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  • Finance Fraud Detection and mitigation using machine learning

    “Machine Learning” essentially alludes to the aptness for machines to learn with the available data and pull off tasks that would primarily require human intelligence. If we look back to its evolution, the studies clearly signify a rapid swelling in the technology. It is stated that by the end of 2022, more than half of analytics and data services will be carried out by machines rather than human beings-- which is overall 10 percent more than today.

     

    Fraud Detection Using Machine Learning

     

    The advent of machine learning and its contrivance & implementation into consumer-facing applications harmonize seamlessly with today’s real-time economy. Nevertheless, it has been instrumental in unraveling some of the crucial business problems such as accurate medical diagnosis, strained product recommendation, and detecting email spams. The adoption of ML has indubitably been accentuated with increasing processing power, advancements in statistical modeling, and the availability of big data.

     

    Now when we talk about fraud management, it has truly been painful for every industry especially the commerce and banking sectors. With a plethora of payment channels available today such as smartphones, debit/credit cards, kiosks, etc, the number of transactions each day has increased significantly. At the same time, the cybercriminals and frauds have excelled in discovering loopholes. And as a result, it is getting really hard for the businesses to authenticate the respective transactions.

     

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    Data Scientists have, however, been victorious in finding the key to this issue with predictive analytics and machine learning. The automated fraud screening systems and channels fueled by the machine learning technology can help industries in detecting frauds and diminish such practices further.

     

    Real-Time Decision Making Needs Artificial Intelligence and Machine Learning

     

    Artificial Intelligence and Machine Learning are significantly revolutionizing brands, entire industries, and many more businesses in diverse sectors. They have the potential to enable real-time automated decision making and operationalize data analytics, which wasn’t previously available. Besides, they also have the capability to generate unexpected and new insights, drastically cut down labor costs, devise predictive models from raw data, and discover new patterns from the available information.

     

    Machine learning and real-time data analytics can have a tangible impact on the high stakes business events and it can be clearly witnessed in the fraud departments across several industries.

     

    Preventing And Mitigating Fraud And Identity Theft In Sales & Financial Services

     

    It is vital to emphasize on the existing methodologies prevailing in machine learning models. As cybercriminals tend to change their practices all the time, it is essential to constantly keep a check on machine learning fraud models and constantly update them to keep the false positive rate low and a high quality of decisions.

     

    A focus on prevention versus detection is also an essential distinction inherent to machine learning. The potential to terminate fraud before it actually takes place is not just a price saver for a lot of industries but also aids in maintaining a high brand value and minimizes the overall exposure to financial and sales risks.

     

    Is Machine Learning The Right Selection For Fraud Detection And Mitigation?

     

    This is probably the foremost and crucial question that pops in our head when dealing with fraud detection and machine learning. When reviewing the fraud related solutions, it is important to figure out what machine learning can do to your business and how it can essentially help. However, there are three primary features of machine learning that can largely contribute to the fraud detection. And they are:

     

    • Quick response and speed
    • Consistent, efficient, and superior decoding patterns and anomalies
    • Highly scalable

     

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    Overall, I believe that in order to beat the complex fraud science, machine learning models and solutions can be of great help. You can possibly prevent and mitigate fraud irrespective of your operating industry.

     

    And besides, if you are looking for a trusted resource for fraud detection and prevention services, we can assist you greatly. Let us know.


     

Tags: MachineLearning