Stackorithm, a trader intelligence and risk technology company built for proprietary trading firms, has received two honors at the FinanceFeeds Awards 2026, winning “Outstanding Risk Management for Proprietary Trading Firms” and “Exceptional Technology and Infrastructure for Proprietary Trading.”
The double recognition highlights Stackorithm’s approach to one of the more difficult challenges facing modern proprietary trading firms: understanding how traders behave as their businesses grow and making sure risk teams have enough information to act before potentially costly problems develop.
Rather than looking only at account balances, profits, losses or individual rule breaches, Stackorithm’s Trader Risk Analysis platform continuously analyzes trader behavior and identifies patterns that may warrant further investigation. These can include copy trading, hedging, gambling-style activity and other forms of toxic trading behavior. Each detection is supported by trade-level evidence, allowing risk teams to examine the specific activity behind a risk signal instead of working from an unexplained score or alert. Stackorithm publicly describes its approach as behavioral intelligence supported by trade-level evidence.
This becomes particularly important as proprietary trading firms expand their trader bases. Reviewing large volumes of accounts manually can quickly become difficult, while simple rules-based systems can leave risk teams working through large numbers of alerts without enough context. Stackorithm brings behavioral detection, evidence and trader risk information together in one environment, giving teams a more structured way to review cases and prioritize those that need closer attention.
When an investigation needs to go beyond the trades themselves, supporting account information such as IP and device fingerprints can help risk teams identify potential relationships between different accounts or users. Combined with trade-level analysis, this gives firms a broader view of trader activity and can make complex cross-account investigations easier to manage.
What the Awards Mean
The Outstanding Risk Management for Proprietary Trading Firms award speaks to one of the hardest parts of running a prop firm today: figuring out who is actually trading well and who is simply exploiting the rules. As firms grow, risk teams are no longer reviewing a small pool of accounts by hand. They are dealing with thousands of traders, overlapping strategies, copied behavior, hedging between accounts, and patterns that can look profitable on the surface while creating very different risk underneath.
That has made behavioral analysis much more important than basic account metrics. A trader can stay within drawdown limits and still create problems through coordinated activity, gambling-style execution, or activity spread across several accounts. Recognition in this category is really about the tools that help firms look past the headline P&L and understand how that P&L was produced, with enough trade-level evidence to investigate the behavior properly.
The Exceptional Technology and Infrastructure for Proprietary Trading award looks at the other side of the same problem. Prop firms have scaled quickly, but their internal systems have had to catch up just as fast. Risk data, account activity, device information, execution records, and investigation workflows can easily end up scattered across different dashboards and spreadsheets. The stronger technology providers are the ones bringing those pieces together so risk teams can work from one clear view instead of chasing data across multiple systems.
That matters because technology in prop trading is no longer just about faster onboarding or a polished trader dashboard. The real test is whether the infrastructure can handle a growing trader base without creating more manual work for the firm behind it. These two awards together reflect where the sector is heading: fewer gut-feel decisions, less spreadsheet policing, and much more attention to trader behavior, evidence, and scalable internal controls.
Continuous analysis can also move the risk process earlier in the trader lifecycle. Potential patterns can be surfaced as they develop rather than being discovered only during a later payout review or manual account investigation. Stackorithm describes this continuous, evidence-based model as a way for prop-firm risk teams to work from shared detections, trade evidence and case information.
Technology Built Around the Risk Team
Winning the technology and infrastructure award alongside the risk management title is particularly relevant for Stackorithm because the two areas are closely connected. Strong risk policies become harder to apply consistently without technology capable of supporting them at scale. At the same time, sophisticated technology has limited value if it does not provide risk teams with evidence they can understand and use.
“Receiving both the Outstanding Risk Management for Proprietary Trading Firms and Exceptional Technology and Infrastructure for Proprietary Trading awards is an important recognition of what we are building at Stackorithm,” said Diki, Co-Founder at Stackorithm. “Prop firms are dealing with more traders, more data and increasingly complex patterns of activity. Our focus is on giving risk teams clear evidence and useful intelligence so they can understand what is happening across their trader base and make better-informed decisions.”
Giving Risk Teams More Context
One of the central ideas behind Trader Risk Analysis is that a detection should be the beginning of an investigation rather than the conclusion.
A behavioral pattern such as suspected copy trading, for example, may require a reviewer to understand which trades triggered the detection, how closely activity between accounts is related and whether other account information supports that connection. By bringing relevant evidence into the same workflow, Stackorithm helps risk managers move from an initial signal toward a more informed assessment.
The same approach applies to hedging patterns, gambling-style behavior and other potentially problematic activity. Instead of treating all unusual behavior in the same way, the platform provides evidence that allows teams to examine the circumstances surrounding each case.
“The two FinanceFeeds Awards recognize different parts of the same challenge. Proprietary trading firms need stronger ways to identify risk, but they also need the technology infrastructure to investigate that risk consistently as their businesses expand. Stackorithm’s approach is centered on turning trader behavior into usable intelligence. Through continuous analysis, trade-level evidence and supporting account insights, the company is building tools intended to help risk teams identify issues earlier, conduct investigations more efficiently and develop a more structured process for managing trader risk at scale,” added FinanceFeeds EIC Nikolai Isayev.