Financial Modeling Software: Features, Integrations, Success Factors, Benefits
ScienceSoft combines 15 years of experience in financial software development with 33 years in AI and 17-year expertise in BI to help businesses implement robust financial modeling solutions powered with cutting-edge data analytics techs.
Financial Modeling Software: The Essence
Financial modeling software is used to create and manage financial models, automate calculations for various financial models, simulate, analyze and forecast financial scenarios of any complexity. Software offers multi-dimensional modeling, automated model updating with new financial data, facilitated collaboration with internal teams and strategic partners on financial modeling processes, and more.
When powered with advanced big data analytics and data visualization techs, such solutions enable businesses to embrace a highly efficient approach to the aggregation, analysis, and interpretation of financial data. They help drive the extraordinary level of accuracy across operational, investment, and financing decisions and ensure informed, data-driven planning of strategic corporate transactions, such as mergers and acquisitions.
ERP, CRM, an accounting system, treasury software, and more.
6 – 10 months for a custom financial modeling solution.
$200,000 – $400,000, depending on the solution complexity.
- Cost model.
- Revenue model.
- Budget model.
- Investment portfolio performance model.
- Financial risk model.
- Three statement model.
- Discounted cash flow (DCF) model.
- Merger and acquisition (M&A) model.
- Initial public offering (IPO) model.
- Asset and liability (ALM) model.
- Leveraged buyout (LBO) model.
- Sum-of-the-parts model.
- Option pricing model,
- and more.
- Aggregating various types of historical financial data from relevant business systems (ERP, an accounting system, treasury software, etc.).
- Template-based generation of financial models based on the collected data.
- Building custom financial models with user-defined parameters and variables.
- AI recommendations on relevant financial data and parameters to include in a financial model.
- Creating custom natural language formulas to calculate industry- and business-specific financial metrics, e.g., revenue per square foot for retail, CLV for SaaS businesses.
- Multi-currency financial models.
- Configurable hierarchies between different financial models.
- Multi-entity financial modeling.
- Collaborative modeling.
- Automated calculation of user-defined financial parameters under various models.
- Automated adjustment of a financial model as new financial data appear.
- Real-time monitoring of financial model variance and notification of the areas of poor/superior model performance.
- Automated model version control to track model changes at the data, logic and structure level.
- Trend analysis, including time series analysis, to compare financial model data across user-defined periods and identify financial performance trends.
- ML-powered analysis of historical financial and business data provided in the financial model to reveal patterns in complex interdependencies between various financial and non-financial variables (e.g., production volume and cost per unit or the number of employees and operating expenses).
- Multi-dimensional sensitivity analysis to assess the impact of particular variables on other parameters and identify key drivers for various financial models.
- Detailed planning of operating, non-operating, capital expenses based on the analysis of relevant data, such as historical cost data, operational and strategic plans (e.g., production plans, workforce plans, investment plans).
- Expense forecasting based on the analysis of current expense data.
- Operating and non-operating income forecasting (including revenue, dividends, interest earned) based on the analysis of current and historical data on sales, debt and investment transactions, financial market data projections on FX, interest and credit rates.
- Template-based creation of time-framed budgets (at the enterprise, department, project level).
- Scenario modeling and what-if analysis for each financial model.
- AI-powered probability assignment to different scenarios.
- Monte Carlo simulations to quantify the impact of risk and uncertainty factors, e.g., the performance of financial market players or changes in governmental regulation policy.
- Comprehensive scenario comparison based on AI-enabled scenario profitability analysis, regression analysis, stress testing, prospective/retrospective effectiveness tests (for derivatives), and more.
- AI-based suggestions on optimal and risky financial scenarios.
- Scenario testing by multiple users independently within the same financial model.
- Support for various visualization types (drill-down dashboards with customizable charts, graphs, tables, interactive maps, and more).
- Configurable financial model visualizations for various departments, business entities, customers, investors.
- Side-by-side visualization of multiple financial modeling scenarios.
- Multi-factor authentication.
- Data encryption.
- Configurable user permissions based on the user responsibility (financial modeler, financial analyst, risk manager, CFO, etc.).
- Role-based access control.
- Audit trail of all user activities.
To streamline and speed up financial data aggregation from relevant sources, ScienceSoft recommends integrating the financial modeling solution with the following systems:
- ERP – to build budgeting and forecasting models for various types of expenses; for data-driven operational and strategic planning.
- Accounting software – for accurate modeling of company’s financial performance.
- CRM – for accurate sales revenue modeling.
- Treasury software – to model and forecast financial results of various investment and financing projects; for data-driven planning of investment, financing, risk management activities.
- Financial data marketplace – to model investment, financing, hedging strategies based on relevant financial market data.
High-quality input data
To ensure financial model reliability and financial forecasting accuracy.
User-friendly financial model visualization
To provide intuitive and well-structured representation of financial data for facilitated financial risk and opportunity identification.
AI-enabled financial performance forecasting
To accurately model predictions on a business’s financial performance and financial results of strategic investment and financing activities.
On-the-fly scenario modeling
To enable real-time what-if analysis and visualization even of complicated financial scenarios for facilitated collaborative scenario testing, e.g., during meetings or presentations.
Data-level user permissions
To limit access to particular financial models or model parts containing sensitive financial data.
ScienceSoft’s Head of Data Analytics Department Alex Bekker shares his expertise
"Financial modeling software development may require creation and training of complex machine learning models for financial analysis and forecasting. I recommend involving professional data scientists to design the finance models and tune them at the model training stage. It helps employ proper models for various types of business transactions and accurately identify main factors affecting the company’s financial performance."
The costs of building the financial modeling system vary greatly depending on:
- The number and complexity of a solution’s functional modules, including the number of AI-enabled features.
- The volume of data to be migrated from spreadsheets and/or existing financial modeling software.
- The number and complexity of integrations with ERP, CRM, an accounting system, treasury software, etc.
Custom financial modeling software of average complexity requires $200,000–$400,000 in investments.
Don’t miss out on the amazing benefits you can get with financial modeling software:
faster financial model creation due to automated financial data consolidation and customizable financial model templates.
Up to x40
faster financial model updating due to automated input of new relevant financial data.
more accurate financial models due to eliminated manual error.
visibility of an organization's projected financial performance due to clear, well-structured data representation in a financial model.
decision-making on strategic and financial activities with real-time, analytics-based insights on their financial outcomes.
financial risks due to ability to proactively identify and avoid risk-prone financial scenarios.
Off-the-Shelf Financial Modeling Software ScienceSoft Recommends
IBM Cognos Analytics
Best for: advanced financial model analysis and visualization
- Financial modeling dashboards with customizable charts, graphs, tables, scorecards, interactive maps, and more.
- AI-powered financial performance forecasting.
- Intelligent recommendations on relevant financial data and parameters to include in a financial model.
Cautions: Substantial product costs for large teams. An additional license is required for app administration, security, user onboarding.
- Scenario modeling and what-if analysis.
- Time series financial modeling.
- Real-time monitoring of financial model variance.
- Built-in chart templates, including comparison charts, trend charts, correlations charts, map charts, and more.
- Scheduled/ad-hoc generation and sending of personalized financial reports.
- A native mobile app to access financial models on the go.
- On Demand plan: $10 user/month for a standard pack, $40 user/month for a premium pack.
- On Cloud Hosted plan: $80 user/month, $40 user/month for viewing only, $5 user/month for mobile access only.
- Client Hosted plan: $450 user/month for an administration license, $40 user/month for a standard pack, $75 user/month for an advanced pack, $12 user/month for viewing only, $5 user/month for mobile access only.
- A free 30-day trial.
Best for: collaborative financial modeling
- Real-time multi-user viewing and editing of financial models.
- Configurable user roles and data-level permissions.
- Automated model version control.
- A built-in instant messaging tool.
- Multi-dimensional financial calculations.
- Automated model adjustment based on real-time financial data.
- AI-powered forecasting based on the analysis of historical and current financial data.
- Time-framed financial modeling.
- Scenario modeling and what-if analysis.
- Comprehensive audit trail to track the finance model changes.
- Interactive dashboards with customizable tables, widgets, branding fields, and more.
Upon request to the vendor.
Best for: scenario modeling and risk analysis
- Monte Carlo simulations and risk analysis.
- On-the-fly scenario modeling and comparison during meetings or presentations.
- Self-service financial model stress testing and what-if analysis without model changing for authorized stakeholders.
Cautions: Limitations on the number of users, financial models, what-if scenarios per financial model based on the subscription plan.
- Multi-dimensional financial model sensitivity analysis.
- Automated calculation of user-defined financial and business ratios.
- Creating custom natural language formulas.
- Real-time financial model scanning for errors, root cause analysis.
- Collaborative financial modeling.
- Configurable model access permissions at the worksheet, report and dashboard level.
- Basic plan: Free.
- Dashboards plan: $9 – 18 user/month.
- Dashboards + Auto-analysis plan: $47 – 97 user/month.
- A free 7-day trial.
You need to build complex, non-standard financial models, e.g., for multi-entity financial performance modeling or forecasting financial outcomes of large-scale financing and investment projects in the long run.
You want to avoid costly, effort-consuming integration of financial model software with your legacy systems (ERP, CRM, accounting software, etc.).
You have large teams involved in financial modeling and want to avoid a considerable subscription amount for platform-based financial modeling software, which scales with the number of users.
Financial modeling software consulting
- Analysis of your financial modeling needs.
- Assessment of the existing financial modeling processes, tools and their integration points (if any).
- Suggesting optimal features, architecture, tech stack for financial modeling software.
- Preparing an integration plan (with ERP, CRM, accounting software, treasury software, etc.).
- Implementation cost & time estimates, expected ROI calculation.
Financial modeling software implementation
- Financial modeling needs analysis.
- Financial modeling solution conceptualization.
- Architecture design for a financial modeling solution.
- Financial modeling software development.
- Integrating the solution with the relevant systems (ERP, CRM, accounting software, treasury software, etc.).
- Quality assurance.
- User training.
- Continuous support and evolution (if required).
ScienceSoft is an international IT consulting and software development company headquartered in McKinney, Texas. We provide consultancy and development services to help businesses build effective financial modeling software. Being ISO 9001 and ISO 27001 certified, we apply a mature quality management system and guarantee that cooperation with us does not pose any risks to our customers’ data security. If you are interested in getting a reliable financial modeling solution, feel free to turn to ScienceSoft’s team.