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Machine Learning Uses in Finance Departments

Inaccurate cash flow projections can cost businesses up to 3% in profits and erode trust in previous decisions. Machine learning incorporates all financial data to deliver accurate projections. Models can explore relationships between thousands of different data points and identify the points with the strongest correlation. Multiple models can be created to play out different scenarios. Once created, models can be adjusted to accommodate new information, providing for proactive, rather than reactionary, decisions.

Cloud Analytics Platforms for Business Decision-Making

  • Machine learning models can help create multiple reliable forecasts and identify potential risks and benefits that are sometimes missed by traditional analysis.
  • Machine learning can shrink the time it takes to produce what-if analysis while increasing accuracy.
  • Models can identify trends in the data and work with what-if scenarios to help finance professionals provide internal stakeholders with a range of accurate forecasts based on different business drivers.
  • Fraud not only costs business money in terms of lost revenue, but it also costs in fines and fees for non-compliance.
  • ML models can analyze large volumes of data to identify and highlight patterns of suspicious activity that may indicate fraud.
  • Alteryx Designer automates every step of analytics, including data prep, blending, reporting, predictive analytics, and data science.
  • The most common analytics end users are data scientists, data architects, data engineers, technical or data executives or managers, and line-of-business executives and managers..
  • Alteryx Intelligence Suite allows users to create innovative machine learning models in minutes.

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