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Custom Financial Modeling Software: Features, Integrations, Cost, Benefits

Financial Modeling Software - ScienceSoft

ScienceSoft combines 17 years of experience in financial software development with 35 years in AI and 19 years 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 enables multi-dimensional modeling, automates model updating with new financial data, and helps facilitate collaboration between internal teams and strategic partners on financial modeling processes. Custom financial modeling software is used to create and manage unique financial models, automate specific calculations, simulate, analyze and forecast financial scenarios of any complexity.

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.

Integrations

ERP, CRM, an accounting system, treasury software, and more.

Implementation time

6–10 months for a custom financial modeling solution.

Implementation costs

$200,000–$400,000+, depending on the solution complexity. Use our cost calculator to estimate your tailored solution.

Key Features of Financial Modeling Software

At ScienceSoft, we design functionality of financial modeling solutions for our clients based on their unique business needs. Here, we share a sample feature set that forms the core of the described software.

Financial model templates
Financial model creation
Financial model management
Financial model data analysis
Financial planning and forecasting
Scenario modeling
Financial model visualization
Security

Financial model templates

  1. Cost model.
  2. Revenue model.
  3. Budget model.
  4. Investment portfolio performance model.
  5. Financial risk model.
  6. Three statement model.
  7. Discounted cash flow (DCF) model.
  1. Merger and acquisition (M&A) model.
  2. Initial public offering (IPO) model.
  3. Asset and liability (ALM) model.
  4. Leveraged buyout (LBO) model.
  5. Sum-of-the-parts model.
  6. Option pricing model,
  7. and more.

Financial model creation

  1. Aggregating various types of historical financial data from relevant business systems (ERP, an accounting system, treasury software, etc.).
  2. Template-based generation of financial models based on the collected data.
  3. Building custom financial models with user-defined parameters and variables.
  4. AI recommendations on relevant financial data and parameters to include in a financial model.
  1. 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.
  2. Multi-currency financial models.
  3. Configurable hierarchies between different financial models.
  4. Multi-entity financial modeling.
  5. Collaborative modeling.

Financial model management

  1. Automated calculation of user-defined financial parameters under various models.
  2. Automated adjustment of a financial model as new financial data appear.
  3. Real-time monitoring of financial model variance and notification of the areas of poor/superior model performance.
  1. Automated model version control to track model changes at the data, logic and structure level.

Financial model data analysis

  1. Trend analysis, including time series analysis, to compare financial model data across user-defined periods and identify financial performance trends.
  2. 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).
  1. Multi-dimensional sensitivity analysis to assess the impact of particular variables on other parameters and identify key drivers for various financial models.

Financial planning and forecasting

  1. 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).
  2. Expense forecasting based on the analysis of current expense data.
  1. Template-based creation of time-framed budgets (at the enterprise, department, project level).
  2. 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.

Scenario modeling

  1. Scenario modeling and what-if analysis for each financial model.
  2. AI-powered probability assignment to different scenarios.
  3. 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.
  1. AI-based suggestions on optimal and risky financial scenarios.
  2. Comprehensive scenario comparison based on AI-enabled scenario profitability analysis, regression analysis, stress testing, prospective/retrospective effectiveness tests (for derivatives), and more.
  3. Scenario testing by multiple users independently within the same financial model.

Financial model visualization

  1.  Support for various visualization types (drill-down dashboards with customizable charts, graphs, tables, interactive maps, and more).
  2. Configurable financial model visualizations for various departments, business entities, customers, investors.
  1. Side-by-side visualization of multiple financial modeling scenarios.

Security

  1. Multi-factor authentication.
  2. Data encryption.
  3. Configurable user permissions based on the user responsibility (financial modeler, financial analyst, risk manager, CFO, etc.).
  1. Role-based access control.
  2. Audit trail of all user activities.

Important Integrations for Financial Modeling Software

To streamline and speed up financial data aggregation from relevant sources, ScienceSoft recommends integrating the financial modeling solution with the following systems:

Essential Integrations for Financial Modeling Software - ScienceSoft

  • 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.

How to Achieve High ROI for Financial Modeling Software

To maximize the value and cost-efficiency of a financial modeling solution, ScienceSoft always seeks to cover the following important factors:

High-quality input data

To ensure high accuracy and reliability of financial modeling results.

On-the-fly scenario modeling

To enable real-time what-if analysis and visualization for facilitated collaborative scenario testing, e.g., during meetings or presentations.

AI-enabled financial performance forecasting

To accurately model predictions on a business’s financial performance and financial results of strategic investment and financing activities.

User-friendly financial model visualization

To provide intuitive and well-structured representation of financial data for facilitated financial risk and opportunity identification.

ScienceSoft’s Head of Data Analytics Department Alex Bekker shares his expertise:

Financial modeling software development may require the creation and training of complex ML models for financial analysis. I recommend involving professional data scientists to design the models and tune them at the training stage. It helps employ proper models for various finance areas and accurately identify the factors affecting financial performance.

Check Alex's profile

Explore ScienceSoft's Featured Projects

Financial Modeling Software Development: Key Steps

Financial modeling software development involves a range of important processes aimed to ensure risk-free project implementation, top-flight solution quality and its seamless operation in the long run. Below, ScienceSoft lists the main steps of the financial modeling software implementation flow.

1

Business needs analysis and eliciting requirements for the financial modeling solution.

2

Designing the functionality, architecture, UX and UI for the solution.

3

Tech stack selection.

4

Project planning: scope, deliverables, team composition, timelines, budget, etc.

5

Financial modeling software development.

6

(for ML-powered solutions) Financial model design, training, and tuning.

7

Quality assurance.

8

Integration with the required corporate systems and third-party financial data sources.

9

User training.

10

Continuous support and evolution of the financial modeling solution (optional).

Financial Modeling Software Development Costs

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.

Based on ScienceSoft's experience, developing custom financial modeling software of average complexity may cost around $200,000–$400,000. Get a personalized estimate with our online cost calculator.

Benefits of Financial Modeling Software

  • 10x

    faster financial model creation due to automated financial data consolidation and customizable financial model templates.

  • Up to 40x

    faster financial model updating due to automated input of new relevant financial data.

  • 9x

    more accurate financial models due to eliminated manual error.

  • Enhanced

    visibility of an organization's projected financial performance due to clear data representation in a financial model.

  • Improved

    decision-making on strategic and financial activities with real-time, analytics-based insights on their financial outcomes.

  • Reduced

    financial risks due to ability to proactively identify and avoid risk-prone financial scenarios.

Off-the-Shelf Financial Modeling Software ScienceSoft Helps Implement

IBM Cognos Analytics

Best for: advanced financial model analysis and visualization

Description

Key strengths:

  • 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.

Features

  • 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.

Pricing

  • 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.
LEARN MORE

Quantrix

Best for: collaborative financial modeling

Description

Key strengths:

  • 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.

Features

  • Multi-dimensional financial calculations.
  • Automated model adjustment based on real-time financial data.
  • AI-powered forecasting based on the analysis of historical 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, etc.

Pricing

Upon request to the vendor.

LEARN MORE

Visyond

Best for: scenario modeling and risk analysis

Description

Key strengths:

  • 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.

Features

  • 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 report and dashboard levels.

Pricing

  • Basic plan: Free.
  • Dashboards plan: $9 – 18 user/month.
  • Dashboards + Auto-analysis plan: $47 – 97 user/month.
  • A free 7-day trial.
LEARN MORE

When to Opt for Custom Financial Modeling Software

Custom financial modeling software is aimed to introduce specific capabilities that off-the-shelf solutions cannot provide to digitally transform complex and unique model management, analytics, and forecasting workflows.

ScienceSoft recommends choosing custom development in the following cases:

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 leverage AI-supported financial modeling automation to get accurate data-driven forecasts and prescriptions on the optimal financial activities.

You want to avoid costly and effort-consuming integration of financial model software with your business systems (ERP, CRM, accounting software, etc.).

You want to establish limited access to particular financial models or model parts containing sensitive financial data and need a solution offering advanced cybersecurity mechanisms.

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.

Development of Financial Modeling Software with ScienceSoft

In corporate finance software development since 2007, ScienceSoft helps companies build effective financial modeling software.

Financial modeling software consulting

  • Analysis of your financial modeling needs.
  • Assessment of the existing financial modeling processes and tools (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.
Request consulting

Financial modeling software implementation

  • Financial modeling solution conceptualization.
  • Architecture design for a financial modeling solution.
  • Financial modeling software development.
  • Integrating the solution with the relevant systems.
  • Quality assurance.
  • User training.
  • Continuous support and evolution (if required).
Request implementation

About ScienceSoft

ScienceSoft is a global 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 an ISO 9001- and ISO 27001-certified company, we apply a mature quality management system and guarantee that cooperation with us does not pose any risks to our clients’ data security.