The Business Context

The European national postal services company is one of the largest cash operators in its country with 7 collection centres across the territory. The company provides services to both private and business customers, covering letter & parcel delivery, newspaper distribution and bill payment services. The main cash activities performed by the company involves the delivery of pensions & state allowances to natural persons, servicing a bank’s ATMs and collecting utility bills and other payments.

The postal services company deals with a large amount of cash and must perform daily planning and tracking for millions of euros. Based on the security clearance of each post office, the volume of cash that can be kept overnight varies deeply. The current situation forced several post offices to return a part of the cash to the collection centres even if it was predicted to be necessary for the next day’s operations, which leads at times to the inability to deliver scheduled payments.

To optimise the cash flow management through an efficient planning process, the company called for a system that could offer predictive analytics to gain accurate results of the potential cash demand, considering different volume, currencies and seasonal fluctuations.

The Solution

The postal services company’s planning and tracking process occurs in 2 steps. The first one implies a daily exchange of the existing currencies between the collection centres and the National Bank to ensure that the postal services company has the right amount of currencies to meet upcoming requests. The second step involves provisioning the postal offices and the postmen with a sufficient amount of cash.

Following the existing business processes, the application developed by iQuest used a forecasting model that would enable an intelligent and secure cash flow management for all national post offices. Using a custom-made algorithm, the predictive analysis is performed in 2 steps:

  • The 2 days prior to the collection day prediction

The system predicts the expected payments and income for each collection centre based on the total number of predictions made for all post offices allocated to a certain collection centre. Also, based on this forecast, the company is able to perform the exchanges of the daily currencies with the National Bank.

  • The 1 day prior to the actual payment day prediction

The application forecasts the expected payments and income for each post office and postman with 1 day in advance, in order to detect fraud, such as late accounting procedures or extra unjustified requests. The new system has the ability to notify the controlling department of potential fraud occurrences.

Using a similar predictive analysis method and based on the expected incomings and outgoings, our solution is also able to forecast the balance on the current account and to allow the creation of a new deposit.

The predictive forecasting models were created based on history and current data, such as:

  • Planned payments, available in advance: pensions, child care allowances, etc.
  • Money transfer orders, available just before transaction
  • Cash collection and returns
  • Utility bill payments
  • Other postal service
  • Expected need of cash by currency

The algorithm behind the solution aims to anticipate a request and to ensure the availability of the necessary cash, focusing also on minimising the cash stocks.

The postal offices are automatically clustered in groups based on last’s year cash volume and for each group a predictive analysis model is being employed.

The Business Impact

With the new solution in place, the postal services company benefits from an efficient cash flow management system and is able to be more accurate in their daily activity.

Our client has gained the flexibility to adapt easily to both, customer needs and external factors, by making daily insight-based decisions.

Key benefits:

  • Increased Productivity & Efficiency
    The system offers accurate and secure predictive analysis of the cash flow by examining multiple aspects, including external factors, such as seasonal fluctuations.
  • Preventive Fraud Detection Service
    The solution improved the internal monitoring system by enhancing operations’ security.
  • Minimised Currency Fluctuations & Cash Stock
    The accurate predictions of the new system optimised the currency exchange with the National Bank and balanced the cash availability.
  • High Customer Satisfaction
    The software application enables efficient cash flow management that improved the company’s overall performance.