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AI is finding exciting new uses in the financial sector and setting the stage for a fintech and banking revolution.
Artificial intelligence (AI) is one of the fastest-growing technologies today. The global AI market was valued at $387.45 billion in 2022 and is projected to reach nearly $1.4 trillion by 2029, registering an impressive 20.1% CAGR over a seven-year period.
AI is deeply integrated into our everyday lives. In fact, smart technologies have become so ubiquitous that we barely even notice them. For instance, AI recommends content for you to watch on Netflix and YouTube, shows you products you might want to buy on Amazon, filters spam from your inbox, and talks to you via chatbots.
Every commercial industry is doing exciting things with AI, from autonomous cars in vehicle manufacturing and AI-powered clinical diagnosis in medicine to digital twins in virtual modeling.
The finance industry, too, is quickly embracing AI technologies and putting them to good use. Fintech companies and incumbent financial institutions increasingly augment their processes, services, and products with artificial intelligence. Let’s look at how AI is finding its way into finance and why:
AI’s penetration and value in the finance industry are unquestionable. A 2020 survey conducted by the World Economic Forum in collaboration with the Cambridge Centre for Alternative Finance paints a clear picture of AI adoption in finance and the motivation behind it. Here are the main highlights from the results after surveying 151 financial institutions across 33 countries:
In an increasingly data-centric industry, AI is a powerful tool for leveraging data technologies to improve financial products and services, streamline business operations, drive customer satisfaction, and optimize the bottom line. According to a recent survey by NVIDIA, incorporating AI in finance results in more accurate models, competitive advantages, better operational efficiency, improved customer experiences, and reduced costs.
Image source: NVIDIA
AI is a highly versatile technology with a wide range of capabilities and uses. Here are five game-changing AI applications in finance:
Banks are notoriously conservative, especially when it comes to tech adoptions. But the banking industry is quickly warming up to digitization due to mounting pressure from fintech competitors and the rapidly evolving financial landscape. And a key area of interest is AI-powered automation.
2023 saw the first-of-its-kind ranking of AI adoption and maturity in banks. JPMorgan Chase topped the list as the most AI-conscious big bank in North America and Europe. The bank spends a whopping $14 billion on tech annually, a large portion of which goes toward AI developments.
In a nutshell, AI banking automation systems eliminate or minimize human involvement in the bank’s business operations. This makes for faster, more accurate, and streamlined banking services.
Personalized banking means delivering relevant solutions tailored to specific customers. Banks have employed some personalization strategies over the years, many of which have yet to capture the customers’ expectations entirely.
AI brings a whole new dimension to personalized banking. With intelligent systems, banks can use sophisticated behavioral analytics, machine learning, and data science to customize their services and products at the individual level accurately. Personalized banking is mainly about improving the customer experience by giving clients exactly what they need, even before the need arises.
The traditional methods of gauging a borrower’s creditworthiness — checking their credit scores, financial status, and payment history — are often unreliable and discriminatory. These systems automatically disqualify all candidates lacking hard “human-intelligible” evidence of creditworthiness. Plus, completing all the paperwork needed to reach a credit decision can take days.
AI changes all that by enabling lenders to check a broad range of data sets in real-time to make heavily-informed credit decisions. Besides fast credit approval, intelligent borrower analytics recommend the optimal loaning limit, rates, and terms on a case-by-case basis.
AI credit decisioning widens a lender’s clientele without lowering the bar for credit approval or introducing unwanted credit risks.
Running a financial institution is risky business, which is partly why banks and credit unions are so critical of their customers and operations. According to the 12th annual EY/IIF global bank risk management survey, CROs in financial institutions are prioritizing risk management efforts around these ten factors:
AI helps mitigate most of these risks by pointing out possible threats before they become problematic. For instance, AI can quickly detect and stop financial fraud by analyzing a user’s activities (buying habits, transactions, and location) against a pre-established behavioral pattern. AI also plays a vital role in regulatory and compliance management, protecting financial institutions from various risks.
To recap, AI minimizes risks in financial management companies mainly through intelligent fraud detection, proactive cybersecurity, smart credit decisioning, and efficient compliance management. Plaid is an excellent example of a smart financial risk management system. It enables banks to connect safely with fintech services without worrying about fraud, data loss, non-compliance, or cyberattacks.
AI is a big part of digital trading, also known as quantitative or algorithmic trading. This method of trading assets, stocks, or capital utilizes powerful computers, advanced mathematical models, and pre-programmed instructions. Artificial intelligence augments the computing power with predictive analytics and neural networks, enabling the trading engine to recognize patterns and adjust its instruction set automatically based on prevailing market signals.
Intelligent trading systems can predict market performance faster and more accurately than their hard-coded counterparts. The high speed and precision minimize trading risks while maximizing returns.
According to one report, algorithmic trading accounts for around 60-73% of the overall US equity trading — and it is only growing stronger. The US algorithmic trading market was valued at $3.5 billion in 2021 and is expected to grow by a 12.2% CAGR between 2022 and 2030.
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AI is undoubtedly part and parcel of financial technologies. It is embedded in just about every banking app, fintech solution, financial CRM system, and funding platform. Moreover, AI’s impact on the financial industry will only grow as more banks embrace intelligent fintech systems and AI tech becomes more competent and reliable. The future is definitely bright for finance-based AI. And with that, we should expect even faster, safer, and more accessible, inclusive, and convenient financial or banking solutions.
Smart tech is just one facet of the inevitable revolution happening in finance. Another disruptive concept quickly catching on is embedded finance, where financial and non-financial firms provide funding solutions to their customers through co-brand partnerships with fintech companies. And the good news is you can be a part of this exciting, lucrative, and meaningful venture by teaming up with Loanspark.
Loanspark is a Business Lending as a Service (BLaaS) provider that equips B2B businesses with the expertise and technology to offer value-added funding products to their customers. We also partner with banks and credit unions to improve service delivery, lower credit risks, and expand clientele. Loanspark has something for everyone.
Contact us today to learn more about our future-proof fintech services.
