Technology has been transforming the financial sector for some time now, introducing everything from the era of online banking to the Fintech sector. But if there’s one innovation that’s genuinely paying dividends for this industry, it’s the rise of AI in finance.
Artificial intelligence has given financial companies new ways to mitigate risk, serve customers, forecast demand, and even make intelligent investment decisions. It’s little wonder the market for AI systems in this industry is growing fast.
In 2021, the market for AI in finance was already worth $9.45 billion, and by 2030, it’s expected to grow at a CAGR of 16.5%. So, how exactly is artificial intelligence revolutionizing the finance sector, and what can we expect in the years ahead?
What is AI in finance?
Artificial Intelligence (AI) in finance is the process of using intelligent technologies, such as computer vision, generative AI and machine learning to streamline and improve financial tasks. AI solutions empower financial services companies to boost the accuracy, speed, and outcomes of functions ranging from data analytics to risk management and fraud detection.
In the digital age, AI is helping to modernize the financial sector, automating manual banking tasks, and offering deeper insights into market dynamics. It’s also influencing the rise of new startups with the evolution of tools like AI investment assistants.
AI models can execute trades with exceptional precision and speed and take advantage of real-time data to improve banking decisions. Plus, while there are risks to using AI in the finance sector (more on that below), the technology can tackle a range of threats, too. AI solutions can help businesses rapidly detect fraud, minimize money laundering, and more.
Overall, AI’s impact in the finance sector is leading to a new era of data-driven decision-making, customer experience, security, efficiency, and cost-effectiveness.
The Drivers of AI in Finance
While some forward-thinking finance companies have been investing in AI solutions for a while, the demand for intelligence in this sector is growing. In fact, more than 85% of IT executives in the banking landscape have a plan in place for adopting AI in the years ahead.
There are a few reasons for this, such as:
- The growth of big data: The evolution of the big data market has had a huge impact on the finance sector. Customers now interact with banks and financial companies through more digital channels, allowing them to collect large volumes of unstructured data to use for personalized service delivery, predictive analysis, and decision-making.
- Transforming infrastructure: In the past, investing in AI would have been extremely expensive. However, the explosion of cloud technology, combined with as-a-service solutions for computational resources now makes AI more accessible. Even smaller companies can experiment with cutting-edge algorithms and AI models.
- Regulatory requirements: Banks have always faced a lot of scrutiny from regulators. However, as demands grow, AI solutions give companies a chance to address various challenges by automating tasks like data collection and fraud detection. AI can help finance companies adhere to changing compliance requirements.
- Advanced AI: In recent years, AI solutions have become far more advanced, from state-of-the-art computer vision models for processing financial documents to generative AI for enhancing customer experiences. This means there are now more use cases than ever before for AI in finance, driving rapid adoption.
- Competition: Finance companies are constantly competing with peers and emerging startups in the industry. Cutting-edge technology has become a crucial differentiator in this space. With AI, companies can stay one step ahead of the competition, accelerate their time to market for new offerings, and increase revenue.
The Benefits of AI in Finance
In every industry, various types of AI promise a wide range of different benefits to companies. As intelligent solutions evolve, the opportunities for finance sector organizations will only grow. For now, some of the most significant benefits of AI in finance include:
- Efficiency: AI can automate workflows and processes, working autonomously to complete countless finance tasks. They can monitor and analyze network traffic for risks or handle repetitive aspects of customer service. This frees financial experts to focus on more strategic activities and complex tasks.
- Accuracy: Errors can be disastrous in the financial sector. Artificial intelligence can help organizations minimize errors in data processing, analytics, onboarding, and customer interactions. With intuitive models, companies can keep manual errors to a minimum and deliver better customer service.
- Speed: The financial sector moves quickly. To stay ahead of the curve, companies need to process huge volumes of data at speed. AI algorithms can sort through information faster than a human, discovering relationships in data we might miss. This enables faster decision making, risk modeling, trading communications and more.
- Innovation: The ability to analyze huge amounts of data at speed can lead financial companies to develop innovative service and product offerings – outperforming the competition. For instance, companies can use AI to modernize insurance and investment experiences, while keeping operational costs low.
- Risk management: The risks in the financial industry are huge and constantly evolving. AI in finance gives companies more opportunities to monitor threats autonomously, identify fraud, and adhere to changing compliance standards. Plus, it can help them predictably anticipate risks and take proactive approaches to future threats.
Example Use Cases for AI in Finance
On a broad scale, artificial intelligence in finance gives companies the power to innovate at speed, maintain a competitive advantage, and deliver better customer service. Although the use cases for this technology are still being explored, there are plenty of examples of companies using AI already.
Here are some real-world insights into how AI works in finance.
1. Transforming Customer Service
AI has become a critical tool for improving customer experiences in virtually every industry. We’re all familiar with chatbots and virtual assistants that offer 24/7 support and guidance. These assistants are becoming increasingly powerful in the finance sector thanks to the implementation of conversational and generative AI models.
Bots in the finance sector can now personalize interactions with customers, drawing from historical and real-time data to help them complete various tasks. They can automate everything from account checks to the process of paying for financial services. Plus, they can offer real-time recommendations on the kinds of products and services customers might need, based on their history.
With speech recognition and sentiment analysis, AI tools can offer deeper insights into how customers feel throughout the interaction journey. They can offer businesses an opportunity to build more comprehensive consumer profiles which they can use to enhance marketing and sales strategies.
Plus, AI tools can even assist agents in contact centers, ensuring customers are routed to the correct professional based on their background or specific needs. This gives finance companies an excellent opportunity to differentiate themselves from the competition.
2. Optimizing Loan and Credit Services
Credit is still king in today’s financial sector. Over 678 billion credit card transactions occurred in 2022, and loans are everywhere. Unfortunately, it’s difficult for financial companies to safely determine how to distribute credit among consumers.
Artificial intelligence technologies help credit lenders and banks make more intelligent underwriting decisions by assessing various factors when evaluating borrowers. There are even enhanced AI lending platforms like C3.ai and Upstart that can help lenders lower default rates, approve more borrowers, and boost efficiency.
For instance, C3.ai says its intelligent lending platform can reduce the time required to approve a loan applicant by 30%. As interest rates continue to fluctuate and economic conditions become more complex, AI tools will become increasingly crucial in ensuring borrowers can access the right credit options without exposing themselves or financial companies to unnecessary risks.
The key to success here will be ensuring the algorithms used to process customer credit information are free from discrimination and bias.
3. Upgrading the Insurance Industry
Insurance and finance are two closely connected sectors, both of which rely on financial modeling to accurately estimate risk. There are various insurance companies embracing AI today, such as Lemonade, which uses artificial intelligence to enhance customer service and streamline insurance management tasks. The AI bots used by this company can process claims at exceptional speed, leading to better results for customers.
Additionally, the AI tools in the insurance landscape can help suggest relevant insurance products to customers based on their specific risks and history. They can even help businesses cut down on fraud, analyzing anomalies in claims to ensure that both companies and consumers are protected.
Leaders in financial companies can also use AI to assist them with various complex processes, such as auditing and tracking trends in the claim landscape. This can help businesses make better decisions about how to manage and deliver insurance products in the years ahead.
4. Improving Risk Monitoring
As mentioned above, one of the most significant issues AI in finance is addressing right now, is the evolving concept of risk. There are countless risks to overcome in the financial landscape, as well as numerous regulatory standards to adhere to. By processing huge volumes of data faster than humans, AI systems can be extremely effective at detecting risks and fraudulent activities.
Machine learning models are particularly adept at analyzing complicated data sets, helping companies to improve risk assessments and financial analyses. Plus, these tools can monitor various ecosystems in real-time, tracking anomalies such as fraudulent transactions, trading spoofing, and financial threats. Companies are even using AI for various know-your-customer (KYC) and anti-money laundering (AML) practices.
Using AI to analyze transaction patterns and customer data, companies can determine which entities pose the most risk. Plus, AI solutions allow for the development of more nuanced risk models for financial analysis. They can identify correlations in huge datasets much more effectively than humans, leading to well-informed decisions about lending, investments, and more.
The application of AI in finance for risk management even extends to enhancing the security of digital financial transactions, particularly in the age of DeFi (decentralized finance). Smart contract audits allow AI to scrutinize the code of smart contracts to detect vulnerabilities and fraud.
5. Enhancing Investment Services
In the investment landscape, AI is being used in various formats to improve performance. Investment platforms can use AI bots and assistants to enhance the way they deliver stock picks and recommendations to customers. Robinhood is a great example of this kind of platform. The app uses AI to differentiate itself from competitors.
Robinhood’s intelligent solutions can analyze risk tolerance, investment style, and history, as well as paying attention to market dynamics and trends to personalize user experience. Other apps, like Magnifi, use ChatGPT and other programs to give personalized recommendations to customers at speed, helping them to optimize their portfolios.
As mentioned above, AI solutions can also streamline trading and portfolio management. Algorithmic trading solutions can analyze historical data and market trends and then execute trades faster than human beings. Portfolio management tools can use economic indicators and market conditions to guide customers through effective strategies for financial growth.
6. Streamlining Tasks and Data Analytics
Finally, one of the biggest benefits of AI in any industry is that it can automate various repetitive and time-consuming tasks with exceptional precision. AI in finance gives companies an opportunity to improve data analysis, making it easier for them to process huge amounts of data and identify trends in the market, boosting decision-making.
Companies can use AI for predictive modeling purposes, using customer, risk, trading, transaction, and other data insights to predict potential future outcomes with phenomenal precision. This can help financial firms boost profitability, while reducing the costs associated with manual labor.
Plus, AI can automate a wide selection of other valuable tasks. AI tools can translate valuable financial content into different languages for consumers or extract structured and unstructured data from documents for team members. AI solutions with computer vision can even derive insights from videos and images to accelerate claims processing in insurance, or complete identity verification tasks.
The Risks and Challenges of AI in Finance
While AI in finance can be extremely beneficial, there are still numerous risks to consider too. Financial companies are held to strict standards when it comes to managing data securely and effectively. Companies still need to ensure they’re adhering to standards like FINRA and PCI-DSS when they’re using AI to serve customers and analyze insights.
At the same time, the risk of biased AI in the finance sector can be extremely high. Algorithms trained with limited or incomplete data can perpetuate discriminatory behaviors. For instance, an insurance company using AI to process claims and applications could accidentally end up showing preferences to customers of a specific age or background.
On top of that, there’s always a risk that AI algorithms may not perform as intended, particularly without regular training and optimization. Because of this, the use of AI in finance will require a focus on strict governance and caution. Companies will need to ensure they’re developing and maintaining safe, secure, and ethical AI systems.
For many businesses, this will mean implementing real-time monitoring measures to track the performance of AI solutions, and using guardrails to adhere to compliance standards. Additionally, firms will need to ensure they’re adapting to new AI governance standards as they emerge, regularly checking to ensure their AI systems are explainable, and transparent.
The Future of AI in Finance
There’s no denying that AI in finance will help to accelerate the growth of the industry. Many organizations already leverage AI to improve efficiency or deliver personalized customer experiences at scale. Continued progress in the AI landscape, with the rise of more advanced models and algorithms, will only increase demand for intelligent technology.
However, businesses will need to take a meticulous approach to adoption to ensure they get the most value out of their AI systems, protect their customers, and remain compliant. Organizations must ensure they find the right blend between AI innovation, and keeping human beings in the loop. Human experts will still be crucial to delivering empathetic customer service and fine-tuning AI and machine learning algorithms.
Like in most industries, AI won’t eliminate the need for real, human professionals in the finance sector, but it will transform tomorrow’s financial services and products.
