Freight shipments for more than 500 businesses were impacted when a container ship struck the Francis Scott Key Bridge in Baltimore, USA, in March 2024. A surge in insurance claims and loan applications followed, as firms sought to recoup their losses and cover immediate expenses that arose from freight diversions and delivery delays. For each business, financial services providers had to follow processes of assessing damage, calculating the cost of replacement orders and lost revenue, reviewing financial history and conducting risk assessments.
Financial services firms must have systems that facilitate a quick response to supply chain disruptions, like the Baltimore bridge collapse of March 2024
The Baltimore incident is just a single example of the severe supply chain disruptions that have impacted all types of businesses across the world in recent years.
“Banks are at the centre of the global supply chain because everything has to be paid for and therefore entails risk,” says Peter Hazou, director of business development for financial services at Microsoft. “Disruptions to the global supply chain can happen quite unexpectedly and, since the banks are doing the financing and taking those risks on shipments, they require quick access to data from delivery companies to track cargo.”
In addition to helping them to calculate risks, accurate data insights can help financial institutions to make smart decisions and identify opportunities for growth.
“Banks first discovered the value of data when they were investigating financial crime,” explains Hazou. “Of course, data was valuable before that but they hadn’t realised it yet. Data helped banks to uncover spending patterns in real time and notify clients about suspicious activity in their accounts. Now, data can drive even greater value as new technology can piece together information from different departments and legacy silos to provide a full 360-degree view of organisational performance.”
For example, banks can use Microsoft Fabric to bring all their data and analytics tools into a single experience by connecting data silos through OneLake. Employees can access this data through Microsoft 365 applications and analyse it with tools like Microsoft Copilot to improve decision-making and customer service.
“Banks are interested in focusing on a much narrower set of data to ensure accuracy and context,” says Hazou. “They do this by starting with internal use cases for internal users. For example, relationship managers in call centres can use agent assist solutions to improve their customer service.”
Generative artificial intelligence tools like Microsoft Copilot for Sales enable employees to better understand customer context along with the historical data they would naturally have access to in their customer relationship management systems.
“Generative AI is a fast-moving technology that has gone from providing the right response to a natural language enquiry to being a model that is more conversational so clients can interact with avatars that actually ‘speak’ with them,” says Hazou. “It gives the context of the person or enquiry, such as whether they have a retail or business-to-business account, and helps relationship managers or call centre agents to frame their responses.
“But Copilot has its name for a reason – it assists the human in the loop of the work to provide better insights so they can address customer needs. It also enables employees to access their organisation’s knowledge bank during meetings so they can answer questions quickly and confidently, providing the best solutions for clients. After meetings, Copilot is perfect for summarising talking points and highlighting any actions that need to be followed up on. It’s a tremendous aid in making relationship managers’ jobs more efficient and minimising mundane activities that are currently a major use of resources in the bank.”
One bank which is putting the power of generative AI into action is Akbank, which has 10.8 million customers across more than 700 branches and 12,000 employees. Akbank developed a smart digital chatbot assistant, based on Microsoft Azure OpenAI Service, to search through approximately 10,000 records to help its employees save an average of three minutes in every interaction with a customer.
“The chatbot presents the most up-to-date information in every query, which is crucial in a fast-paced banking environment,” says Gizem Yalçin, the smart digital assistant applications technical product owner at Akbank. “When needed, branch employees save time in every customer interaction using the chatbot. And with every minute saved, our productivity increases.”
Looking ahead, Akbank plans to bring the chatbot directly to its millions of active customers and enable them to address their queries without middlemen.
Similarly, Intellect Design’s iGTB Copilot, also powered by Azure OpenAI Service, enables bank customers to self-serve by answering natural language enquiries with AI.
“iGTB Copilot can discern insights from payments,” says Hazou. “It can also find out which counterparties are paying customers late and from which locations. Currently, organisations do this by viewing a bank statement through a Swift message type called an MT 940 and correlating it manually. But with natural language processing, simple enquiries can be resolved quickly and easily. It’s about empowering clients so they can self-serve and that’s a result of the whole modernisation of this interface between clients and their banks.”
“New technology can piece together information to provide a full 360-degree view of organisational performance,” says Peter Hazou, director of business development for financial services at Microsoft
As such, digital transformation strategies such as getting data in order provide value for financial services customers who are looking for insights about their own business and how they are performing in comparison to their peers.
“Data can offer insights into a client’s business operations, such as forecasting cash flow based on historical transactions,” says Hazou. “It can also pull value from environmental, social and governance, weather and economic data like movement, exchange and interest rates. There’s a broad set of data that can affect, for example, financial forecasting and help companies better predict their positions and what their needs are.”
The power of data in trade finance
Technologies that help businesses capture and analyse their data can also help to automate traditional back-office processes, such as those in trade finance operations.
“The work that Microsoft is doing in trade finance focuses on data,” says Hazou. “In the current environment, trade finance documentation is processed manually. There are said to be four billion pieces of paper in circulation for trade finance every year. This is because it follows an old business model that dates back to the House of Medici, an Italian banking family in the 15th century. A lot of the documents – such as bills of lading and exchange, invoices and certificates of inspections – have been mandated to be in paper form due to pre-existing legislation.”
In 2022, the International Chamber of Commerce estimated that digitising trade documents could generate $25 billion in new economic growth by 2024, and the industry is already making significant changes to digitise and automate bank processing, paving the way for increased efficiency globally.
“There have been changes to the regulations for trade paper,” says Hazou. “The UK passed a new act called the Electronic Trade Documentation Act in 2023, replacing the former law, which was set in 1882 and required wet signatures, meaning that trade documentation had to be on paper. It is currently being adopted in other European countries and in the USA.”
The new law enables organisations to digitise processes. “For example, a letter of credit is traditionally printed out on paper, signed, dated and mailed to the bank,” says Hazou. “The big move at the moment is to scan those documents into a system through optical character recognition and apply rules related to letter of credit to check the documents for compliance and identify trade-based money laundering with AI. With certain trade documents now able to be provided in digital format, it means that bank processing can be carried out more efficiently.”
Microsoft is collaborating with several partners to develop solutions for digitising trade documents that can be processed automatically with AI, including Cleareye.AI, Conpend and Traydstream, which all power their solutions with Azure. These documents include letters of credit for trade finance and bills of lading for supply chain finance, which are issued by carriers to acknowledge receipt of cargo for shipments.
The internet of things (IoT) is also helping banks to improve their trade finance functions with real-time data, specifically in supply chain finance.
“During the pandemic, one bank asked us to help it monitor the temperature of hundreds of batches of vaccines,” says Hazou. “The bank needed to be sure that the value of the cargo would remain high to benefit from its investment in the supply chain, which it referred to as a ‘chill chain’ because the vaccines needed to be kept below a certain temperature to remain effective and bought by government organisations.
“Under the right conditions, IoT sensors could continuously track and report the temperature of the vaccine batches in real time, ensuring any deviations were promptly addressed to maintain the cargo’s integrity and value. IoT data can also be used to track transport routes, weather and geopolitical risks that can affect the duration and financing of shipments.”
Microsoft partner Trade Ledger has developed a solution to help with supply chain queries like this. The firm’s Working Capital Copilot uses generative AI, powered by Azure OpenAI Service, to answer mundane and repetitive trade and supply chain finance questions in Microsoft Teams so banks can better serve their clients. Examples of possible questions might include: “when can I expect my payment for the shipment of goods?” and “what documentation do I need to complete for cross-border trade?”.
“Users can ask simple natural language questions and the copilot will transform them into queries about the business and respond with the answers that they need,” says Martin McCann, CEO of Trade Ledger. “Through this, we’re making conversational analysis available for everyone who needs to see it for their corporate customers.”
This technology represents a shift in how banks can interact with and support their clients more effectively.
“Traditionally, banking is a passive business where you go to a bank to do something,” says Hazou. “But with all of these insights from data, banks are in a position to provide more value-added services that go right to the centre of what clients need.”
Read more: Peter Hazou on how modern technologies like AI can improve customer service, combat financial crime and increase profits
Partner perspectives
We asked selected Microsoft partners how Microsoft-powered solutions are helping financial services firms to upgrade their systems and use data more effectively
“At Finastra, we leverage Microsoft-powered solutions to enhance data utilisation and streamline trade and supply chain finance processes through automation,” says Anastasia McAlpine, head of product management for trade and supply chain finance at Finastra. “AI-powered tools can help banks to overcome challenges of manual tasks to boost everyday productivity and cost efficiency, enhance risk and fraud management, provide real-time insights and seamless digital customer experiences, and support sustainable finance – all of which foster stronger global trade growth.”
“Working capital lenders still deal with data that remains on paper and in PDFs for business customers,” says Martin McCann, CEO and founder at Trade Ledger. “Microsoft solutions like Azure, Power BI and Dynamics 365 are game-changers, providing scalable cloud infrastructure, real-time analytics and actionable insights that drive smarter decision-making.”
“Microsoft technology, particularly Azure services, supports us significantly by offering seamless integration and advanced analytics and AI capabilities,” says Stephan Hufnagl, chief technology officer at Traydstream. “We leverage Fabric to consolidate our data assets, generating comprehensive reports and metrics for the organisation. This provides an in-depth view of every aspect of our business, identifies focus areas, and establishes a foundation for our AI developments.”
Read more from these partners and others including Cleareye.ai, Conpend, Infosys and Orion Innovation in the Autumn 2024 issue of Technology Record. To get future issues delivered directly to your inbox, sign up for a free subscription.