The fintech industry is rapidly evolving, and among the most notable trends that have arisen are asset management, AI-powered advice, and intelligent automation. Simultaneously, previous fintech innovations like neobanking, embedded banking, big data and analytics, and blockchain integration are still growing and evolving. Furthermore, the fintech industry is expected to grow rapidly and reach a valuation of $556.5 billion by 2030.
The fintech industry will continue to expand quickly due to both changing customer behavior and continuous technology developments. In this piece, we’ll examine the fintech developments that will influence the sector in 2024 and beyond, as well as their possible benefits for financial services firms.
Financial services firms now have new options to provide services that are quicker, more precise, and more economical – thanks to intelligent automation. Automation technology will significantly change the banking industry by enabling the standardization and simplification of key financial operations. Automation necessitates the development of utilities tailored to finance that are distinct from those used in other business areas.
Leaders in the financial services business acknowledge that intelligent automation has the potential to be disruptive. According to a Deloitte analysis, robotics, intelligent automation, and organizational excellence can increase productivity by 20–25% overall in a year. When applied appropriately, it improves service quality, speed, and accuracy, which is crucial for procedures like reconciliation and billing.
However, intelligent automation goes beyond specific procedures. It has the ability to enable automated operations across the entire organization, even going so far as to establish automated processing centers that carry out and confirm job completion with little assistance from humans. The following requirements characterize intelligent automation in finance both now and in the future:
For financial institutions, timing is critical, and it can be significantly enhanced by using automation technologies, which enable concurrent validation, modification, and calculation across several processes. Furthermore, because automation minimizes downtime due to time zone differences and process wait times, it permits task balancing. Automation solutions may essentially operate continuously, eliminating time zone differences and enabling a far more compact weekday schedule.
Recurring control inconsistencies can be identified and reduced with the use of business rules, uniform quality levels, and standardization.
Business partners’ trust in financial services organizations will continue to be greatly influenced by the promptness, caliber, and correctness of the services and information they receive. Automation guarantees fast and accurate operations, which upholds high service standards and improves the standing of financial service providers.
Consolidation of working locations and facilities is made possible by automation. It significantly lessens the need for outsourcing, which is especially important given the seasonality of several essential processes like filing taxes.
Given that intelligent automation is already a key factor in the success of the financial industry, it is safe to argue that it transcends current trends. Financial services companies will keep investigating and utilizing robotics and intelligent automation in 2024 to increase productivity and accuracy.
Personal finance management is already being transformed by AI and machine learning, and in the near future, financial advisors powered by AI will be the norm. The use, accuracy, and utility of AI-powered advisers are already among the fintech trends that are expanding the fastest, and these tools will continue to rise in popularity. After evaluating the user’s spending habits and financial goals, these advisers will provide them with tailored advice for a variety of use scenarios.
AI-driven advisors for budgeting will support customers in creating a budget based on their income and costs, track their spending patterns, and provide recommendations for possible cost-saving measures.
Investing Intelligent advisors will help choose investments based on consumers’ risk tolerance and financial objectives. Additionally, they will closely monitor the existing investments and offer advice as needed.
AI-powered advisors for debt management will assist consumers in creating a productive plan to pay off debts quickly. With the help of these tools, which monitor expenditure, recommend eliminating unnecessary expenses, and recognize accomplishments, the user will be encouraged to pay off their debt.
The general population will have more access to and benefit from financial advice. One-size-fits-all financial advice is almost history, and in the years to come, the main emphasis will be on more individualized financial guidance. In the broader context of financial services, asset management will also depend more and more on technologies driven by AI and ML.
Due to a few fintech investment trends, the total amount of wealth under management globally is increasing gradually and is expected to reach $4 trillion in 2024:
As the early excitement surrounding AI fades, businesses start to see its real potential. Financial services companies are rapidly approaching the productivity plateau by utilizing artificial intelligence (AI) in asset management and financial consulting, which will remain a top fintech trend in 2024.
Fintech systems can utilize generative AI models to handle activities like credit rating, asset management, and fraud protection. Financial services companies are able to utilize generative AI in more and more scenarios as their capabilities grow. Let’s examine the potential effects of generative AI on the fintech sector in 2024 and the years to come.
Financial services organizations may make better and more accurate decisions by using generative AI to analyze past trends, transaction records, spending habits, and other client data. This can be very helpful when determining whether an investment is reliable or if a client is trustworthy.
Trading is transformed by the use of generative AI, which makes it possible to analyze market data trends and current market circumstances to anticipate future events with confidence. Automated and pre-programmed trading instructions covering variables such as price, time, and volume can be implemented through algorithmic trading. This allows for the majority of active trading to be automated with little need for human intervention.
The global market for fraud detection and prevention is expected to reach $252 billion by 2032, up from $29.5 billion in 2022, according to Allied Market Research. A key factor in this growth is generative AI. These trained models can sort through enormous amounts of transaction data by utilizing the constantly developing AI, and they can spot odd patterns that could indicate possible fraudulent activity. Generative AI functions as a deterrent against questionable behaviors by identifying abnormalities in user behavior and suspicious data patterns.
Generative AI provides important assistance in guaranteeing adherence to financial regulations and reducing the possibility of regulatory transgressions. It is able to comb through large amounts of legal and financial documentation while keeping an eye on changes to regulations and upgrades in real-time. This capacity can be used to automate processes, lower the possibility of human error, guarantee compliance with important legislation, and eventually avoid fines from the authorities.
As previously indicated, generative AI greatly increases the precision and effectiveness of financial advice, especially when it comes to financial planning and investing decisions. This might be carried out on a large scale for a single client or for the whole company. AI-powered financial solutions can assist with risk management, expense analysis, investment suggestions, and creating customized investment plans that meet each client’s specific financial objectives. Generative AI, for instance, may build personalized investment portfolios based on a person’s goals and risk tolerance, and it can modify recommendations when conditions alter.
Artificial intelligence (AI)-driven chatbots and digital assistants may produce context-driven material, which allows them to help users with activities like choosing investments and making complicated financial decisions. Furthermore, contemporary chatbots are able to retain user context and carry on conversations that use past inputs to produce more insightful and helpful responses.
Naturally, generative AI has applications in the financial services industry beyond the use cases mentioned above, and these applications will only grow over time. Financial service organizations will be able to make even more significant decisions thanks to the use of generative AI, which will also increase the accessibility of sound financial decisions for larger audiences.
Big data is becoming more and more important in the financial services sector. Large datasets can be used and leveraged by businesses to improve customer experience, lower costs, increase operational efficiency and get insightful knowledge about customer behavior and preferences. Financial services businesses will benefit from and find many uses for big data, one of the major fintech trends.
Facilitates the development of deals and marketing efforts that are specifically designed to appeal to particular customer segments.
By examining transaction patterns across numerous accounts, fraud detection builds confidence and reveals fraudulent activities, such as money laundering or identity theft.
Financial organizations can improve the way they analyze risk for loans and investments by analyzing historical data. Big data-enabled predictive analytics models can also facilitate better decision-making by leveraging past patterns, anomalies, and variations in data sets. In this sense, the aforementioned powers of generative AI and intelligent automation can augment the advantages of large data.
Big data, when combined with automation, ensures accurate and dependable outcomes by doing away with the need for expensive human labor. It also enables businesses to identify any problems early on and prevent them from becoming serious ones, which saves money, effort, and reputation.
The use of big data in finance is not without its difficulties, despite its many advantages and wide range of applications:
Notwithstanding these difficulties, big data in banking has advantages that outweigh the dangers by providing insightful information, freeing up resources, and reducing expenses. Realizing big data’s full potential in financial operations is the key.
One of the main factors promoting expansion and progress in the financial services sector is big data, which provides better consumer experiences along with cost savings, greater security features, and better decision-making abilities. Big data and analytics will undoubtedly be among the top fintech trends in 2024 as the volumes of data generated and used by financial organizations increase.
Embedded finance solutions improve client accessibility by seamlessly integrating financial services and products with non-financial products or applications, such as websites or mobile apps. Customers can use their digital wallets or other fintech-based payment methods, such as online savings accounts, when making purchases online, for example.
When the financial services sector realized it could provide services to consumers directly without depending on traditional banking institutions, that’s when the fintech trend started. The advent of digital-only banks was brought about by this change, which forced established banks to adopt embedded financing solutions.
A Dealroom analysis projects that by 2030, the market for embedded finance solutions would be worth $7.2 trillion, more than the total value of the top 30 global banks and insurers as well as fintech startups put together. According to the report, insurance, loans, and payment-related services like branded credit cards would be the main drivers of this increase.
This trend is anticipated to continue in 2024 as more businesses become aware of the time and money benefits that come with incorporated finance solutions. Fintech will be used by an increasing number of businesses to offer customized financial services to their clientele.
The crux of this article is that we can expect major developments in the fintech sector in 2024, and in coming years as well. High-end technical innovations and technology like intelligent automation, AI-powered devices, generative AI tech, big data and analytics, and embedded financial solutions will have a major impact on financial services and will change them for good. As more and more financial institutions adopt these new technologies and trends, they will see improvements in client experiences, enhanced operational efficiency, and more new growth and innovative opportunities.
