rewrite this title Aurum’s CEO On How AI and Machine Learning Redefining Crypto Trading

by
Alisa Davidson

Published: December 10, 2025 at 6:00 am Updated: December 10, 2025 at 5:47 am

by Ana

Edited and fact-checked:
December 10, 2025 at 6:00 am

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AI has transformed trading by enabling systems to process vast amounts of historical and real‑time market data far beyond human capacity. By combining past price and volume data, order‑book dynamics, on‑chain metrics, and sentiment signals from news or social media, AI can detect patterns and market inefficiencies that might take human traders days to spot—or that humans might miss entirely.

In a conversation with Mpost, Bryan Benson, CEO of Aurum, explained how the platform leverages AI and machine learning to identify trading opportunities, manage risk, and execute trades at speeds and scales impossible for human traders.

AI trading algorithms can process massive amounts of market data in milliseconds, spotting patterns and opportunities that would take human traders days. Aurum’s AI models leverage both historical and live cryptocurrency data to identify mid-term trading opportunities that might elude manual traders.

“It’s all about scale and speed,” the Aurum founder said. “A human trader might track five indicators on a few assets. Our AI analyzes thousands of data points across every major exchange and updates positions in milliseconds.” Years of historical price action, order book depth, volume trends, and on-chain metrics teach the models which patterns repeat across cycles. But history alone isn’t enough. “We validate it against live signals—social sentiment, breaking news, whale wallet movements, liquidity shifts on DEXs. The AI continuously adjusts, so it can act before humans even notice an opportunity.”

Overcoming Human Bias And Volatile Markets

As retail traders often succumb to fear and greed, AI systems execute trades purely on data and preset rules. This requires sufficient training and validation of the AI models to avoid human biases and maintain discipline during highly volatile market swings.

“The beauty of AI is that it has no baggage,” the Aurum founder explained. “No fear, no ego, no emotional memory of past losses. We train it on the worst periods in crypto history—flash crashes, liquidation cascades, panic sell-offs. Those are exactly the moments when our models shine.” Drawing from their experience as Managing Director at Binance, they added: “I’ve seen traders abandon rules under pressure. The AI doesn’t do that. It follows discipline, not emotion.”

Unlocking Benefits Of AI Trading Bots: Arbitrage And 24/7 Trading Advantage

Aurum’s AI trading bot is unique because it is capable of various activities on par with humans—it implements arbitrage and other grid-trading strategies.

“Yes, arbitrage is core, but we do it differently,” the founder said. “We use AAVE’s flash loans to execute trades in a single atomic transaction. The AI spots price discrepancies across DEXs, borrows funds, buys low, sells high, repays the loan—and if anything fails, it all reverts. The only cost is gas.” By integrating directly with major DEXs and checking liquidity in real time, the system only executes when the spread guarantees profit.

Addressing concerns related to market volatility, he further noted: “Traditional stop-losses aren’t needed for our flash loan arbitrage model. Volatility creates opportunity. Wider spreads between exchanges generate more arbitrage. Position sizing and risk limits are adaptive, built into the system.”

Furthermore, the solution offers opportunities for 24/7 nonstop trading, which is advantageous to users.

“Humans need sleep, weekends off, time away from screens,” the founder said. “The market doesn’t. Some of the sharpest moves happen on Sunday nights, when liquidity dries up, or during timezone handoffs between Asia, Europe, and the U.S. Our AI never sleeps. It sees inefficiencies, reacts instantly, and captures opportunities before anyone else does.”

“Our philosophy is zero stress for the user,” they said. “Complexity happens on our side. Zeus AI Bot lives on Telegram, so people manage portfolios where they already spend time—no new apps, no learning curve. You check in when you want, not because you have to.”

Regarding the data inputs and features Aurum’s trading AI uses, to ensure the quality and relevance of signals, Bryan Benson notes: “We use everything that matters—price, volume, order books, on-chain metrics like whale wallets, DEX liquidity, and curated social sentiment,” they said. “Most online chatter is noise. A $50 million whale move outweighs a thousand tweets. The AI weights signals based on historical reliability and acts only when they align.”

Advancing With Continuous Performance Optimization

In order to evaluate performance and set realistic expectations, Aurum does several things: “We track ROI, Sharpe ratio, drawdowns, and other risk-adjusted metrics,” the founder explained. “Past performance is never a guarantee. Markets evolve. Any system promising risk-free returns isn’t honest. We’re transparent with users about potential and limits.”

“While we keep the exact architecture proprietary, our team—from Binance, Morgan Stanley, IBM, and OKX—specializes in this level of work,” the founder said. “Models are stress-tested on unseen market conditions. The proof is live performance: bull runs, corrections, sideways markets. They’re not just memorizing patterns—they’re adapting.”

Looking ahead, Aurum’s CEO expects AI-based trading to become ubiquitous for crypto investors. “It’s inevitable,” he said. “Most retail traders lose money manually. DeFi is where it gets exciting—flash loans, layer-2s, deeper DEX liquidity, richer on-chain data. The next frontier? Soft signals—social chatter, governance votes, developer activity. AI that interprets these human signals will have a real edge.”

Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.

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