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How predictive maintenance can reduce machine breakdown and maintenance time
Banks are installing ATMs in large numbers to increase their service footprint to meet the rising demand for customer self-service and a more personalized experience. With this, we see ever-increasing numbers of machine outages proportional to ATMs’ installed base. Resolving these breakdowns and general ongoing maintenance presents a challenging task for banks.
In this use case, we establish how banks and other financial institutions can reduce maintenance time & associated costs by leveraging AI and data science.
Use case highlights:
- How AI and data science technology will help in the predictive and preventive maintenance of ATMs
- Detailed information on machine learning models and how they predict ATM downtime with 94% accuracy
- Preventative steps to reduce downtime and associated costs
Why Choose IntellectDataTM as your AI and data science partner?
Broad-spectrum of products and services employing leading-edge technology, providing a strategic and competitive advantage- Â
 Industry-leading expertise developing and implementing digital products and software services incorporating data science, artificial intelligence, image and video analytics, text analytics, predictive analytics, recommendation engines, and visualization- Â
Easily integrated with other mission-critical enterprise applications and platforms to solve any data-driven problem
Unmatched standards for quality, scalability, and performance create exceptional value, propelling organizations to the next level of insight and action
End-to-end services from consulting to full-cycle software development
Empower non-experts to use machine learning models and techniques without the need for prior expertise in the field
Complete adherence to data and security regulations such as HIPAA, Data protection 2018, etc.- Â