputs drive rolling cash forecasts with reconciliation-centered outputs.
Validate mapping and governance load for the first model
Choose Jirav when templates must standardize driver inputs for consistent scenario runs across forecast iterations for mid-market cycles. Choose Agicap when liquidity assumptions are the planning lever, but require disciplined mapping of cash drivers to payment sources to keep scenarios credible.
Who should use each forecasting approach
Cashflow forecasting software fits teams that must run repeatable forecast cycles and then explain differences between forecasted cash and observed cash. The best fit depends on whether the organization treats variance as an item-level breakdown problem or as a driver discipline problem tied to treasury reporting.
The tools below map to distinct operating models for finance and treasury, not just feature checklists.
Treasury teams running bank-linked cash position reviews
Kyriba ties forecasting inputs to automated bank-connected cash position reporting used in treasury reviews, so forecast refresh stays aligned to cash position workflows.
Finance teams that must reconcile forecast deltas to modeled cash movements
Dryrun’s item-level variance analysis identifies which modeled inflows and outflows caused ending cash deviations versus actuals, which supports action-oriented variance reviews.
Planning organizations that manage forecasting from budgeting assumptions
PlanGuru connects scenario modeling to account-level budgeting assumptions inside the same planning model, so cash outcomes follow budgeting changes with traceability.
Teams that run frequent what-if scenarios with stable templates
Cashflow Frog recalculates outcomes from driver and template changes without rebuilding forecast structure, which reduces friction when assumptions shift often.
Mid-market teams standardizing driver inputs across cycles
Jirav templates standardize driver inputs and keep scenario runs consistent across forecast iterations, which reduces manual rebuilds of 13-week cash scenarios.
Common failures during cash forecasting software rollout
Rollout failures usually come from mismatched data relationships between modeled items, drivers, and the bank or accounting sources used for validation. Many tools can produce forecasts quickly, but forecast credibility depends on mapping consistency and on how scenario reruns handle changed assumptions.
These mistakes show up during pilot cycles and then repeat during monthly or weekly forecast iterations.
Using forecast item mappings that are inconsistent across revisions
Dryrun’s forecast quality drops when transaction-to-forecast-item mappings are inconsistent, so mapping rules must be stabilized before running scenario comparisons.
Treating scenario modeling as a one-time build rather than an input-governance system
Trovata’s scenario modeling requires disciplined input governance to avoid inconsistent assumptions, so driver definitions and schedules need ownership before scaling.
Underestimating the model-design effort needed for clean driver inputs from ERP
Cashflow Frog can require extra configuration work for clean driver inputs when ERP-driven mappings are deep, so integration scoping should include mapping normalization steps.
Assuming bank connectivity depth will match treasury suite expectations
PlanGuru has limited bank connectivity depth compared with treasury management systems, so teams that require direct connectivity should validate the integration path against their operational bank workflow.
Overbuilding entity structures before confirming mapping capacity
Fathom can require careful model design up front for complex entity structures, so the first build should validate entity mapping throughput before adding advanced collaboration.
How We Selected and Ranked These Tools
We evaluated how each cashflow forecasting software supports scenario modeling reruns, forecast-to-cash variance discipline, and bank-linked input refresh workflows. Features accounted for 40% of the scoring because variance attribution and scenario mechanics determine whether teams can explain forecast changes consistently.
Ease and value each accounted for 30% because forecast mapping effort and configuration overhead decide how quickly a model becomes usable in recurring cycles. Dryrun earned the top ranking because item-level variance analysis identifies which modeled inflows and outflows caused ending cash deviations versus actuals, which makes forecast-to-cash differences actionable instead of only directional.
Frequently Asked Questions About cashflow forecasting software
How do Dryrun and Kyriba handle driver-based scenarios when only parts of the forecast change?
When a cash flow forecast must follow a direct method and an indirect method, which tools support both views from one model?
Which tool is better for reconciling forecast cash movements to imported bank balances and then explaining variances?
What breaks if bank connectivity fails during a rolling forecast run in Float or Agicap?
How do PlanGuru and Jirav differ in how forecasting structure is maintained across cycles?
How do forecasting automation workflows differ between Kyriba and Dryrun?
Where does data migration typically matter most when moving an existing model into Fathom or Jirav?
How do admin controls and collaboration differ in Fathom versus Kyriba?
What integration and API expectations should teams set before choosing Trovata or Spotlight Reporting?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
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- Supply Chain In IndustryTop 10 Best Supply Chain Forecasting Software of 2026
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