Harnessing AI and machine learning for fraud detection in trade finance
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Harnessing AI and machine learning for fraud detection in trade finance
Banks, retailers, and other companies rely on trade finance controls to ensure their operations run smoothly. At the same time, criminals are always looking for ways to exploit processes, whether to launder money or get loans and avoid paying them back.
As financial organizations evolve from physical to digital documentation and security checks, it’s important to understand how artificial intelligence (AI) and machine learning (ML) can help detect and prevent fraud.
Get to know the benefits of such technologies in trade finance, especially when it comes to countering criminal activity. The next step is to understand how to best employ AI-based solutions and protect your company.
Why AI and machine learning are important for financial fraud detection
Considering the damage that financial fraud can cause, a security system with high-level manual and automated controls can catch suspicious activity before it leads to bigger problems.
Take the trade finance fraud case against Balli Steel Plc, for example. Through misleading information, as well as false documentation and business deals, the steel trader acquired loans amounting to around $500 million. Over 20 creditor banks were affected.
If your network and workflow incorporate AI-based tools, you’ll be able to verify identities, channel data into useful insights about customers and workers, see behavior and transaction patterns that don’t add up, and more.
However, perfectly combining your business with intelligent technology is easier said than done. It takes a careful plan and setup, as well as regular monitoring of data, programs, and people. Keep reading to find out what you need to set up the best system for your company.
How to use AI and machine learning in trade finance to combat fraud
The annual value of AI in banking is estimated to reach $1 trillion, and 25% of services in the financial sector employ ML techniques to support fraud detection, underwriting, and risk management.
The growing popularity of AI and machine learning in trade finance security is a direct result of how efficient the technologies can be. To put them to good use, follow the tips below.
1. Manage transactions
The main concern in this regard is transaction monitoring. It’s a major asset in countering fraud, money laundering, and terrorist financing as fraud increased by 30% between 2021 and 2022.
So, while setting up your company’s payment methods, from cards to virtual wallets, make sure you’re also able to check how customers use them.
Your AI/ML system can facilitate transactions, while flagging up suspicious activity, such as multiple failed log ins, inconsistent user details, large payments or deposits, and sign ins from different devices or geolocations.
2. Monitor other processes affecting trade finance
Securing your financial infrastructure as a trader isn’t just about transactions. There are more factors to consider, which AI/ML tools can enhance just as much.
For example, their automated operations make it easier to verify customer and worker IDs, assess risks during and after the onboarding stage, and comply with AML, KYC, and other regulations.
3. Collect and analyze data
All the information your company collects can be used constructively, but without the right tools or manpower, much of it is often stored and forgotten.
As the technology evolves, there’s no better option than AI for managing financial data. It can index, segment, and retrieve information faster and more efficiently than humans.
Such an algorithm can automatically organize data like email and IP addresses, card details, transactions, and behavior patterns. Then, it can deliver requested information or even in-depth reports full of insights about your business’s performance.
Data also teaches machine learning programs how to improve in their allocated tasks. The more information you feed them, the better they can meet your demands. It’s a mutually beneficial relationship.
4. Establish sophisticated security checks
According to AI in financial services reports, 31% of responding companies noted an increase in annual revenue and 28% a decrease in costs by at least 10% respectively.
While accurate models, efficient operations, and improved customer experiences are largely to thank for this, enhanced security shouldn’t be overlooked.
With AI-based payment and identity verification checks that utilize methods like device fingerprinting, IP analysis, and two-factor authentication, you can analyze users’ data and make sure you’re not dealing with fraudsters.
Making the effort helps avert data breaches and the loss of resources, from money and sensitive information to customer loyalty. The heavy penalties for failing AML and KYC mandates are easier to avoid, too.
5. Enforce consistent documentation and audits
If you don’t record and store financial information regularly and accurately, you will miss data vital to your company’s operation and advancement.
Besides setting strict rules for workers and algorithms, review all documentation when possible and specifically check for errors, discrepancies, hidden details, and other red flags of financial crime.
With the digitalization of auditing, it’s easier than ever to access and control data sources, streamline processes, and communicate with all parties involved.
6. Train staff in AI and machine learning
Your super intelligent network won’t be of much use if you and your employees don’t know how it works.
Before installing your desired software, assess your workforce’s understanding of AI/ML technology, identify what training you can provide, and prepare your staff for what’s to come.
If you aim to combine human and computer processes in a hybrid security system, for example, relevant workers should grasp what your AI tools even do and how to use them for different tasks.
With practice and additional training, your manual and automated operations should run all the smoother, whether you’re detecting and preventing fraud or streamlining your financial reporting.
Protect your finances as a trader with AI and machine learning
Think about the infrastructure your company’s financial processes need. Factor in the amount of data you generate, how many employees you have, what skillsets they lack, and, most importantly, what threats you’re likely to encounter.
AI/ML solutions are the way forward. They do have a steep learning curve, but once you understand their functions and benefits, your business will become safer and far more productive.
Wanda Rich has been the Editor-in-Chief of Global Banking & Finance Review since 2011, playing a pivotal role in shaping the publication’s content and direction. Under her leadership, the magazine has expanded its global reach and established itself as a trusted source of information and analysis across various financial sectors. She is known for conducting exclusive interviews with industry leaders and oversees the Global Banking & Finance Awards, which recognize innovation and leadership in finance. In addition to Global Banking & Finance Review, Wanda also serves as editor for numerous other platforms, including Asset Digest, Biz Dispatch, Blockchain Tribune, Business Express, Brands Journal, Companies Digest, Economy Standard, Entrepreneur Tribune, Finance Digest, Fintech Herald, Global Islamic Finance Magazine, International Releases, Online World News, Luxury Adviser, Palmbay Herald, Startup Observer, Technology Dispatch, Trading Herald, and Wealth Tribune.
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