Fraud attacks that enlist AI-generated deepfakes that impersonate high-level executives and AI-created synthetic identities are only rising. According to SWIFT, the global industry estimates the total cost of fraud in financial services to be $485 billion in 2023.

“Bad actors are using increasingly sophisticated tactics to commit financial crime, and the global financial industry needs to raise its defenses higher to ensure their customers can continue to transact globally with confidence,” said Jerome Piens, chief product officer at SWIFT.

The project relies on the billions of transactions that transverse SWIFT’s network annually as learning data for the AI engine. SWIFT strips identifiers from the data to protect privacy and replaces them with pseudonyms.

“The technology will identify suspicious patterns in real time, reducing fraud risk and ensuring a safer banking experience for clients,” added John McHugh, head of CIB Operations and Control at Standard Bank, in a prepared statement.

The new technology builds upon the cooperative’s Payment Control Service, which numerous small and midsize financial institutions use, and is part of SWIFT’s portfolio of AI innovations.

Participating banks in the Asia-Pacific region, Europe, the Middle East, and North America completed the pilot with SWIFT earlier this year.

Additionally, the organization is working with major financial institutions to explore other ways they could share data among institutions while maintaining data privacy. One such technology they are investigating is federated learning, a machine learning technique that trains models across multiple decentralized servers or devices without revealing proprietary data.

Data sharing also earned a panel discussion during SWIFT’s 2024 Sibos conference in Beijing. Representatives from Deutsche Bank, Intesa Sanpaolo, UniCredit and SWIFT recognized the benefits of data sharing but called for regulators to define a minimum level of data that could be shared to improve fraud detection, Finexta reported. Until such regulations are in place, financial institutions will likely hesitate to share transaction data.

 The move comes as part of the Central Bank of Nigeria’s (CBN) broader efforts to address inefficiencies in the FX market, which has long been plagued by illiquidity, opacity, and multiple exchange rates. By introducing the Electronic Foreign Exchange Matching System (EFEMS), the CBN aims to create a more efficient and accessible market for all participants.

The most significant benefit of automation will be increased transparency. Under the current system, determining the real state of supply and demand in the FX market has been difficult, leading to market distortions, with insiders holding an advantage.

With EFEMS, real-time data on FX transactions will be available to the public, businesses, and international investors, allowing them to see market conditions clearly and make informed decisions. This shift is expected to level the playing field, reducing opportunities for bias and favoritism in foreign currency allocation.

Moreover, automation will improve efficiency. The manual, paper-based system currently in use often results in delays that frustrate market participants. With EFEMS, transactions will be processed much faster, eliminating these bottlenecks and allowing smoother operations for businesses reliant on foreign exchange.

While automating FX trades will not directly resolve all of Nigeria’s currency challenges, aligning the official exchange rate with market realities is expected to more accurately reflect the naira’s value.

Over-reliance on oil exports has made the naira vulnerable to external shocks, resulting in multiple devaluations. If the new system fosters a more transparent market, it could help stabilize the naira by narrowing the gap between official and parallel market rates. Still, EFEMS faces hurdles, such as the technology’s stability, widespread user adoption, and the CBN’s continued independence in enforcing policies. Automating FX trades represents a significant step toward creating a fairer and more efficient Nigerian market. If well implemented, the reform could restore investor confidence, reduce corruption, and strengthen the naira—helping Nigeria move toward a more sustainable economic future.           

Small and midsized enterprises (SMEs) typically face challenges securing trade finance, but by using real-time commercial data through Dowsure, HSBC can offer finance to sellers based on their transaction data. Dowsure, a lending partner of Amazon, provides HSBC with the interface, while Amazon offers merchant data on the Amazon platform. 

“This is a huge opportunity for suppliers and e-commerce platforms,” says Vivek Ramachandran, head of Global Trade Solutions: HSBC. “As an SME business customer on a large marketplace platform, like Amazon, Alibaba or XYZ.com, you can secure financing. You can click at the point of purchase to pay now or after 30 days. The large seller knows you and has a relationship with you, so giving you that stud page enhances sales.”

Ramachandran says it is a commercial decision for the large seller to make that decision thanks to their trust in the data and the relationship from previous sales. “I know you would come back to me so we can actually place embedded finance into the journey.”

He is exuberant about what this could mean for SMEs, saying, “This is where the next wave of innovation in trade finance will come from because eCommerce has moved faster than financing, and we need to change. Sellers on eCommerce platforms are small business customers to large and this will hopefully start making financing a lot more accessible today.”

Historically, trading relationships were built on intimacy. With the availability of so much data, Ramachandran says you can trade anonymously but still retain the trust built up through good experiences and consistency.

“Although our clearing systems, like the [US Federal Reserve’s Fedwire], don’t currently operate 24/7 when they do, we will be ready,” says Gayathri Vasudev, global head of cross-border payments at J.P. Morgan. 

“It is an always-on ecosystem, which will be a fantastic outcome, but immediately our clients can benefit from processing payments across a global network of 4,000 institutions,” continues Vasudev.  

Wire365 facilitates the cross-border movement of funds beyond the traditional processing cut-offs, with extended clearing windows to support clients in local time zones. This enhances the client experience across the Asia-Pacific region and the Middle East while optimizing working capital and liquidity between institutions and branches, even on weekends and holidays.  

“With Wire365, we enhance client productivity, especially for those constrained by traditional banking hours. Clients already banking with us can immediately benefit from enhanced efficiency and faster payment processing, with no implementation delay,” states Ciaran Byrne, head of Global Clearing Product and Transformation at J.P. Morgan Payments. 

As the world’s number one US dollar clearer, Vasudev says it is essential that J.P. Morgan can make payments cheaper, faster, and better. “One way we can do that is to settle through a real-time rate. Not only is it the speed of payment,” she says, “but it is also instant acknowledgement. It is not just being able to make the payments, but the readiness of your bank to provide your credit back to you.”

In the future, she continues, “We think having real-time always-on networks, where you don’t have to worry about clearing system cut-off times and having programmable payments, will be the ideal. But for now, we still invest in the traditional business, but we also have one leg in the future so that when our clients and other banks are ready, we can move them onto the new platforms if necessary.” 

The use of Large Language Models (LLMs) to increase efficiency, improve customer service, and enhance decision-making has been part of the conversation since the launch of ChatGPT by OpenAI in November 2022.  

While LLMs represent a significant advancement in the capabilities of AI, particularly in how machines understand and interact with human language, banks are taking a cautious response owing to concerns around regulatory compliance, data privacy and security, model accuracy and reliability, bias, and fairness.  

“Banks have been awash with data forever, but there is no prioritization, and tagging is incomplete or inconsistent,” states Andy Schmidt, vice president and global industry lead for Banking, CGI. “To be able to simply train a large language model to find the data, you need to have enough confidence in the data that it is usable enough.”  

“I think the important part that people need to sort out first is really getting the data sorted out. Setting out your data governance and making sure that the data is of a decent quality. Being able to de-dupe it and then figuring out where you need to enrich it,” he says.  

Standard Chartered is delivering AI-driven solutions and Margaret Harwood Jones, global head of Financing and Securities, says the bank has been working hard to solve data-management challenges. “You get so many instruction requests that come in in a very unstructured format, so we are using AI to turn those into structured data formats that we can then process efficiently.”  

At a Women in Tech Sibos event hosted by EY, panelists discussed how the only way to avoid biases in AI is to train LLMs to represent everyone from their inception, not just white males, and the only way to do this is to employ a more diverse range of staff.  

IBM believes that organizations need to proactively detect and mitigate risks; monitoring for fairness, bias, and drift. Updates to Granite Guardian 3.0, a widely used network monitoring tool in North America by Granite Telecommunications, allow developers to implement safety guardrails by checking user prompts and LLM responses. This includes checking for things like social bias, hate, toxicity, profanity, violence, and jailbreaking on 10 of the largest LLMs. 

Because of the potential risks and ethical implications, banks need to take responsible AI seriously, which includes taking a stringent approach to their data. 

As CFOs navigate an increasingly complex and interconnected world, understanding how to leverage data effectively can be a game-changer in mitigating risks and safeguarding financial institutions.

One of the key themes that emerged from the panel was the power of collaboration during one panel discussion, reports Finextra. By sharing relevant data, financial institutions can create a more comprehensive view of potential threats and identify emerging fraud trends.

This collaborative approach can help detect and prevent fraud more effectively, ultimately protecting institutions and their customers.

However, due to existing privacy laws and regulations, banks remain hesitant to share financial data. If data is shared, it is done via lateral agreements. The approach, while available today, has its limitations. From a technology perspective, relying on lateral agreements doesn’t scale well, and participation is entirely voluntary.

But something must be done and soon, said Sergio Antonio Dalla Riva, head of GTB product development solutions at Intesa San Paolo. “Hesitation is causing fragmentation and the fraudsters are laughing.”

Advanced technologies such as artificial intelligence (AI) and machine learning (ML) are increasingly crucial in fraud detection. These tools can analyze vast datasets to identify patterns and anomalies that may indicate fraudulent activity. By leveraging AI and ML, financial institutions can automate many aspects of fraud detection, freeing up resources for more strategic initiatives.

Data sharing and a technological initiative like SWIFT’s Federated Learning AI initiative, launched at last year’s Sibos, could provide the critical mass for an industry-backed solution.

While the benefits of data sharing are significant, it’s crucial to address the privacy concerns associated with handling sensitive information. The panel underscored the importance of robust data governance and security measures to safeguard customer data. This includes implementing strong encryption protocols, conducting regular risk assessments, and adhering to relevant regulations.

“The skeleton in the room is the concern that this data falls into the wrong hands…privacy is a key element,” said Michele Gentile, head of group correspondent banking, APAC, UniCredit, during the panel discussion.

By embracing collaboration, leveraging advanced technologies, and addressing privacy concerns, financial institutions can fortify themselves against the ever-evolving threat of fraud. As the financial landscape continues to evolve, the ability to effectively utilize data will be a critical factor in ensuring long-term success.

Representatives from China, the Bahamas, Kazakhstan and Europe each addressed the nuances of this burgeoning subgroup of the financial technology sector, according to Finextra.

The big takeaway: A more complete ecosystem is needed for widespread adoption of CBDCs to become a reality.

For Changhun Mu from China’s Digital Currency Institute, improving the legal environment is necessary in order to properly integrate the CBDC or eCNY (digital yuan or digital renminbi) and raise public awareness.

“Let every participant in the market understand what you are doing, what your products are, and what kind of incentives you can provide,” he said. “Then we can make the whole ecosystem for the market.”

Mu also highlighted China’s tiered wallet system for the digital yuan, which allows users to open a basic wallet with just a phone number. This system balances privacy and anti-money laundering (AML) efforts, with caps on wallet balances to prevent illicit activity. Mu stressed the importance of AI and big data technologies in securing transactions and protecting user privacy.

Evelien Witlox of the European Central Bank outlined progress on the Digital Euro, which has not yet been officially launched but is currently in the development and exploration phases.

Privacy concerns remain at the forefront of the design. In order for it to be structured for retail use, with both online and offline functionalities, central bankers want to ensure that online transactions would be anonymized once settled by the central bank.

Offline transactions, meanwhile, would resemble the privacy level of cash exchanges.

Witlox emphasized that stakeholder feedback and ongoing research are crucial as the Digital Euro moves toward standardization.

Henry Campell of the Central Bank of the Bahamas, shared insights on the Digital Sand Dollar—the world’s first fully deployed CBDC.

The coin, which launched four years ago this month, made the Bahamas a pioneer in the field of digital currency.

Currently in limited production, the Sand Dollar is expected to be fully operational by 2025 and integrated into tax management, decentralized finance (DeFi), and cross-border payments. Campell noted that the CBDC is reducing the costs and risks associated with cash and increasing circulation.

Assel Marchenko from the National Bank of Kazakhstan focused on curbing corruption, enhancing cross-border payments, and integrating with DeFi. Transparency in public spending is a priority, with the CBDC providing citizens with insights into the use of public funds.

Marchenko predicted that CBDCs will gain global traction due to their interoperability and efficiency in facilitating cross-border transactions.

The panel concluded with advice for central banks: Collaborate closely with private sector entities and develop clear business strategies in order to foster adoption.

Treasuries’ top challenge is securing financial investments focused on environmental, social and governance (ESG) concerns. Matt Cox, EY Global Commercial and Commercial Banking Leader, says that while expecting an ESG retracement, the opposite was true, as participants around the globe all thought banking ESG products and services were lacking.

The three subsequent challenges are digitizing treasury functions, managing real-time data feeds for accurate reporting and benchmarking performance. “I think we pick up a sense that treasurers are feeling under some pressure to evolve how they run operations in the context of this new technology-driven, digital world,” Cox suggests.

Adding: “I think it presents a huge opportunity for banks and other institutions, as only one in four corporate treasurers thought that their company was capable of delivering that capability in-house.”

The fifth challenge is accessing capital funding from non-bank lenders. “We see a high proportion of corporates accessing finance now from non-banks, and we expect that to increase in the future, and this is also something banks could get involved in facilitating from private credit,” states James Sanky, EY EMEA Corporate, Commercial and SME Banking Leader.

“In our mind, there are a lot of opportunities where banks could provide managed services for clients,” Sanky continues. Of the top five opportunities for banks to enhance treasury solutions, the top three areas they are willing to outsource are treasury risk functions, payment processing and cash and liquidity management.

If treasuries were to outsource those operational functions, they could focus on more strategic things, such as more analytics and decision-making, which can really help drive business growth.

On data-driven insights, 87% of the respondents said they would be comfortable with strategic advice based on aggregated internal and external data. In comparison, 92% said they were comfortable incorporating artificial intelligence into treasury operations. The desire for sector-specific offerings driven by data and insights also polled 92%.

“Although treasuries are moving to more strategic functions, they are still seen more of a cost center, while banks spend and invest a lot in technology,” remarks Cox. “So, if they can actually deploy that out to their clients, they could monetize treasury management services.”

The rise in e-commerce businesses, services, manufacturing and the gig economy has resulted in dramatic increases in both the volume and value of cross-border payments in recent years.

Long-term guaranteed fixed rates allow corporate treasuries to enhance financial stability, optimize liquidity, and align cash management practices with overall corporate strategy. It offers predictable returns, stable cash flow, interest rate protection and long-term liquidity planning.

“When FX risk is managed appropriately and efficiently, it can bring enormous value to companies that process large volumes of cross-border payments,” states Bhupen Velani, head of Transactional FX Trading in Global Markets at Bank of America. “As our clients’ business models have evolved, these volumes have increased, and so too has the appeal to lock in FX rates with longer tenors.”

BofA launched Guaranteed FX Rates beyond a 24-hour period eight years ago, supporting over 200 currency pairs. The one-year tenor is available in 37 currency pairs.

Daniel Stanton, head of Transactional FX in Global Payments Solutions, Bank of America, says for corporate treasurers, volatile FX markets exacerbate the challenge of cash flow forecasting. “Securing guaranteed FX rates of longer tenors can help them improve forecasting, which will lead to better informed decision-making.”

By forecasting cash inflows with greater accuracy, it allows for better budgeting and financial planning. With fixed returns, treasury departments can strategically manage cash reserves, deciding when to deploy excess cash or when to maintain liquidity for operational needs. Guaranteed rates also allow treasurers to align cash management strategies with long-term corporate financial goals, optimizing the use of excess cash for strategic investments.

Guaranteed FX Rates  can be obtained by BofA clients through the CashPro platform and via SWIFT with no additional technology changes required.

Long-term guaranteed fixed savings rates can be mutually beneficial, creating stability for both corporates and banks in a fluctuating economic environment. While they might not offer the same returns of some of the riskier FX products, the stability they provide makes them an attractive option.