Real-time bank account aggregation
Direct bank API connections that pull balances and transactions across accounts, entities, and currencies into one view.
Cash flow visibility is the difference between a proactive treasury team and one that finds out about a shortfall too late, so we treat forecasting accuracy and real-time bank data as architecture decisions. Every delivered system by Svitla reconciles forecasted and actual cash positions and logs every assumption behind a forecast from day one.
Before writing code, we map your bank accounts, accounting systems, and existing forecasting spreadsheets, so integration complexity and data quality issues surface at the start.
Your forecast lives in a model one person maintains, and it breaks the moment they’re out sick. We build a system that doesn’t depend on any one person’s spreadsheet.
Consolidating cash across entities and currencies by hand is slow and error-prone. We build automated consolidation that gives treasury one accurate global view.
A forecast that missed badly once is hard to trust again. We build forecasting grounded in actual payment behavior, not optimistic assumptions.
A cash flow forecast that’s wrong doesn’t fail gradually, it fails exactly when the business needs it most, at the moment a shortfall was supposed to be predicted. Here’s where that failure usually starts.
We’ll discuss your business goals, budget, and timeline, then map your current forecasting process and data sources.
We look at how customers and vendors actually pay today, not just their contractual terms, and where your current forecast diverges from reality.
We’ll craft a plan based on your requirements and assemble a team of specialists with experience in treasury and financial software.
Our engineers build the solution, delivering working functionality in short, reviewed cycles so you see forecasting logic working early.
We test forecast accuracy against your actual historical cash positions before launch, not a hypothetical scenario.
Below, Svitla shares a sample feature set that forms the core of a cash flow analysis solution. Each real-life use case is unique, so you should elaborate on the functionality and tailor it to your business specifics.
Direct bank API connections that pull balances and transactions across accounts, entities, and currencies into one view.
Short- and long-term forecasts that update automatically as actuals come in, rather than static one-time projections.
Best-case, worst-case, and custom scenario modeling to stress-test liquidity against different assumptions.
Early flagging of unusual transactions or projected cash shortfalls before they become a crisis.
AI-supported tagging of bank transactions into cash flow categories, reducing manual reconciliation work.
Rollup of cash positions across subsidiaries, currencies, and bank relationships for a group-level view.
Automated comparison of forecasted versus actual cash flow to improve forecasting accuracy over time.
Configurable liquidity dashboards and exportable reports for treasury, FP&A, and board reporting.
Answer a few simple questions to find out whether you should choose a custom solution or a pre-built cash flow platform.
Do you manage cash across multiple banks, entities, or currencies?
Does your current tool’s forecasting methodology fail to match how your business actually generates and uses cash?
Does your team still spend significant time manually rebuilding cash flow forecasts in spreadsheets?
Do you need the system to integrate with a specific bank, accounting system, or ERP?
Have you been surprised by a cash shortfall that your forecast didn’t catch in time?
Do you need scenario planning to stress-test liquidity under different assumptions?
Do you need AI-based capabilities such as anomaly detection, automated categorization, or shortfall forecasting?
Have you already tried an off-the-shelf cash flow platform that didn’t cover your workflows?
Do you plan to keep scaling your bank accounts or entity structure over the next 2–3 years?
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In Svitla’s projects, we consistently aim to address the key factors that drive maximum value and cost-effectiveness in cash flow analysis software:
Automated, AI-supported forecasting flags liquidity gaps early enough to arrange financing or adjust spending before they become urgent.
Automated bank feeds and rolling forecasts eliminate the weekly rebuild of spreadsheet-based cash flow models.
Systematic variance analysis between forecasted and actual cash flow improves model accuracy with every cycle.
Clear, consolidated visibility into cash positions across entities and banks supports more effective short-term investment decisions.
Consolidated visibility into balances across banks strengthens your negotiating position and reduces unnecessary short-term borrowing.
Automated dashboards reduce the time treasury and FP&A spend preparing liquidity reports for leadership and the board.
Developing cash flow analysis software means building a forecast that survives contact with how customers and vendors actually behave, not how their contracts say they should. At Svitla, we implement cash flow analysis systems in six stages.
We analyze your treasury objectives, current forecasting process, and gather detailed requirements that reflect real payment behavior, not just stated terms.
We define the optimal feature set, forecasting model, and technology stack tailored to your entity structure and currency exposure.
We outline the project scope, deliverables, timeline, budget, and team structure, so treasury, finance, and IT stakeholders share the same expectations before development starts.
Our engineers build the solution iteratively, delivering working forecasting functionality in short, reviewed cycles.
We verify forecast accuracy and consolidation logic against real historical data, then connect the system to your banking, ERP, and FX data sources, testing each integration against live data.
We train treasury and finance staff on the new workflows before rollout. After launch, we offer ongoing technical support and implement enhancements as your entity structure and business requirements evolve.
Based on Svitla’s experience, the average cost of building custom market data analysis software ranges from $80,000 to $500,000, depending on solution complexity.
Want to understand the cost of your cash flow analysis software?
Calculate the costPlease answer a few quick questions about the cash flow analysis solution you’re looking to build. This will help our experts better understand your needs and calculate a tailored quote much faster.
Thank you! We will be in touch soon.
What our clients say about us
Real feedback from teams who worked with us on forecast accuracy, multi-entity consolidation, and early warning system challenges like these.
A closer look at real projects where behavior-based forecasting, bank reconciliation, or scenario modeling were part of the challenge, not just the pitch.
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With 17 years of experience in engineering financial software and practical knowledge of 10+ industries, Svitla offers full-cycle consulting and engineering services to deliver effective cash flow analysis solutions.
Cash flow forecasting and treasury process needs analysis.
Audit of the existing cash flow tools and forecasting methods (if any).
Recommendations on optimal features, architecture, and tech stack.
A plan of integrations with your banks, accounting software, and treasury systems.
Implementation cost and time estimates, expected ROI calculation.
Cash flow analysis solution conceptualization and architecture design.
Custom development of the cash flow analysis system.
Integration with the necessary financial systems.
Quality assurance and user training.
Continuous support and evolution (if required).
Yes. We have experience building software for regulated entities and complex, multi-entity organizations, and understand the compliance requirements, security standards, and audit processes involved. Our team is familiar with SOX, GDPR, and industry-specific reporting requirements.
We build security into the architecture, not add it afterward. We apply encryption in transit and at rest, role-based access controls, secure development practices, and complete audit logging of every forecast, assumption, and data source.
Yes. Integration with your banks, accounting software, ERP, and treasury management system is planned in the first project phase. We work with commonly used systems via their APIs and build custom connectors where standard ones don’t exist.
Custom development pays off when your forecasting methodology or entity structure doesn’t fit standard templates, when per-entity or per-account licensing becomes expensive at scale, or when you need integrations and AI features that packaged platforms don’t offer. If a pre-built platform covers your needs, we’ll tell you, and can help implement it instead.
The timeline depends on the feature scope, bank integrations, and entity structure involved. We typically deliver in phases, starting with a working core (bank data aggregation and basic forecasting), so you see value before the full rollout.
Yes. We offer post-launch support and enhancement engagements: monitoring, maintenance, and the implementation of new features as your bank relationships and forecasting needs evolve.