Optimizing Cash Replenishment in ATMs using AI/ML

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Liberin team was tasked with managing and optimizing the cash replenishment process in ATMs for banks and financial institutions. The challenge was to predict the cash flow requirements at the ATMs using AI/ML models while dealing with high volumes of data, multiple permutations of input data features, and ensuring speed, accuracy, and performance. 

The Objective: 

The primary objective was to develop a system that could efficiently forecast and manage the cash replenishment in ATMs. The solution was required to predict the cash flow requirements at the ATMs using AI/ML models. The challenge was to handle high volumes of data, and multiple permutations of input data features, and ensure speed, accuracy, and performance. The system was also expected to be bias-free providing explainability & validation. 

Solution Developed: 

The system is a comprehensive solution that takes into account a multitude of critical parameters and workflows for forecasting the cash replenishment amount, denominations, and cash-out scenarios in ATMs. These include monitoring ATM capacity, tracking ATM terminal balances and cash dispensed, determining denominations to be loaded with precise percentage distribution, creating an efficient cash load schedule, and addressing special days such as holidays and salary days. Additionally, the system is equipped to handle emergency replenishments, manage cash order revisions, and generate real-time alerts. It boasts automated cash order generation and provides valuable insights into forecasted cash amounts and upcoming events. This robust system streamlines cash management with precision and foresight. 

Quality Assurance: 

Liberin provided end-to-end development and testing of the replenishment forecasting system. The services included test data creation & curation, test data verification, model validation, model performance testing, functional testing, non-functional testing, test environment setup, and integration testing. The company used big data tools and technologies for data ingestion and feature engineering for data munging. Historical data of each ATM was used by multiple algorithms for training and building learning models. 

Key Benefits: 

  • Enhanced system: Liberin’s solution resulted in significant system improvements. 
  • Automation efficiency: The automation of data curation reduced testing time significantly. 
  • Improved performance: Performance optimizations led to faster system training. 
  • Streamlined testing: Efficient test data and environment management enabled faster test cycles for multiple teams. 
  • High accuracy: The system achieved a remarkable accuracy rate and offered fast forecasting capabilities. 
  • Exceeded expectations: Liberin’s solutions not only met the objectives but also surpassed expectations in terms of speed, accuracy, and performance. 

In summary, Liberin’s solutions effectively optimized the cash replenishment process in ATMs, utilizing AI/ML models to predict cash flow requirements. Their end-to-end testing services, including data curation and model validation, played a vital role in achieving remarkable results. The system demonstrated enhanced efficiency, streamlined testing, improved performance, high accuracy, and exceeded expectations in terms of speed, accuracy, and performance. Liberin’s expertise in leveraging AI/ML technologies was instrumental in delivering significant improvements to the cash replenishment process in ATMs. 

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Optimizing Cash Replenishment in ATMs using AI/ML