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How AI is changing Healthcare, Finance, Fraud Detection, and more...


Artificial intelligence has been indicated as a revolutionary technology. AI and its related technologies, such as machine learning and deep learning, have heralded a new era of intelligent automation and human-level recognition.

It has been the most commonly used buzzword in current systems, promoted as a revolutionary technique of labor provision. For businesses all throughout the world, these technologies have permitted a new level of low-cost, precise labor. Furthermore, using analytics, they are able to create new value prospects for businesses. The impact of AI on the business sector is undeniable. AI offers a wide range of applications in organizations, from predictive analytics for corporate intelligence to deep learning applications.

The impact of AI, on the other hand, maybe seen in a variety of businesses. In this article, we will explore the use cases and ethical consequences of using AI in finance, healthcare, National security, and Fraud Detection.



Healthcare

AI can have a significant impact on healthcare in the future, assisting radiologists in detecting cancers in x-rays, researchers in detecting disease-related genetic sequences, and discovering chemicals that could lead to more effective treatments. The recent accomplishment by Google's AlphaFold 2 machine-learning algorithm is projected to cut months from the time it takes to develop new drugs to hours.

Artificial intelligence technology has been tested in hospitals around the world. This includes oncologists using the IBM Watson Clinical Decision Support Tool being trained at Memorial Sloan Kettering Cancer Center, and the UK National Health Service using Google DeepMind to identify abnormalities in the eye and streamline the screening process for head and neck cancer patients.

What deep learning can do in these situations is to train a computer on a data set to learn what normal and irregular lymph nodes are. By doing this through imaging exercises and honing their labeling accuracy, radiologists can apply this knowledge to real patients and determine the risk of lymph node cancer.




Finance

"From now until 2030, Saudi Arabia will invest $20 billion," stated Abdullah al-Ghamdi, the head of the Data and Artificial Intelligence Authority. "Decisions concerning loans are now being made by software that can take into account a range of finely parsed data about a borrower, rather than just a credit score and a background check," according to industry observers. There are also "Robo-counselors," which "build tailored investment portfolios without the need for stockbrokers or financial advisers." These advancements are intended to remove emotion from investing and allow investors to make decisions based on analytical factors in a matter of minutes.

The stock exchanges are a good example of this, where high-frequency trading by robots has replaced a lot of human decision-making. People place buy and sell orders, and computers match them without human intervention in the blink of an eye. On a very small scale, machines can detect trading inefficiencies or market differentials and execute profitable trades based on investor instructions. These instruments, which are powered by powerful computing in some places, offer significantly greater capacity for storing information because they focus on "quantum bits," which may store many values in each spot rather than a zero or a one.



Fraud Detection

What people used to buy in stores is now being bought online, including furniture, groceries, and clothing. Detecting fraud can be challenging in a dynamic global corporate environment with massive amounts of traffic and data to monitor.

Fraud detection is an excellent application for machine learning, with a proven track record in areas such as banking and insurance. Shocking, yet true! According to the latest McAfee report, cybercrime is currently costing the global economy $600 billion (0.8% of global GDP). Fraud is an increasingly serious threat to banks and their consumers, costing them billions of dollars each year. Some banks offer refunds to consumers, while others do not refund because they claim the customer's responsibility to open the transaction. Banks are losing money and consumer trust anyway.

Frauds such as false invoices, CEO frauds, and Business Email Compromise (BEC) are done through social engineering rather than hacker attacks. By using AI to detect fraud, companies have been able to improve internal security and simplify their operations. Therefore, artificial intelligence has evolved into an important tool for preventing financial crimes due to its increased efficiency. With AI, you can analyze a large number of transactions to uncover fraud trends and use them to detect fraud in real-time.

When fraud is suspected, AI models can be used to completely deny transactions or flag them for further investigation, as well as to assess the possibility of fraud, allowing investigators to focus efforts on promising cases. The AI ​​model can also provide the cause code for the reported transaction. These reason codes tell investigators where to look for defects and help speed up the investigation process.


CONCLUSION

In summary, the world is at the limit of revolutionizing many sectors through artificial intelligence and data analytics. Finance, national security, healthcare, criminal justice, transportation, and smart cities already have significant developments in transforming decision-making, business models, risk mitigation, and system performance. These developments bring significant economic and social benefits.

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