How AI creative in cloud computing

Safalta Expert Published by: Vanshika Jakhar Updated Tue, 15 Nov 2022 10:36 PM IST

In the post-pandemic world, emerging technologies are disrupting all industries, and Artificial Intelligence has gained popularity. We are currently witnessing enormous advancements in digitalization, not to mention several ground-breaking applications for every facet of business management and to improve people's lives, thanks to AI and other emerging technologies. The pandemic forced many of banking and financial services companies to innovate by using AI in banking and finance to provide digital services, even though they had previously relied on face-to-face interactions. The widespread use of artificial intelligence in finance is evident in all areas, including the digitalization of back-end procedures like KYC or verifications or the opening of bank accounts. 
How about Artificial Intelligence, though?
Systems that mimic human intelligence to carry out tasks are referred to as AI. These systems or machines can also iteratively improve themselves based on the data they gather.

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Source: Safalta

Virtual assistants like Alexa and Siri are some of the common types of AI that we already unknowingly use. Artificial intelligence is upending several industries, including the financial services or fintech sector. The term "fintech," which is a portmanteau of the words "financial technology," describes the use of technology to deliver financial services. With the use of artificial intelligence in finance and other cutting-edge technologies like cloud computing, Big Data, and Blockchain, the fintech sector has advanced significantly. 
The banking and insurance sectors have undergone the most significant change, even though artificial intelligence adoption in the financial services industry has advanced significantly. A lot of unstructured data can be analyzed and insightful data can be extracted using AI. In the banking and finance industry, artificial intelligence has thus replaced fraud prevention and credit monitoring. There have been numerous front-end use cases for AI in finance. Businesses now offer digital wallets and touchless payment methods, and financial apps have greatly improved and now provide users with several advantages. These solutions aimed at consumers rely only on financial AI. In addition, chatbots and virtual assistants today are capable of much more than just answering straightforward queries. To process insurance claims for things like auto accidents, fintech, and insurance companies are also using AI. Artificial intelligence in finance is being used to spot frauds like photo-shopping images submitted with claim applications. There are examples of businesses using AI, Big Data, and behavioral economics to offer customers insurance policies and process numerous claims. Some of these businesses claim to be able to process claims in just a few seconds. With a combination of machine learning and advanced analytics, the use of AI in finance has increased significantly, but there is also a lot of innovation taking place with its many applications. As a result, AI in fintech contributes to better app usability as well as real-time data collection and analysis, all of which enhance the online experience. AI has a bright future in finance, with many advantages for businesses to increase efficiency and improve customer engagement.

Table of Content
Uses of Ai in Banking and Finance Risks of AI in Fintech  

Uses Of AI in Banking and Finance

Let's examine some additional uses of AI in banking and finance:

Protection from fraud and security

Data security has significantly improved as a result of AI in the financial sector. Several banks and fintech companies have started to rely on AI solutions to enhance data security while facilitating easy navigation for their customers. Additional access controls, cyber threat reduction, and other AI solutions have already been implemented.

Artificial intelligence in finance and accounting

AI has proven useful in several back-end financial processes, including accounting and finance. Finance professionals do not necessarily need to be tech-savvy to understand how to apply artificial intelligence to accounting and finance to automate and improve processes.

Contract management solutions

Contract management, which is essential to the fintech industry, has historically been a major pain point. It was time-consuming and difficult to keep track of. However, financial institutions have been able to streamline and automate the management of contracts since the adoption of AI, using a combination of Machine Learning, Natural Language Processing, and Optical Character Recognition.

Better customer service

Due to its being personalized to provide incredibly personalized solutions, AI is already being embraced by a wide range of industries. In the fintech industry, customer service is essential. Given that the younger generations are already well-versed in digital solutions, fintech is implementing AI to both attract younger customers by providing them with digital financial management solutions and to keep them by providing highly personalized services.

Future of payments

There have been significant improvements made in the way we pay, going from using cash to simply scanning a QR code to make a purchase. AI is likely to further disrupt society in the future. In 42 different locations across the United States and the United Kingdom, Amazon Go stores offer a preview of what can be anticipated. Computer vision, deep learning algorithms, sensor fusion, and other technologies are used to automate the stores so that customers can enter after scanning a QR code, pick whatever they need, and leave. The customer's linked account will be automatically debited for the cost of the items picked up.


Risks of AI in Fintech

There are risks associated with adopting AI in the financial services industry, despite its many advantages, including hyper-personalized offerings, automation of previously manual processes, real-time data analysis, data security, and other advantages.

Lack of judgment:

Unlike humans, AI cannot be expected to make decisions based on context and the surrounding environment, among other variables. Even though AI is superior in other ways, it cannot take the place of a human when making decisions or rendering judgments in urgent situations.

Poor data quality:

In addition to hurting how AI and ML systems make future inferences and decisions, poor data quality will restrict the learning capacity of these systems. Poor data, inaccurate data, etc., could pose a significant risk because they will result in a biased judgment and poor predictions.

Loss of jobs:

As AI automates manual processes, job losses are a possibility. The adoption of AI and the automation of processes, according to many experts, will help free up valuable human resources from menial jobs. However, the automation of processes is hailed as a benefit.

Despite these dangers, the potential damage that AI could do to the financial services industry has only just begun to be explored. Many of these risks can be reduced with strict laws and regulations governing the adoption and use of AI and other technologies. Data scientists, engineers, AI practitioners, etc. are in high demand in the fintech industry as a result of the introduction of digitalization and the adoption of AI and other forms of cutting-edge technology. There is, however, a sizable supply-demand gap. Because there are so many job opportunities in the fintech industry, businesses are looking for people with the right attitude and willingness to try new things. Fintech will be one of the most fascinating fields and careers over the following ten years.

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