Moderate Automobile Accident Claim Process Automation Using Machine Learning

2021 ◽  
Author(s):  
Fazli Imaam ◽  
Achinthya Subasinghe ◽  
Hiruni Kasthuriarachchi ◽  
Senura Fernando ◽  
Prasanna Haddela ◽  
...  
Keyword(s):  
Machine Learning ◽  
Process Automation ◽  
Automobile Accident

scholarly journals THE FINANCIAL ASPECT OF IoT PROCESS AUTOMATION IN CREATING NEW VALUE FOR THE ECONOMY

2020 ◽  
Vol 18 (2) ◽  
Author(s):  
Nedeljko Šikanjić ◽  
Zoran Ž. Avramović ◽  
Esad Jakupović
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Scientific Paper ◽  
General Purpose ◽  
Advanced Technology ◽  
Process Automation ◽  
Advanced Technologies ◽  
Financial Benefits ◽  
Financial Aspect

In today’s world, devices with possibility to communicate, are emerging and growing daily. This advanced technology is bringing ideas of how to use these devices, in order to gain financial benefits for enterprises, business and economy in general. Purpose of research in this scientific paper is to discover, what are the trends in connecting these devices, called internet of things (IoT), what are financial aspects of implementing IoT solutions and how leaders in area of cloud computing and IoT, are implementing additional advanced technologies such as machine learning and artificial intelligence, to improve processes and gain increase in revenue, while bringing automation in place for the end users. Development of informational society is not only bringing innovation to everyday life, but is also providing effect on the economy. This effect reflects on various business platforms, companies and organizations while increasing the quality of the end product or service that is being provided.

Robot Process Automation (RPA) and Its Future

2022 ◽  
pp. 35-58
Author(s):  
Ozge Doguc
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computer Vision ◽  
Customer Satisfaction ◽  
Human Behavior ◽  
The Other ◽  
Human Intervention ◽  
Process Automation ◽  
Robotic Process Automation ◽  
Human Agent

Many software automation techniques have been developed in the last decade to cut down cost, improve customer satisfaction, and reduce errors. Robotic process automation (RPA) has become increasingly popular recently. RPA offers software robots (bots) that can mimic human behavior. Attended robots work in tandem with humans and can operate while the human agent is active on the computer. On the other hand, unattended robots operate behind locked screens and are designed to execute automations that don't require any human intervention. RPA robots are equipped with artificial intelligence engines such as computer vision and machine learning, and both robot types can learn automations by recording human actions.

Interpretable machine learning with reject option

2018 ◽  
Vol 66 (4) ◽  
pp. 283-290 ◽  
Author(s):  
Johannes Brinkrolf ◽  
Barbara Hammer
Keyword(s):  
Machine Learning ◽  
Vector Quantization ◽  
Random Forests ◽  
Black Box ◽  
Learning Models ◽  
Process Automation ◽  
Reject Option ◽  
Interpretable Machine Learning ◽  
Adversarial Examples ◽  
Machine Learning Models

Abstract Classification by means of machine learning models constitutes one relevant technology in process automation and predictive maintenance. However, common techniques such as deep networks or random forests suffer from their black box characteristics and possible adversarial examples. In this contribution, we give an overview about a popular alternative technology from machine learning, namely modern variants of learning vector quantization, which, due to their combined discriminative and generative nature, incorporate interpretability and the possibility of explicit reject options for irregular samples. We give an explicit bound on minimum changes required for a change of the classification in case of LVQ networks with reject option, and we demonstrate the efficiency of reject options in two examples.

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