WHY MACHINE LEARNING IS THE BEST WAY TO REDUCE FRAUD_

Views:
 
     
 

Presentation Description

Machine learning is a field of science that offers machines an ability to understand data and carry out processes just as a human would do. Sometimes, even more efficiently.

Comments

Presentation Transcript

slide 1:

Data Science Session 1 1

slide 2:

Copyright © Global Tech Council www.globaltechcouncil.org Why Machine Learning Is The Best Way To Reduce Fraud Machine learning is a field of science that offers machines an ability to understand data and carry out processes just as a human would do. Sometimes even more efficiently. The ML technology uses complex algorithms to analyze large data sets and find data patterns that help in business decisions. This is why machine learning can detect fraud in the system easily. It is in fact used for various other purposes such as spam detection product recommendation image recognition predictive analysis etc. 2

slide 3:

Copyright © Global Tech Council www.globaltechcouncil.org Gartner predicted that by the year 2022 the machines would be analyzing 50 of the data which is only 10 more from the present scenario. Since machines are far better at detecting patterns ML can analyze huge sets of data in one chance and find fraud-related behavior through cognitive technology. Let’s dive in and analyze in detail how machine learning helps in fraud detection: 3

slide 4:

Copyright © Global Tech Council www.globaltechcouncil.org Machine Learning For Fraud Detection Implementation of machine learning can streamline many functions and enhance the real-time economy. Needless to say this technology also empowers organizations to detect fraud occurrence even before it impacts the users. Here are the three steps involved in fraud detection through machine learning: 4

slide 5:

Copyright © Global Tech Council www.globaltechcouncil.org Data Extraction After the extraction of data the ML algorithm is trained with a data set. This training is tweaked in the next step with some modifications in the testing set. Then the results of all the sets are compared through cross-validation of sets. The models that are high performing are extracted and various data splits are tested to ensure that the algorithm shows consistency. 5

slide 6:

Copyright © Global Tech Council www.globaltechcouncil.org Training Sets The main use of ML in detecting fraud is a prediction which means that the algorithm predicts whether a transaction is authentic or not. For instance the algorithm will quickly check the usage pattern of a credit card along with its origin country. This will help eliminate the chances of fraud. 6

slide 7:

Copyright © Global Tech Council www.globaltechcouncil.org Model Building At the time of building models it is determined how a set of input and output data can be used to predict future occurrences of fraud. Prediction can be achieved in the following ways: · Logistic regression · Neural networks · Decision tree · Random forest 7

slide 8:

Copyright © Global Tech Council www.globaltechcouncil.org How Machine Learning Helps In Reducing Fraud Take Huawei Technologies for example. They use the translytical database to ensure real-time detection of fraud that may happen through mobile payments and credit cards. Every time a user scans a phone swipes a card or follows any other process for a financial transaction the authorization process is carried out. This authorization process involves making a decline or authorized decision. This decision is made with ML algorithms where previous data is used to evaluate fraudulent behavior. 8

slide 9:

Copyright © Global Tech Council www.globaltechcouncil.org The whole training is carried out in a big data environment where the translytical database exports information to the system. The whole model is then loaded numerous times in one day as user-defined functions or stored procedures. Note: It is necessary to ensure ongoing training in your ML system because fraudulent methods change. Hence it is essential to keep training the algorithm so that efficient quality situations can be made. 9

slide 10:

Copyright © Global Tech Council www.globaltechcouncil.org It is amazing how machine learning algorithms focus on prevention of fraud rather than management. This means that ML is efficient in figuring out when any fraudulent activity is about to happen which helps in preventing the loss that can happen. 10

slide 11:

Copyright © Global Tech Council www.globaltechcouncil.org Conclusion Machine learning combined with other technologies has the power to save a lot of resources of a company. Apart from the cost saving fraud activities put the identity of users at risk. Losing this data threatens the personal security of customers which of course reduces brand loyalty. Hence machine learning can help prevent fraud and assist companies to offer better services to users. 11

slide 12:

Copyright © Global Tech Council www.globaltechcouncil.org Globaltech Council Certifications - You can check out our certifications and kick start your career. ● Certifies Artificial Intelligence Expert ● Certified Augmented Reality Developer ● Certified Chatbot Expert ● Certified Data Scientist Expert ● Certified Big Data Expert ● Certified Machine Learning Expert ● Certified Virtual Reality Developer Learn more about GlobalTech Council click here 12

slide 13:

THANK YOU Any questions You can mail us at helloglobaltechcouncil.org Copyright © Global Tech Council www.globaltechcouncil.org 13

authorStream Live Help