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Key applications of artificial intelligence (AI) in banking and finance

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Artificial intelligence (AI) technology has become a critical disruptor in almost every industry and banking is no exception. The introduction of AI in banking apps and services has made the sector more customer-centric and technologically relevant. AI-based systems can help banks reduce costs by increasing productivity and making decisions based on information unfathomable to a human agent. Also, intelligent algorithms are able to spot anomalies and fraudulent information in a matter of seconds. A report by Business Insider suggests that nearly 80% of banks are aware of the potential benefits that AI presents to their sector. Another report suggests that by 2023, banks are projected to save $447 billion by using AI apps.


Artificial Intelligence in the Finance and Banking Sector?

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AI is fantabulous and in demand in the banking and finance sector. The technological furtherance in AI – machine learning, computer vision and natural language processing has downright remodelled the business world. The expert opinion states that the growth of the AI market would reach $190 billion by the year 2025! The application of conversational assistants or chatbots is one of the substantial benefits of AI in the banking and finance sector. As opposed to an employee, a chatbot is at one's disposal 24 hours a day, and clients are more complacent using this software programme to answer inquiries and complete many typical banking procedures that traditionally called for face-to-face interaction.


Artificial intelligence in Banking advantages, disadvantages & Mobile banking services Science online

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AI can be used in banks to decrease financial risk, It can improve loan underwriting through machine learning, improve financial crime risk with advanced fraud detection, It can improve compliance and controls, and reduce operational risk through improved accuracy in transcription & production of documents, banks can use machine learning and big data to prevent criminal activities and monitor potential threats to customers in commerce. Artificial intelligence (AI) includes machine learning and natural language, it can be used in the banking industry, Machine learning is a method of data analysis which automates analytical model building, Machine learning occurs when computers change their parameters/algorithms on exposure to new data without humans having to reprogram them. Natural language processing (NLP) refers to the ability of technology to use human communication, naturally spoken or written, as an input that prompts computer activity, natural language generation (NLG) refers to the ability for technology to produce human quality prose, It sorts through large amounts of available data to produce a human-sounding response, NLG can take the form of speech, or of a multipage report summarizing financial results. AI can help the bank understand the expenditure pattern of the customer, The bank can come up with a customized investment plan & assist the customers for budgeting, banks can send the notification about the advice for keeping a check on the expenses and investments based on the data, The transactional & other data sources can be tracked to help understand the customer's behavior and preferences to improve their experience. Artificial intelligent can sift through massive amounts of data and identify patterns that might elude human observers, One area where this capacity is particularly relevant is in fraud prevention, Artificial intelligence and machine learning solutions are deployed by many financial service providers to detect fraud in real time.


Global Big Data Conference

#artificialintelligence

Artificial intelligence (AI) technology has become a critical disruptor in almost every industry and banking is no exception. The introduction of AI in banking apps and services has made the sector more customer-centric and technologically relevant. AI-based systems can help banks reduce costs by increasing productivity and making decisions based on information unfathomable to a human agent. Also, intelligent algorithms are able to spot anomalies and fraudulent information in a matter of seconds. A report by Business Insider suggests that nearly 80% of banks are aware of the potential benefits that AI presents to their sector.


The 18 Top Use Cases of Artificial Intelligence in Banks - Fintech News

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This article in CustomerThink identifies many different solutions where Artificial Intelligence can enhance banking, but makes it appear these solutions are already widely deployed. While each solution is currently in-market by at least one large bank this is a far cry from broadly deployed. Mercator surveyed large banks and found 93 different Artificial Intelligence solutions deployed in 13 different departments. "Machines are getting smarter globally. Thanks to thriving Artificial Intelligence (AI) concept, companies can make their devices more powerful and'intelligent' to serve their customers in a better way. Both B2B and B2C businesses have started adopting this revolutionary technology as per their scale and size. However, the penetration of AI in the banking sector is somewhat limited to date. The distinct datasets and the risk of confidential data are primarily responsible for the sluggishness of AI integration in the banking system.