Blockchain and AI-Empowered Healthcare Insurance Fraud Detection: An Analysis, Architecture, and Future Prospects

Aim:

           The main aim of this project is to detect Healthcare Insurance Fraud and eliminate using blockchain and machine learning.

Abstract:

          Health insurance has become an essential part of people’s lives as the number of health issues increases plan can be a solution to deal with the rising medical costs. It provides financial security by covering the costs related to treatment, hospitalization, free health check-up, and pre and post hospitalization expenses. Health insurance helps people cover healthcare services expenses in case of a medical emergency    and provides financial backup against indebtedness risk. Health insurance and its several benefits can face many security, privacy, and fraud issues. And various security issues in health insurance.  Insurance Covered with   protection, Risk Sharing, Value of Risk, Capital Generation, Economic Growth, Saving Habits.This paper presents a taxonomy of We proposed a blockchain and AI-based secure and intelligent system to detect health insurance fraud. Then, a case study related to health insurance fraud is presented. Finally, the open issues and research challenges in implementing the blockchain and an AI-empowered health insurance fraud detection system is presented.

Existing System:

             In existing surveys, security issues and HI fraud detection were not discussed. So, there is a need for a comprehensive survey that inspects the secure AI and blockchain empowered HI fraud detection system centralized systems provide security to a certain extent, but they could crash due to malicious attacks or faults. HI frauds as they aren’t limited to fraud patterns with predefined class labels. Medical insurance fraud is a serious subject in each country and the forged behavior patterns vary according to the situation. So, the chances of fraud occur from the insurance provider, insurance subscriber, and healthcare service provider due to lesser transparency and privacy. It is less cost-effective due to the involvement of the intermediary broker or agent costs.

Problem Definition:

            Various types of HI frauds occur in each country and multiple parties are involved with this fraud. There are mainly three parties engaged in this fraud. First, health- care service providers such as doctors, hospitals, ambulance firms, and laboratories. It Possible to create a duplicate doctor prescription and duplicate hospital bills. The third is HI provider’s fraud which includes private insurance firm, and the government sector. Health claim records are easily alterable and accessible.

Proposed System:

            A privacy, and fraud detection in HI is key criteria. Without the security and privacy of the HIC system, patient’s sensitive Personally Identifiable Information (PII) can be compromised, which can in the insurance firm’s reputation. Fraud in healthcare insurance causes loss for individuals, private firms, and governments. So, the devise of secure fraud detection methods for HIC has become necessary. We have discussed major security issues and their countermeasures in HIC and proposed a blockchain and AI-empowered architecture for HIC fraud detection. A health record storage and management method based on the consortium blockchain for data security, reliability, immutability, traceability, and nonrepudiation. Every insurance plan, including HI, is vulnerable to fraud. Every year, HI protect and   provider firms lose revenue due to fraudulent claims. Cybercrime affects the HIC industry from both internal and external sources, including the third parties. HIC data is stored in various systems, and it is interlinked between systems which causes authentication and authorization problems. Insurance firms lose lots of revenue and reputation due to the compromised security of the HI system. Firms hike premiums to maintain profit, which impacts legitimate insurers.

Advantage:

• Health Insurance Fraud can be attempted by fraud identification method at their occurrence.
• We present a background and various security and privacy issues of HI fraud detection and present a taxonomy on possible security attacks on the HI systems along with their countermeasure tools.
• We propose a blockchain and AI-based system to fight against various security issues in HIC fraud detection that increases the transparency and trust among the HI provider and subscriber.
• We also present a case study on HIC fraud detection using healthcare wearable devices.Identifying the frequent fraud patterns from the HI database using rule mining which analyzed HIC fraudulent patterns according to period and disease.