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Predictive analytics systems

Predictive analytics systems use machine learning and statistical modeling algorithms to forecast key business indicators, identify trends and prevent potential risks. It is an intelligent decision support tool that provides proactive, data-driven bank management.

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Predictive analytics in the banking environment allows forecasting customer behavior, profit levels, transaction volumes, risk of delinquency, customer churn, channel load and other key indicators.  These systems generate forecast models based on historical and current data, allowing management to make decisions before deviations from target scenarios occur.

Functionality:

  • Building models based on ML/AI and regression analysis;
  • Forecasting income, expenses, balance sheet indicators, customer activity;
  • Models of customer churn, probability of default, demand for products;
  • What-if modeling and scenario forecasts;
  • Integration with DWH, BI, CRM, scoring platforms and marketing tools;
  • Configuring automatic alerts and triggers;
  • Visualization of forecasts in dashboards (Power BI, Tableau, etc.).

Who works with the system inside bank:

  • Financial Directorate / Planning and Economic Department
  • Data Science / Advanced Analytics
  • Customer Experience and Marketing Unit
  • Business Units
  • IT and Data Architects

System Owners:

  • Chief Data Officer (CDO) — model and data management
  • CFO — financial forecasting and budgeting
  • CIO/CTO — architecture, computing resources and security

What strategic objectives do the proposed solutions solve

Provides the ability to make decisions based on probable future scenarios, and not just post factum

Management becomes proactive rather than reactive.

Provides proactive identification of risks, deviations and hidden threats in financial and customer indicators

The bank is prepared for corrective measures in advance.

Improves planning accuracy, marketing profitability and the quality of business initiatives

Models support the launch of targeted campaigns and resource planning.

Make working with documents simpler and faster

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Who are the solutions suitable for?

Results after solution implementation

Improve strategic and operational planning through accurate forecasts of key performance indicators.

Improve campaign performance, business decisions and resource allocation using data.

Reducing management risks and errors thanks to models that warn of possible negative scenarios.

Processes are optimized, routine operations are automated, and employees have more time for truly valuable tasks.

Want the same? Find out all the details at

Consultations.

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