AI impact to Detect Fraud & Substance Abuse

Authors

  • Praveen Kumar Rawat, Amit Nandal

Keywords:

Artificial Intelligence, Fraud Detection, Substance Abuse, Predictive Analytics, Behavioural Monitoring

Abstract

Conventional techniques of inquiry and diagnosis have been transformed by the use of AI in fraud detection and drug usage monitoring. Artificial intelligence-powered systems utilise machine learning, natural language processing, and predictive analytics to identify patterns, anomalies, and hidden hints that could indicate drug addiction or fraud. By rapidly analysing large datasets, identifying anomalies in transactions, and detecting suspicious behaviour in real-time, artificial intelligence systems have the potential to significantly reduce human error and response time in the area of fraud detection. Because stopping fraudulent transactions may result in significant losses for clients and a general reduction in trust in these sectors, financial institutions, insurance firms, and online merchants significantly depend on these abilities. At the same time, artificial intelligence is transforming drug usage detection via advanced monitoring methods, digital phenotyping, and speech and facial expression recognition. Artificial intelligence (AI) systems that scan speech patterns, facial microexpressions, mobile usage behaviour, and biometric data for signs of psychological distress or relapse may be able to identify patients with a history of drug dependence early on. AI chatbots and virtual counsellors, which provide scalable, private, and rapid intervention channels, enable better access to mental health care while reducing stigma. AI's predictive capabilities may also be used by legislators and medical experts to anticipate drug abuse patterns, improve rehabilitation methods, and allocate resources efficiently. Doctors may more accurately assess patients' risk levels and develop individualised treatment plans by integrating AI models with EHRs. Despite AI's enormous potential, ethical issues including data privacy, algorithmic bias, and informed consent are brought up by its use in these delicate industries, necessitating strict regulatory frameworks and open algorithmic management. When it comes to increasing the scalability, accuracy, and speed of drug and fraud detection, artificial intelligence is ultimately revolutionary. When used responsibly and with the appropriate safeguards, AI technology has the potential to significantly improve public health outcomes, loss prevention, and early intervention.

DOI: https://doi.org/10.17762/ijisae.v11i11s.7670

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Published

15.12.2023

How to Cite

Praveen Kumar Rawat. (2023). AI impact to Detect Fraud & Substance Abuse. International Journal of Intelligent Systems and Applications in Engineering, 11(11s), 837 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7670

Issue

Vol. 11 No. 11s (2023)

Section

Research Article

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