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Artificial Intelligence (AI) is transforming companies by radically streamlining processes, crunching massive amounts of data, and creating cutting-edge projections. In finance, the rise of AI and machine learning is fueling financial technology (fintech). As AI revolutionizes finance, estimations indicate banks’ aggregate potential cost savings will reach $447 billion by 2023.1 With various applications like chatbots and fraud detection, these technologies will be crucial to staying competitive in the evolving financial market.1

Defining AI

Computer and cognitive scientist John McCarthy coined the term “artificial intelligence” in 1956 when he and his students created programs that let computers learn checkers strategies.2 Modern AI encompasses a wide range of processes like task automation and robotics. The popularity of AI has skyrocketed in the digital era due to massive data generation. With more online transactions, businesses have access to overwhelming information and need AI to produce useful insights.

AI falls into two main categories, weak and strong AI.3 Weak AI handles specific tasks and is bound by a distinct ruleset. One example is Apple’s Siri, which relies on an internet database to produce the illusion of intelligent speech.3 On the other hand, strong AI is not bound by defined rules. Also called artificial general intelligence (AGI) or general AI, strong AI is theoretical as it necessitates human-level intelligence.4

Finance organizations use weak AI for applications like cognitive computing, personal assistants, and robotic advisors. Currently, these technologies primarily augment rather than replace human labor. Nevertheless, as AI advances, companies are applying the technology to broader tasks.

The Current State of AI in Finance

AI is already critical to the finance industry, particularly with larger financial institutions. A 2020 report indicates that 75 percent of banks with over $100 billion in assets currently use AI versus 46 percent of those with less than $100 billion in assets.5 For smaller banks to compete with the industry’s juggernauts, adopting effective AI solutions will be critical over the next few years. Cost-savings opportunities are immense, with an estimated $199 billion for conversational banking and $217 billion for anti-fraud measures.5 Embracing AI will generate revenue across the sector by saving time, money, and human labor. A McKinsey study indicates that AI technologies could generate over $250 billion across the banking industry.5

The financial sectors rapid adoption of AI is inextricable from the rise of financial technology (fintech), which encompasses any software-based financial services, such as online banking, mobile payments, and cryptocurrency.7 The digitization of the financial sector and fintech have created massive volumes of data that companies use AI to analyze. Currently, large financial companies rely on AI-based technology for a competitive edge, like robotic advisors and risk management programs.

How Companies are Using AI

AI is streamlining various aspects of the financial sector, and personal finance has seen significant changes. Around-the-clock chatbots provide consumers financial guidance powered by natural language processing algorithms.

Consumer finance also uses AI to prevent fraud and cyberattacks. With online payment fraud predicted to reach $48 billion annually in 2023, consumers want secure financial services.1 By analyzing irregularities in huge datasets, AI can detect fraud where human oversight fails. One large bank using AI for consumer finance security is JPMorgan Chase, which uses a proprietary algorithm to identify fraud.

Corporate finance companies use AI technology like machine learning for loan underwriting, reducing risk, and preventing financial crime. U.S. Bank is a major player in corporate finance that uses AI to analyze customer data with deep learning (an advanced machine learning subset) and detect money laundering or other illegal activities.1

Staying Ahead of the Financial Curve

AI has become a revolutionary force in finance. These technologies improve transactional and account security, provide consumers with 24/7 digital support, and reduce costs through task automation. However, in 2018 only a third of financial companies had implemented AI technology, and many risk falling behind their competitors.7 For finance companies looking to stay ahead of the competition, maximize efficiency, and offer customers front-line solutions, embracing AI is a necessity.

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  2. McCarthy, John (1988). “Review of The Question of Artificial Intelligence”. Annals of the History of Computing. 10 (3): 224–229., collected in McCarthy, John (1996) Check this link/reference