Your AI agent just became a privileged user

Jasie Fon08-12 02:25

Autonomous action raises a question regulators and auditors will keep coming back to: when an agent takes an action, who is answerable for it? On 3 July, the Monetary Authority of Singapore (MAS) ...

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On 3 July, the Monetary Authority of Singapore (MAS) ...</p>\n\n<a href=\"https://www.theedgesingapore.com/digitaledge/focus/your-ai-agent-just-became-privileged-user?utm_source=Blog&utm_medium=RSS&utm_campaign=Tiger_Brokers_app_RSS\">Source Link</a>\n\n</div>\n","source":"edge_highlight","html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>Your AI agent just became a privileged user</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; }\nul,ol{ margin-left:2em; }\nul{ list-style:disc; }\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nYour AI agent just became a privileged user\n</h2>\n\n<h4 class=\"meta\">\n\n\n2026-08-12 02:25 GMT+8&nbsp;&nbsp;&nbsp;<a href=https://www.theedgesingapore.com/digitaledge/focus/your-ai-agent-just-became-privileged-user?utm_source=Blog&utm_medium=RSS&utm_campaign=Tiger_Brokers_app_RSS><strong>Jasie Fon</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>Autonomous action raises a question regulators and auditors will keep coming back to: when an agent takes an action, who is answerable for it? On 3 July, the Monetary Authority of Singapore (MAS) ...</p>\n\n<a href=\"https://www.theedgesingapore.com/digitaledge/focus/your-ai-agent-just-became-privileged-user?utm_source=Blog&utm_medium=RSS&utm_campaign=Tiger_Brokers_app_RSS\">Source Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","isBrief":false,"type":0,"news_type":1,"symbol":"ARTY","symbol_name":"ISHARES FUTURE AI & TECH ETF","start_time":0,"source_url":"https://www.theedgesingapore.com/digitaledge/focus/your-ai-agent-just-became-privileged-user?utm_source=Blog&utm_medium=RSS&utm_campaign=Tiger_Brokers_app_RSS","article_id":"2658903015","we_media_id":null,"thumbnails":[],"rights":{"source":"edge_highlight","url":"https://www.theedgesingapore.com/digitaledge/focus/your-ai-agent-just-became-privileged-user?utm_source=Blog&utm_medium=RSS&utm_campaign=Tiger_Brokers_app_RSS","rn_cache_url":null,"directOrigin":true},"url":"https://stock-news.laohu8.com/highlight/detail?id=2658903015","pubTimestamp":1786472700,"columns":[],"sourceInfo":{"source_id":"edge_highlight","name":"Edge"},"weMediaInfo":null,"summary":"Autonomous action raises a question regulators and auditors will keep coming back to: when an agent takes an action, who is answerable for it? ","collect":0,"end_time":0,"defaultTopTitle":"theedgesingapore.com","property":[],"viewcount":null,"language":"en","relate_stocks":{"ARTY":"ISHARES FUTURE AI & TECH ETF","BK4585":"ETF&股票定投概念","VTHR":"Vanguard Russell 3000 ETF","LU2413665964.HKD":"BNP PARIBAS AQUA \"C\" (HKD) ACC","LU0170899867.USD":"EASTSPRING INVESTMENTS WORLD VALUE EQUITY  \"A\" (USD) ACC","LU1620156213.USD":"BNP PARIBAS AQUA \"C\" (USD) INC","MAS":"马斯科","LU1165135440.EUR":"BNP Paribas Aqua Classic Cap EUR","BK4086":"建筑产品","LU1721427968.SGD":"BNP PARIBAS AQUA \"CRH\" (SGDHDG) INC","LU2413666004.HKD":"BNP PARIBAS AQUA \"CRH\" (HKDHDG) INC","QTOC":"Innovator Growth Accelerated Plus ETF - October","BK4588":"碎股","LU1596574779.USD":"BNP PARIBAS AQUA \"C\" (USDHDG) ACC","AIPO":"Defiance AI and Power Infrastructure ETF","LU1543694498.USD":"法巴水资源基金RH MD Dis","CHAT":"ROUNDHILL GENERATIVE AI & TECHNOLOGY ETF","AGIX":"通用人工智能 ETF-AGIX","SG9999001440.SGD":"United Global Dividend Equity Fund A SGD Dist","LU1620156130.USD":"BNP PARIBAS AQUA \"C\" (USD) ACC"},"translate_title":"您的人工智能代理刚刚成为特权用户","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"ARTY":1.5,"QTOC":1.5,"MAS":1,"CHAT":1.5,"AGIX":1.5,"VTHR":1.5,"AIPO":1.5},"content_text":"Autonomous action raises a question regulators and auditors will keep coming back to: when an agent takes an action, who is answerable for it? On 3 July, the Monetary Authority of Singapore (MAS) published a new industry white paper, Safeguards for Agentic Finance at Runtime (SAFR), developed with financial institutions and fintechs under its BuildFin.ai initiative. The paper builds on the AI Risk Management toolkit that emerged from Project MindForge's second phase, and it moves the conversation from how banks should govern AI models to how they should control what AI agents actually do once they are given a task and deployed to execute it.\nMAS is careful to note that this is not regulation. It's an industry reference model, not a mandate. But the direction it points to is unmistakable. AI agents that can initiate payments, submit trading orders, approve credit applications or file regulatory reports are being treated as a distinct risk category, one that needs checkpoints before action is taken, not just review after the fact. For banking, risk and technology leaders, that distinction matters more than the paper's non-binding status suggests.\nAgents don't fit the boxes we already built\nMost access control in a bank falls into one of two buckets. Human identity governance handles employees, with role-based permissions, manager approval chains and periodic access reviews built around the assumption that a person is making each decision. Machine identity governance handles service accounts and API keys, built around the assumption that behaviour is fixed and predictable once configured.\nAn AI agent fits neither. It acts without a human in the loop, which rules out the human model. But its behaviour also isn't static. An agent can be re-prompted, can chain tasks together in ways nobody explicitly configured, and can end up requesting access to systems or data that were never anticipated when it was first provisioned. Treating an agent like a service account and granting it a fixed set of permissions ignores the fact that what the agent decides to do next is not fully predictable in the way a scheduled batch job is.\nThe result is a governance gap. Agents are commonly provisioned with far broader access than any single task requires, because it's operationally simpler than granting and revoking permissions dynamically. That gap is exactly what MAS's paper is trying to close, by pushing institutions toward validating and logging what an agent proposes to do at the point of action, rather than relying solely on upfront provisioning.\nAccountability gets harder before it gets easier\nAutonomous action raises a question regulators and auditors will keep coming back to: when an agent takes an action, who is answerable for it? The developer who built it, the business unit that deployed it, or the institution that approved its use? Existing audit trails were designed around human decisions and system logs of fixed processes. They were not designed to capture a chain of agent reasoning, tool calls and sub-decisions that might unfold in seconds across multiple systems.\nThis is not a hypothetical compliance problem. Regulators reviewing an incident will ask for a record of what the agent was authorised to do, what it actually did, and where the two diverged. Institutions that cannot produce that record quickly will struggle to demonstrate control, regardless of how sophisticated their underlying models are. Auditability of agent behaviour must be built into the infrastructure agents run on, not bolted on after deployment.\nWhat this means for CISOs and risk leaders\nMAS's paper effectively hands chief information security officers (CISOs) and risk leaders a checklist for something the finance sector has not yet operationalised at scale: authorisation that happens in real time, validation of an agent's proposed action against defined policy boundaries before it executes, and logging detailed enough to reconstruct decisions after the fact.\nThat is a different discipline from model governance, which focuses on training data, bias testing and output quality. It sits closer to identity and access management, because the underlying question is not whether a model is accurate, but whether an actor is authorised to take a specific action, at a specific moment, within a defined scope. Institutions that keep agentic AI oversight solely inside the model risk or data science function are likely to find they have built the wrong kind of control for the risk in front of them.\nTreat agents as privileged identities, starting now\nThe institutions best placed to meet MAS's direction, and whatever follows it, will be the ones that stop treating agents as extensions of the applications they run inside and start treating them as identities in their own right, subject to the same discipline applied to humans with elevated access. That means individual authorisation scoped to a task, time-bound permissions rather than standing access, and continuous logging rather than periodic review. This is a bigger shift than adding a new line item to an existing IAM programme. It asks institutions to rethink identity governance for an actor that doesn't behave like a person or a fixed system.\nMAS has signalled where financial regulation is heading on this question. Institutions that build the identity controls now, rather than waiting for a rule that requires it, will spend far less time retrofitting when that rule arrives.\nJasie Fon is the regional vice president for Asia at Ping Identity","kind":"highlight","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":false,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":0,"need_auth":false,"need_login_tip":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)","isDev":false,"isTTM":true,"isLaohu8Offline":false,"tenantId":"TBGLOBAL","deviceId":"web-server-community-laohu8-v3","version":"4.47.1","shortVersion":"4.47.1","platform":"web","vendor":"web","appName":"ttm","isIOS":false,"isAndroid":false,"isTiger":false,"isTHS":false,"isWeiXin":false,"isWeiXinMini":false,"isWeiBo":false,"isQQ":false,"isBaiduSwan":false,"isBaiduBox":false,"isDingTalk":false,"isToutiao":false,"isOnePlus":false,"isHuaWei":false,"isXiaomi":false,"isXiaomiWebView":false,"isOppo":false,"isVivo":false,"isSamsung":false,"isMobile":false},"href":"/m/news/2658903015","isCrawlerRequest":true}