Cash Optimization – as a real cost-saver – is about forecasting cash movements (deposits and payouts) to and from branches / atms, creating an automatic, cost-optimized transportation plan that keeps cost the lowest possible while keeping liquidity and other kpi’s. The monitoring function calculates the probability of going out of cash until the next planned transport every 15 minutes and proposes an emergency transport if needed. Cash optimization provides a forecast for all cashpoints based on historical data and creates optimized transport plan to reduce cash- related costs by 20-30% while keeping liquidity.
ApPello generally undertakes to run a simulated Cash Optimization scenario for interested banks. This means that after providing 1-1.5-year historical transactional data for a limited number of cash points, ApPello will use the Cash Optimization engine to simulate the last month of the data available with actual transactions and simulated optimized transportations and thus cash stocks. Comparing the actual costs incurred vs. simulated a good prediction of the potential savings can be provided, which is in most cases 20-40% of the total cash management costs of the bank and thus ROI is generally within 1 year. Simulations within the System are also made available for the banks to test effects of changes on cash costs.
The Cash Management module centralizes all information about cash requests (including announced client and branch requests and the forecast if the module is available), handles the creation and approval of cash transports by denominations as well as supports the processes of the transportation, including cash counting, bagging and handover procedures.
Cash Forecasting is the part of Cash Optimization that prepares a traffic forecast for each cash point (branch, ATM, …) per day for both cash-in and cash-out directions for a period of a couple of weeks, including the intra-day distribution of forecasted transactions. This is done by hightech mathematical algorithms, that use historical transactional data and recognize patterns within the data set. A selection of algorithms is available and each of them can be fine-tuned by each cash point to give optimal accuracy.
Based on the forecast and the actual stocks, the Transport Optimization function prepares a transport plan. This algorithm considers all cost factors of cash management, i.e. the lost interest on the cash stock sitting in the branch or ATM, transportation cost, cash handling and insurance costs to find the transport option (when and how much) with the lowest cost while keeping liquidity of the cash point and respecting constraints of transport order deadlines, transport capacities as well as KPI’s like for example ATM cashback level.
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