Best Finance Software for JMP Statistical Software

Compare the Top Finance Software that integrates with JMP Statistical Software as of August 2026

This a list of Finance software that integrates with JMP Statistical Software. Use the filters on the left to add additional filters for products that have integrations with JMP Statistical Software. View the products that work with JMP Statistical Software in the table below.

What is Finance Software for JMP Statistical Software?

Financial software is a broad category of financial software. Finance software provides all the necessary tools to record, store, manage, analyze and process financial information, accounting, trading, records, bills, transactions, and more. Compare and read user reviews of the best Finance software for JMP Statistical Software currently available using the table below. This list is updated regularly.

  • 1
    Microsoft Excel
    Microsoft Excel is the industry-standard spreadsheet application that helps users organize, analyze, and visualize data with precision and power. Whether you’re managing budgets, tracking performance, or analyzing complex datasets, Excel simplifies every task with intuitive tools and intelligent automation. With Copilot, you can now ask Excel to write formulas, summarize data, or create visualizations—all powered by AI. From basic spreadsheets to advanced financial modeling, Excel adapts to your skill level and workflow. Its cloud collaboration through Microsoft 365 lets multiple users edit, share, and comment in real time from any device. With flexible templates, built-in charts, and cross-platform integration, Excel turns numbers into insights you can act on.
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    Starting Price: $8.25 per user per month
  • 2
    MATLAB

    MATLAB

    The MathWorks

    MATLAB® combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, rigorously tested, and fully documented. MATLAB apps let you see how different algorithms work with your data. Iterate until you’ve got the results you want, then automatically generate a MATLAB program to reproduce or automate your work. Scale your analyses to run on clusters, GPUs, and clouds with only minor code changes. There’s no need to rewrite your code or learn big data programming and out-of-memory techniques. Automatically convert MATLAB algorithms to C/C++, HDL, and CUDA code to run on your embedded processor or FPGA/ASIC. MATLAB works with Simulink to support Model-Based Design.
  • 3
    SAS Viya
    SAS Viya is a cloud-native data and AI platform that unifies data management, analytics, AI modeling, and governance within a single environment. The platform helps organizations build, validate, deploy, and govern AI models with transparency, fairness, and auditability built into the entire lifecycle. SAS Viya provides seamless access to data across multiple sources and platforms while maintaining governance, lineage tracking, and compliance controls. Businesses can use the platform to accelerate AI model training, improve workflow productivity, and operationalize data-driven decisions at scale. SAS Viya also supports AI agents through the SAS Viya MCP Server, enabling secure integration of AI-powered tools and decision-making processes. The platform is designed to support cloud, hybrid, and on-premises deployments for greater flexibility across enterprise environments.
  • 4
    Ledge

    Ledge

    Ledge

    Ledge is an AI-powered finance operations platform designed to help finance teams automate and accelerate their month-end close and high-volume operational workflows. Rather than starting with spreadsheets each cycle, Ledge’s intelligent agents automatically populate reconciliations, journal entries, cash-application matches, and working papers using connected bank, ERP, billing, and payment-processor data, so when your team opens the checklist, much of the heavy lifting is already done. It supports continuous reconciliation of accounts, daily cash-application, and a close-checklist that behaves like an intelligent workbench; tasks come pre-completed, exceptions get flagged, approvals are tracked and audit trails link every item back to source transactions. Finance teams can therefore move from a reactive, end-of-month crunch to a forwmplex jouard-looking, context-rich review process where controls are strong, auditors are satisfied, and decisions are timely.
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