AI in Financial Transactions: What Businesses Need to Know

The rise of AI is changing the way every business works, and nowhere more so than in the world of financial services. This means that whatever sector you’re in, you need to understand the benefits and challenges that AI is bringing, and in particular how it is affecting financial transactions now, as well as its ongoing direction of travel. The development of AI in finance is moving at lightning speed. Just keeping up with the latest developments isn’t enough. If you want to truly benefit from the AI revolution, you need to embrace it.

These are the major AI talking points in the area of financial transactions and digital payments.

The scope of AI in financial services

AI is shaping a revolution in financial services, payments and digital banking and, because every business uses digital finance, every business leader needs to understand its sudden rise. There are multiple opportunities to lean into, but at the same time AI in bringing new challenges. Remaining competitive in this new technological era requires being aware of and open to the extraordinary power that AI in financial services can – and will – bring.

AI in finance is the adoption of machine learning technologies in a wide range of banking and transaction services to deliver steep gains in efficiency, speed, and accuracy. AI algorithms can be used to analyze data, devise more accurate forecasting, manage investments, assess risk and enhance customer services. Many of the most time-consuming and repetitive tasks can now be automated, while AI’s ability to instantly analyze large quantities of raw data in depth offers a more accurate picture of financial markets and trends, enabling more-informed decision making. AI in banking has the ability to interact and engage with customers, allowing companies to scale up customer service offerings in ways that are highly cost effective.

Here are some of the key ways in which banks and financial institutions are embracing financial AI tools:

• Data analytics and modelling – the processing power of large language models makes light work of forecasting, giving more accurate insights into market trends, investor behavior, and risk/benefit analysis.
• Credit scoring and loan processing – AI is being utilized to assess the creditworthiness of bank customers and loan applicants as it can quickly access and analyze wider ranges of data than human counterparts. The loan process can be streamlined by automating routine elements such as document verification and risk assessment.
• Back office automation – routine tasks can be automated using AI, reducing manual labor and staff costs to contribute to operational efficiency.
• Algorithmic trading – AI’s speed of analysis is being harnessed to develop automated trading strategies.
• Compliance – AI is taking over monitoring and reporting for regulatory compliance, reducing costs, and increasing efficiency.
• Fraud detection – AI can spot unusual transaction patterns more efficiently than humans, making fraudulent transactions and cyber threats easier to detect.

These are just a handful of the ways in which AI in finance is already being used to transform day-to-day financial operations. According to a Bank of England/FCA survey, 75% of UK financial services companies are already reaping the benefits of introducing AI. These institutions are finding new ways to scale up efficiency, streamline workflows, make better decisions, and improve customer service. But as well as these, banks and other financial service providers are using AI to develop innovative ways of working, create new financial products and leverage new markets and income streams – from personalized banking to blockchain and crypto.

How AI is changing digital transactions

AI financial services are outstripping traditional banking services and nowhere more so than in the area of AI payment systems. It’s a dynamic arena, with fast-moving changes as new AI tools are introduced daily. Payoneer is at the forefront of the digital finance revolution for businesses, and we’re leading the way with our adoption of AI to streamline and speed up operations.

Payment systems are using AI both for back office and customer-facing functions, and the list of use cases in the sector is expanding quickly. AI is being integrated throughout digital payment systems to streamline processes and deliver more efficiently across areas such as security, analysis and customer service. The savings to be made in both time and money can be substantial, and the speed of adoption and development is transforming this area of digital finance.

These new AI transaction developments are creating new opportunities as the global payment ecosystem builds increasingly complex connections. For the players involved, competition is fierce, while for the regulators the challenge is to ensure that AI financial services are safe, secure, and working in the best interest of the businesses that use them.

Digital finance and AI transactions have proliferated in both business and personal finance. By harnessing the power of AI to analyze data at speed, payment service providers are able to gain insight into user behavior and market trends. This enables them to better anticipate and service their customers’ needs, leading to new innovations which make AI financial services easier and more convenient to use. Combatting fraud is another area where payment platforms are discovering the benefits of introducing AI into the mix. Fraud analysis and detection using AI is widespread across the sector.

AI financial tools that have already been introduced into digital payment systems include:

• data analysis
• customer behavior analysis
• demographics analysis
• trend forecasting
• fraud detection and mitigation
• customer onboarding processes
• document analysis
• handling large volume invoice processing
• analyzing transaction routing options
• auto-population of frequent payment details
• automation of reconciliation

In each of these areas, the efficiency gains contribute to making AI payment systems faster and easier to use, and as AI continues to develop apace, there will be more and more innovations coming onstream.

What businesses need to know to leverage the AI benefits

The adoption of AI financial services has happened very fast. For most people, the technology burst onto the scene just a couple of years ago, though obviously it has been in development for far longer than that. Now, it’s a major consideration for businesses of every size, while AI in finance is revolutionizing the way banks and financial institutions conduct their business.

So, what do you need to know about this new technology, both for integrating it within your own business and for assessing its usage in the companies you partner and do business with?

Here are some of the factors worthy of consideration when negotiating your way through AI financial services, and the ways in which the most successful adopters are leveraging benefits by embracing it.

• For AI adoption to reach its full potential, it’s essential to make a serious and ongoing commitment to introducing it in every sphere of the business. A half-hearted introduction in just one or two departments, followed up with nothing further, won’t benefit the company or its business. AI can’t be viewed as a finite project to be done and finished, allowing you to move onto other things. The key to understanding it and leveraging the power it offers is to view it as an ongoing and critically important process. It’s all too easy to get left behind, and no business can afford that.
• The commitment to AI needs to start at the top. If the boardroom doesn’t understand the potential of AI in finance, it will be very difficult to create and sustain a strategy for its rollout across the company. Not everyone in the organization will understand AI financial tools or be on board with its introduction, so part of an investment in AI must be to win hearts and minds, and educate people as to why it matters. A supportive workforce will make implementation easier. A company that sees the way forward with AI builds momentum and competitive advantage, leaving slow adopters in its wake.
• A central AI strategy needs a co-ordinated plan. Introducing AI piecemeal, department by department, results in confusion. A business needs to create a plan and then a framework that different AI functions can be built on, while working together in harmony. It also allows for AI skills within the business to be concentrated into a single strong unit, leveraging up knowledge and experience to take AI integration further. A central AI team can be used in a consultative capacity by individual departments, while taking ownership of a coherent whole.
• A company’s AI infrastructure needs to be as futureproof as possible. This means understanding what you’re trying to achieve, now and moving forward, and creating a framework that can handle the data and programming aspects, the required architecture to achieve goals, and the risks and regulatory environment in which the business operates, both locally and globally. The focus needs to be on the solutions and desired outcomes, and not just the technology for its own sake.
• Understanding the value of data in this new fintech world is critical. AI’s value lies in its ability to handle, analyze and draw conclusions from large data sets. This means data is your new raw material – a valuable asset that needs to be handled with care and closely guarded.

Keeping ahead of the AI challenges

Like all game changers in business, there are some challenges and risks involved with the adoption of AI in banking and AI in finance. After all, we’ve all seen the Terminator movies!

In reality, the challenges and risks resultant of adopting AI are generally more mundane than the naysayers would have you believe. However, it’s still absolutely necessary to be aware of them and the ways in which they might or might not develop as AI continues to evolve at high speed.

• While AI can bring considerable power to anti-fraud protocols, it is also attracting attention from bad actors who want to harness its capabilities for illegal use. This will come as a surprise to no one.
• Internally, the use of AI to analyze sensitive data comes with its own challenges. Data privacy and security must be paramount. Companies need to ensure that they are working within the regulatory frameworks for such activities, across whatever jurisdictions they operate in.
• Financial AI tools also need to comply with any banking and financial regulations any particular activity is subject to. Regulators include the FCA in the UK, the EU AI Act in Europe, and the NSCAI in the US. Regulations need to evolve as quickly as the technology they regulate, and businesses using AI will need to remain vigilant over compliance.
• AI LLMs are only as good as the data they’ve been trained on, and their tendency to hallucinate or show bias has been well-documented. Users need to be aware of this and take measures to ensure that these issues don’t impact their business.
• The wide scale adoption of AI will change companies’ workforce requirements. More employees will need to be trained to utilize AI, while other roles within the business will become redundant.

None of these challenges are insurmountable, but they do need to be taken into account.

How Payoneer is harnessing AI to benefit its customers

Payoneer is a mission-driven company that exists to connect small and midsized businesses and entrepreneurs to the ever-expanding digital economy. Talent is distributed evenly around the world. Opportunity isn’t. But by enabling our five million plus customers to enter the global marketplace and allowing them to receive payment from clients in other countries, Payoneer helps grow innumerable businesses around the world.

Payoneer has integrated the technology into its digital finance AI platform across a number of areas to ensure that it’s one of the safest AI payment systems in the world.

• By integrating AI-powered fraud detection and prevention into the customer onboarding journey, Payoneer protects against document forgery.
• The analytic capabilities conferred by AI allows the company to identify new fraud threats more quickly and accurately than ever before.
• The introduction of AI to onboarding allows for significantly faster and more accurate document processing, making the entire experience quicker and better for customers.
• Through the acquisition of an AI-powered data platform, Payoneer has been able to leverage AI and machine learning to analyze large datasets and provide quantifiable results to help it make predictions and decisions about its service offerings for its global customer base.

These are just some of the reasons to choose Payoneer for your digital payment platform. Others include the freedom to open local receiving accounts for international transfers, low fees, and the convenience of using our mobile app.

AI in finance is a gamechanger

AI has brought substantial and growing changes to the world of digital finance in a very short space of time. Its ability to leverage the use and value of huge datasets can be applied across all areas of AI financial services. The opportunities are multiple for companies who are willing to lean into this brave new world. Don’t get left behind, because the future belongs to those who grasp its potential.

Frequently asked questions 

The rise of AI in banking is happening fast, and it can be a lot to keep up with. If you have questions, we have the answers – a quick read through these should make things clearer.

What are the top AI financial tools available today?

AI is being incorporated into an increasing number of financial tools for automation, forecasting, compliance, operational efficiency, fraud detection and a multitude of other functions. Payment systems like Payoneer are leading the way to offer users faster and better services and enhanced capabilities, while banking and accounting apps are also becoming AI driven. When choosing a new AI financial tool, focus on whether it offers the functionality required, how much it will cost and how secure it is.

Is AI being used in payment systems and digital wallets?

Digital wallets and payment systems are using AI to meet increasing global demand for safe, user-friendly payment solutions. These allow for faster transactions that are safer for consumers, businesses and financial organizations. The technology is being integrated into existing payment systems to increase capability and functionality in areas such as data analysis, security and customer service.

How can businesses leverage AI to reduce fraud in transactions?

New technology can bring new opportunities for criminals, and cybercrime is on the rise. However, using AI to combat fraud is helping companies to fight back. AI can be used to analyze huge volumes of payments in order to spot suspicious patterns and deviations from normal locations, devices and payment histories. Unauthorized accesses can be challenged and cardholders notified.

What are the risks of using AI in financial services?

New opportunities also come with risks, and the widespread adoption of a new technology can present challenges. However, being fully aware of the risks of AI allows users to mitigate them. The risks of AI in financial services fall into four main categories:

• Data privacy and security issues
• Hallucination and bias
• Regulation of a fast-evolving technology
• Skill shortages and redundancies in the workforce

How does AI improve speed and efficiency in banking?

Data analysis and automation across the workflow are the two big areas in which AI is making an impact on productivity in the financial sector. AI’s ability to handle, analyze and draw conclusions from huge sets of data are also fueling improved decision-making and forecasting, while automation in customer services is bringing increased efficiency and satisfaction to customer interactions.

Are AI-powered payment solutions secure?

AI payment systems are generally more secure than non-AI payment systems. The technology can enforce more powerful methods of customer authentication, for both initial onboarding and regular logging in. It’s further able to immediately flag any change in spending habits that might suggest fraudulent payments being made, reducing fraudulent losses for customers and financial institutions.

Will AI replace traditional financial service providers?

While there are plenty of fintech startups bringing new AI tools into the financial services industry, traditional financial institutions are introducing AI into their own services and often partnering with these new companies to ensure that they remain competitive and relevant in a changing marketplace.

How is Payoneer preparing for the rise of AI in finance?

Payoneer is already using AI across a range of functions, including forecasting and modelling to identify new business areas for development. We also use AI to combat fraud, making every transaction more secure for our users, while at the same time improving our customer service to enhance the user experience.