Disclosure: The views and opinions expressed here belong solely to the author and do not represent the views and opinions of crypto.news’ editorial. From rising costs to attribution trust concerns, blockchain analytics will face many challenges in the coming year. As the year comes to a close, it’s that time again—time for predictions. We’ve heard plenty about the bright future of blockchain, from the promise of seamless cross-border payments to the rise of tokenized real-world assets (about $117.74 billion worth of assets tokenized as of now) and decentralized identity solutions (this market is projected to reach $2 trillion by 2030). You might also like: The strategic entry of institutional investors into cryptocurrency | Opinion Year of DeFi compliance DeFi is already on regulators’ radar. To name a few prominent cases, Uniswap Labs received a notice from the SEC and a $175,000 penalty from the CFTC; the court designated Lido DAO as a general partnership. Moreover, the court determined that identifiable participants actively managing the DAO’s operations cannot avoid liability simply because it is decentralized. No matter how decentralized DeFi projects are, be ready—2025 will be the year of DeFi compliance. And it has to be done. The total number of DeFi users has surpassed 131 million. Criminals use DeFi services to transfer and launder illegal funds, exploiting weaknesses in the technology behind DeFi platforms, enforcement, and AML/CFT regulations. Applying FATF standards to DeFi is challenging , especially when it comes to determining where platforms are based, operate, or are registered. With its no KYC, P2P transactions, cross-chain protocols, privacy tools, decentralized finance challenges regulators and analytics as well. Increasing compliance costs With more regulations, compliance is getting pricier. The alternative? Risking hefty fines, damaged reputations, and business interruptions. This is another big issue we will have to address, and we are already seeking ways to manage this by increasing the speed of operations. There are two main reasons for the cost growth: More challenges, which include: 1) The surge in cybercrime. For example, crypto investment fraud losses reported to IC3 jumped 53% in 2023. 2) Sanctions evasion. In 2023, a 114% rise in sanctions evasion incidents was recorded compared to 2022. This followed a 71.5% increase in 2022 over the previous year. 3) Fraudsters are learning fast and becoming harder to catch, for example, using AI. Regulators, such as the CFTC, warn about criminals leveraging artificial intelligence to execute more sophisticated crypto scams. 4) Growing political instability is driving shifts in crypto adoption and value. In regions experiencing political unrest, Bitcoin ( BTC ) adoption increases as individuals seek to protect their wealth from government interference and economic instability. The rising workload on compliance officers. With the growing regulatory clarity, there are more regulations to follow, which results in a greater workload for compliance officers who must ensure adherence to these new requirements. To sort just, say, 1,000 alerts per month, you need about 20 compliance officers, not to mention the money spent on KYC checks. So, if a business gets a customer who deposits $100, even $1,000, it doesn’t pay off if the officer has to check at least one alert regarding this customer. The compliance department is not the one generating profit—it spends money, and its costs are distributed across clients. Additionally, there is the risk of fines and imprisonment for non-compliance (remember Binance paying over $4 billion for AML and sanctions violation and CZ getting four months in prison ). This heightened workload not only strains resources but also increases the risk of oversight errors. The pressure to process thousands of transactions daily, each requiring detailed analysis and documentation, quickly can lead to missed red flags, incomplete investigations, or incorrect risk assessments. AI introduction One potential way to reduce costs is by introducing AI to automate simple tasks that don’t require a compliance officer’s decision-making. For example, it can handle sending notifications to specific compliance officers or distributing alerts among team members with the least workload, answering FAQs, etc. However, so far, AI is not ready to handle tasks that require human judgment, such as risk scoring. So, the best approach for now is to integrate it cautiously for routine tasks, and everyone can sign up to test AI in analytics with us. Attribution trust One of the reasons AI can’t yet be used for serious matters is the lack of attribution trust. It exists because two types of data might be confused: Instances where the data is 100% verified and reliable to be used in court. Cases where information comes from less trustworthy sources, for example, someone on X claiming some project is a scam. This type of data is not sufficient to seize funds or accuse a customer. Still, it can raise flags for compliance officers to investigate further. For attribution, only data with 100% proof can be relied upon—concrete enough to be used as evidence in court. Without solid proof, attribution can be dismissed or challenged in court. This weakens enforcement efforts and damages the reputation of the entire crypto industry. If attribution is inaccurate or unverified, people lose trust in blockchain analytics providers. As that trust fades, regulators and legitimate businesses may become hesitant to engage with crypto. Privacy of operations When we talk about trust, privacy is important, too. It’s crucial to keep all compliance activities private so no one knows which transactions are being reviewed until the process is finished. This level of confidentiality is essential not just for the business but also for regulators and law enforcement. For regulators and law enforcement, confidentiality allows carrying out investigations without interference so that bad actors don’t receive advance warnings. If it becomes public knowledge that transactions are under review, fraudsters and money launderers could exploit information to cover their tracks, delete evidence, or move illicit funds elsewhere. Using private servers like we do is a good solution to prevent this. It ensures the company/law enforcement/regulators can handle compliance activities without worrying about leaks or unauthorized access. With such servers, sensitive data stays under strict control, so bad actors won’t get tipped off about ongoing investigations. Read more: Mass crypto adoption requires transparency and education | Opinion Author: Lex Fisun Lex Fisun is a CEO and co-founder at Global Ledger, a Swiss company providing cryptocurrency AML risk analysis, blockchain forensics, and cybercrime investigation tools. Since 2015, Lex has worked in fintech, AI, and anti-fraud tech companies, leading him to founding Global Ledger in 2019 in response to increased scrutiny of crypto regulations. He has forged connections with top global organizations, including the United Nations Office on Drugs and Crime and the Global Coalition to Fight Financial Crime.
