ThailandFinance and insurance2023 – ongoingBank of Ayudhya
Machine-learning optimization of ATM cash deliveries
Krungsri used machine learning to plan cash deliveries to more than 6,000 ATMs in Thailand
Problem
Bank of Ayudhya, operating as Krungsri, needed to keep cash available across a nationwide ATM network. Delivery planning depended on local cash demand and traffic conditions.
Approach
Krungsri used Amazon SageMaker to predict traffic and cash demand by location. The predictions supported route optimization for cash-delivery vehicles. AWS reported lower fuel costs and transportation time.
Results
Takeaway
The bank applied machine learning to a physical distribution task. AWS did not quantify the fuel or transportation savings.
Categories
- Size
- Large enterprise
- Industry
- Finance and insurance
- Business function
- Logistics and supply chain
- Innovation type
- Process innovation
- AI technology
- Predictive analytics and MLOptimization
- Adoption
- Off-the-shelf tool or platform
- Evidence
- Vendor case study
Sources
Source summaries
AWS described Krungsri's use of SageMaker to predict traffic and local cash demand for deliveries to more than 6,000 ATMs. It reported fuel and transportation-time savings without giving their size.
Full details are in the original sources.
