- Artificial intelligence (AI) is revolutionizing how consumers and companies alike access and manager their finances.
- And with the aggregate potential cost savings for banks from AI applications estimated at $447 billion by 2023, banks are finding new ways to incorporate the tech into their services.
- Do you work in the Fintech industry? Get business insights on the latest tech innovations, market trends, and your competitors with data-driven research.
Artificial intelligence (AI) and machine learning in finance encompasses everything from chatbot assistants to fraud detection and task automation. Most banks (80%) are highly aware of the potential benefits presented by AI, according to Insider Intelligence's AI in Banking report.
The decision for financial institutions (FIs) to adopt AI will be accelerated by technological advancement, increased user acceptance, and shifting regulatory frameworks. Banks using AI can streamline tedious processes and vastly improve the customer experience by offering 24/7 access to their accounts and financial advice services.
Applications of AI in Financial Services
With key business benefits and pressure from tech savvy consumers top of mind, AI algorithms are being implemented by FIs across every financial service—here's how:
AI in Personal Finance
Consumers are hungry for financial independence, and providing the ability to manage one's financial health is the driving force behind adoption of AI in personal finance. Whether offering 24/7 financial guidance via chatbots powered by natural language processing or personalizing insights for wealth management solutions, AI is a necessity for any financial institution looking to be a top player in the industry.
An early example of AI in personal finance is Capital One's Eno. Eno launched in 2017 and was the first natural language SMS text-based assistant offered by a US bank. Eno generates insights and anticipates customer needs throughover 12 proactive capabilities, such as alerting customers about suspected fraud or price hikes in subscription services.
AI in Consumer Finance
One of the most significant business cases for AI in finance is its ability to prevent fraud and cyberattacks. Consumers look for banks and other financial services that provide secure accounts, especially with online payment fraud losses expected to jump to $48 billion per year by 2023, according to Insider Intelligence. AI has the ability to analyze and single-out irregularities in patterns that would otherwise go unnoticed by humans.
One bank taking advantage of AI in consumer finance is JPMorgan Chase. For Chase, consumer banking represents over 50% of its net income; as such, the bank has adopted key fraud detecting applications for its account holders. For example, it has implemented a proprietary algorithm to detect fraud patterns—each time a credit card transaction is processed, details of the transaction are sent to central computers in Chase's data centers, which then decide whether or not the transaction is fraudulent. Chase's high scores in both Security and Reliability—largely bolstered by its use of AI—earned it second place in Insider Intelligence's 2020 US Banking Digital Trust survey.
AI in Corporate Finance
AI is particularly helpful in corporate finance as it can better predict and assess loan risks. For companies looking to increase their value, AI technologies such as machine learning can help improve loan underwriting and reduce financial risk. AI can also lessen financial crime through advanced fraud detection and spot anomalous activity as company accountants, analysts, treasurers, and investors work toward long-term growth.
U.S. Bank is using AI in both its middle- and back-office applications. U.S. Bank unlocks and analyzes all relevant data on customers via deep learning to help identify bad actors. It's been using this technology for anti-money laundering and, according to an Insider Intelligence report, has doubled the output compared with the prior systems' traditional capabilities.
Benefits of AI in Finance
The benefits of implementing AI in finance—for task automation, fraud detection, and delivering personalized recommendations—are monumental. AI use cases in the front and middle office can transform the finance industry by:
- Enabling frictionless, 24/7 customer interactions
- Reducing the need for repetitive work
- Lowering false positives and human error
- Saving money
Automating middle-office tasks with AI has the potential to save North American banks $70 billion by 2025. Further, the aggregate potential cost savings for banks from AI applications is estimated at $447 billion by 2023, with the front and middle office accounting for $416 billion of that total.
Fintech: Future of AI in Financial Services
Between growing consumer demand for digital offerings, and the threat of tech-savvy startups, FIs are rapidly adopting digital services—by 2021, global banks' IT budgets will surge to $297 billion.
With millennials and Gen Zers quickly becoming banks' largest addressable consumer group in the US, FIs are being pushed to increase their IT and AI budgets to meet higher digital standards. These younger consumers prefer digital banking channels, with a massive 78% of millennials never going to a branch if they can help it.
And while the migration from traditional banking channels to online and mobile banking was underway pre-pandemic due to the growing opportunity among digitally native consumers, the coronavirus dramatically amplified the move as stay-at-home orders were implemented across the country and consumers sought more self-service options. Insider Intelligence estimates both online and mobile banking adoption among US consumers will rise by 2024, reaching 72.8% and 58.1%, respectively—making AI implementation critical for FIs looking to be successful and competitive in the evolving industry.
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Artificial Intelligence is vital in order for banks and other financial institutions to remain relevant and competitive in the financial industry. In the AI in Banking Report, Business Insider Intelligence identifies the most meaningful applications of AI in finance across banks' front and middle offices while discussing winning AI strategies used by FIs and providing recommendations for how banks can best approach a machine learning-enabled digital transformation.
>>Click here to purchase this report.
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