Case Study

Early Warning System implementation


Our Client is one of the largest private banks in Eastern Europe with 33 years of history, providing financial services to 22 million active corporate customers and over 1 million active retail clients as of 2021.

The bank is constantly improving its processes on the way to technological excellence. An enterprise-scale project was aimed at creation of a fully automated EWS for monitoring that leads to automatic revision of restrictions, recalculations of banks’ reserves and interest rates in relation to its SME clients.


EWS gathers data from multiple internal and external sources to identify risks at an early stage by a variety of tools including those based on statistical analysis and ML algorithms. The results of monitoring should be available for users working in numerous internal banking systems, each with its proprietary UI requirements, business models, and roles models.


  • The system reads messages about changes by clients (financial & other parameters), aggregates them, and collects all the necessary information.

  • The system redirects the summary information to the module for calculating limits for the corresponding reaction.

  • The reaction in this case may be to disable the restriction, after which transactions with these clients will go through standard control.


Automated Group of Clients identification

The Early Warning system requests a financial assessment module to get actual financial data. It calculates financial position of a Borrow and returns the value back to the system.

The system allows automatic identification of a Group of Clients based on interconnections with other companies in a State Register through ownership relations and bank’s internal consolidation reports.

Automated Group of Clients financial assessment

The Early Warning system component provides assessment on key financial indicators taking into account a weight of a certain indicator in a financial assessment mod.

It results in automatic amendments of a loans’ quality based on loans’ quality categories. Following a designed process, in some cases additional manual screenings (standard control) may apply with tasks appointed in a relevant BPM system.


EWS implementation Project result.

  • In-time amendments of reserves and interest’s rates
  • Automatic precise definition of quality categories based on financial assessment
  • Reduction of overdue loans by 7%
  • Increased share of Pre-approved loans in SME loans portfolio
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