The Latest Predictions and Trends Shaping AI’s Role in Finance
The financial industry is rapidly changing these days. Looking back over the years, we’ve seen the introduction of mobile payments, blockchain, and AI, which begs the questions; what is next? And even though there has been recent talks about AI having to slow down progress and advancements, AI labs have been working hard to bring about the best artificial intelligence software, and it’s already making a huge impact on the finance sector.
According to venture capitalist Nikita Arora from Dig Ventures, “the long-term demographic transition and improving AI technology will create a new “race to zero” cycle that reduces fees". She also predicts that the downward pressure on fees will lead to a further consolidation amongst the current financial corporations.
When it comes to the financial industry, AI can recognize fraudulent patterns, flag suspicious activities, detect fraud, and analyze cash flows. Because of these capabilities, businesses depend on AI to assist with credit scoring, transaction validation, budgeting, etc.
Here are a few predictions about what’s to come:
1. Risk assessment and enhanced precision
Artificial intelligence has been used to provide enhanced precisions and improve on risk assessments. Since AI can analyze large amounts of data at a time, it can assist with the identification of potential compliance issues and risks in the financial industry. This capability can assist corporations to better manage challenges and mitigate them.
2. AI cryptos
AI isn’t just used in traditional finance markets; AI cryptocurrencies are crypto coins that use advanced artificial intelligence technologies to enhance various aspects of their operation. These enhancements can include improved security, more efficient transaction processing, and smarter trading algorithms. AI can analyze large volumes of data at high speeds, enabling these cryptocurrencies to adapt to changing market conditions more quickly and accurately than traditional systems.
With elements or decisions generated by AI, these cryptocurrencies aim to offer a higher level of performance and user experience, which are already granted with crypto — so they take things to a whole new level. Blockchains such as Injective (INJ) and The Graph (GRT) are two of the most well-known examples of AI crypto at the moment, but there are sure to be more and more of such projects as AI technology becomes even more powerful.
3. Financial management
With a more personalized touch to the financial services, AI can advise customers on which investment plans and insurance policies would best fit their needs. With individual data analysis and preferences, AI can create tailor made solutions for all customers.
4. Investments and automatic trading
According to the senior vice president and general manager of AltLINE by The Southern Bank, Jim Pendergast, “ AI is inherently persistent, so it can improve a much narrower picture of what will work and what won’t based on previous information. When it comes to investing, having this level of consistent understanding of the market can help investors make the right choices."
The same logic applies to the trading industry. With the right algorithms in place and by analyzing past and future trends, AI can efficiently predict which trades would be safe to take and which not. With data analysis and complex mathematical models, AI can analyze financial data, the market trends at higher speeds over human capabilities, and assist investors with informed and efficient trading strategies.
5. Generative AI in finance
When it comes to the banking and financial industry, General Data Protection Regulations (GDPR) is of the utmost importance and both challenging and critical due to the amount of sensitive data that the firm handles. With the innovative solutions offered by generative AI, compliance to the GDPR is assured — especially when it comes to the awareness and fines related to GDPR breaches.
Banks and financial institutions can use automated classifications to protect the sensitive data across multiple systems to ensure they are compliant with the GDPR requirements.
6. AI Chatbots: 24/7 assistance
Customer service is another field affected by AI, not just in finance. Recently, there has been an increase in AI-powered virtual assistants and chatbots, which can provide customers with more efficient support for all their baking needs. These AI-powered tools mainly handle routine enquiries, but over time this fact might change, as AI is a fast adapting industry.
7. Fraud detection and prevention
AI is being used by organizations in the finance industry to detect and prevent fraud and will continue to grow in the years to come. With the use of advanced algorithms, AI has the ability to analyze a large amount of data to identify any suspicious activities and patterns to help the financial corporations to detect fraudulent activities early on or rather before anyone is harmed financially. With the advancements of fraud detection and prevention, financial institutions can better protect their assets and customers.
8. Enhance data analysis and decision making
With the ability to analyze large and complex datasets, AI has been helping financial organizations make more informed decisions. With the use of predictive analytics and machine learning, we have seen AI provide more valuable insights that can improve the financial sector. With overall operational efficiency, enhanced data analysis and decision-making, we can see bigger improvements coming to the financial industry.
Conclusion
As AI grows within financial organizations, transforming the industry and automating operational tasks all while reducing manual labor. This growth allows all employees to focus more on the impactful and creative side of the job, while AI brings about innovation and change. Most people view AI as “machines that will replace human workforce”, however, as technology and artificial intelligence grow and evolve, we can see AI plays a lucrative role in shaping the future of finance and not as a replacement of the human workforce.