{"id":34917,"date":"2026-05-27T14:25:59","date_gmt":"2026-05-27T06:25:59","guid":{"rendered":"https:\/\/aiportek.com\/?p=34917"},"modified":"2026-05-27T14:26:04","modified_gmt":"2026-05-27T06:26:04","slug":"redis-graph-database-bank-aml-regtech","status":"publish","type":"post","link":"https:\/\/aiportek.com\/en\/redis-graph-database-bank-aml-regtech\/","title":{"rendered":"Redis + Graph Database: Bank AML and Anti-fraud Real-Time Risk Control Architecture"},"content":{"rendered":"<div data-elementor-type=\"wp-post\" data-elementor-id=\"34917\" class=\"elementor elementor-34917\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-303a47ec elementor-section-stretched elementor-section-full_width elementor-section-height-min-height elementor-section-content-middle elementor-section-height-default elementor-section-items-middle\" data-id=\"303a47ec\" data-element_type=\"section\" data-settings=\"{&quot;stretch_section&quot;:&quot;section-stretched&quot;,&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-27d5e225\" data-id=\"27d5e225\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-4e369ae3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4e369ae3\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-inner-column elementor-element elementor-element-6555484e\" data-id=\"6555484e\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-397ef20e elementor-widget elementor-widget-heading\" data-id=\"397ef20e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Hongke's latest articles<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<div class=\"elementor-element elementor-element-4b5c0d9b elementor-absolute elementor-widget elementor-widget-heading\" data-id=\"4b5c0d9b\" data-element_type=\"widget\" data-settings=\"{&quot;_position&quot;:&quot;absolute&quot;}\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">HongKe<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-6d18033c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6d18033c\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1f96cecf\" data-id=\"1f96cecf\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d303089 elementor-widget elementor-widget-text-editor\" data-id=\"d303089\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Lorem ipsum dolor sit amet, consectetur adipiscing elit. 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class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Redis + Graph Database: The best division of labor: real-time scoring to Redis, correlation analysis to Graph?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-226f412 elementor-widget elementor-widget-post-info\" data-id=\"226f412\" data-element_type=\"widget\" data-widget_type=\"post-info.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-inline-items elementor-icon-list-items elementor-post-info\">\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item elementor-repeater-item-2358f4d elementor-inline-item\" itemprop=\"author\">\n\t\t\t\t\t\t<a href=\"https:\/\/aiportek.com\/en\/author\/hongketechnology\/\">\n\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-far-user-circle\" viewbox=\"0 0 496 512\" 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data-docx-has-block-data=\"false\"><div class=\"ace-line ace-line old-record-id-OH24dKqd0o2dKExvGWecyiusnuh\">Many banks are torn between the need to be fast in the moment and the need to look deeper in the aftermath of a transaction when doing AML and fraud. redis and graph databases aren't really one or the other, but rather the most natural combination of tasks: the former is for real-time scoring and the latter is for correlation insights. hkma in its aml\/cft regtech guidelines clearly states that banks need to Integrate <strong>multi-source data<\/strong> and <strong>network analytics<\/strong> To identify behavioral patterns and correlation risks, these two needs correspond to very different technical characteristics - millisecond responses for transactional decisions and multi-hop correlation queries for investigative analysis.<\/div><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9aba933 elementor-widget elementor-widget-heading\" data-id=\"9aba933\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">01. Introduction: The two speeds of counterfeiting and AML determine the technical division of labor<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-853e9ed elementor-widget elementor-widget-image\" data-id=\"853e9ed\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"683\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-1024x683.jpeg\" class=\"attachment-large size-large wp-image-34451\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-1024x683.jpeg 1024w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-300x200.jpeg 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-768x512.jpeg 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-1536x1024.jpeg 1536w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-2048x1366.jpeg 2048w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-18x12.jpeg 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-600x400.jpeg 600w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d3381e7 elementor-widget elementor-widget-text-editor\" data-id=\"d3381e7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div data-page-id=\"CrVId1JAwoKvX2xe4HVcwX2CnSW\" data-lark-html-role=\"root\" data-docx-has-block-data=\"false\"><div class=\"ace-line ace-line old-record-id-I7ucd5nyioza0XxnBUac4jGenFg\">There are two distinct time scales for counter-fraud and AML decisions:<\/div><ul class=\"list-bullet1\"><li class=\"ace-line ace-line old-record-id-Om60dxSWdokk1lxaBlacIWtAnFe\" data-list=\"bullet\"><div><strong>Transaction Decision Making (milliseconds):<\/strong> FPS RTGS, virtual banking API authorization, digital wallet top-ups - these are all scenarios where risk judgment must be completed before the transaction is released, or the most accurate model will not be able to intercept it. HKMA's TM-E-1 guidelines require banks to implement a risk-based approach to high-risk transactions. <strong>real-time monitoring<\/strong>The customer will be notified of the suspicious activity as soon as it occurs.<\/div><\/li><li class=\"ace-line ace-line old-record-id-BBisdohNMoK91cxyyTCcSAaYn2d\" data-list=\"bullet\"><div><strong>Survey Analysis (minute to hour level):<\/strong> After a suspicious transaction is detected, it is necessary to track account relationships, fund flows, device networks, merchant relationships and group patterns, and this kind of multi-hops relationship query often takes tens of seconds or even minutes in traditional RDBMS.<\/div><\/li><\/ul><div class=\"ace-line ace-line old-record-id-TcIQdS40koKyIXxw9y2c0LFvnsg\"><strong>Neither Redis nor Graph alone is complete:<\/strong> Redis specializes in high-consolidation real-time reads and writes, but is not suitable for complex graph traversal; Graph databases specialize in correlation analysis, but the query latency is not sufficient for transactional decision-making. The optimal division of labor is <strong>Redis for real-time scoring and popular features layer, ArangoDB for association mapping and partnership analysis.<\/strong>The two complement each other through event streams or APIs to form a complete RegTech architecture.<\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c0546d0 elementor-widget elementor-widget-heading\" data-id=\"c0546d0\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">02. Three Core Values: How Redis + ArangoDB Built a Complete RegTech Defense<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f9ee543 elementor-widget elementor-widget-heading\" data-id=\"f9ee543\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">Value 1: Redis takes on pre-trade decision making, millisecond risk scoring<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a761ec3 elementor-widget elementor-widget-text-editor\" data-id=\"a761ec3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div data-page-id=\"CrVId1JAwoKvX2xe4HVcwX2CnSW\" data-lark-html-role=\"root\" data-docx-has-block-data=\"false\"><div class=\"ace-line ace-line old-record-id-MD0ZdOJBnobuIbxurj6cias4nch\"><strong>Pain Points:<\/strong> In an FPS real-time transfer scenario, where the transaction authorization time window is only a few hundred milliseconds, any data query that exceeds 100ms becomes a bottleneck; traditional database queries are more likely to time out during peak hours, resulting in degradation of the release.<\/div><div class=\"ace-line ace-line old-record-id-Z1qEdTtehowVKnxKkDUcw7oUn1e\"><strong>Redis response:<\/strong> Redis as <strong>online scoring layer<\/strong>In addition to the above, the system also takes on recent transaction characteristics, device risk, black and white list comparison, velocity metrics and real-time customer risk scores; maintains transaction counts within the time window with Sorted Sets, black list comparison with Cuckoo Filters, and stores session context with Hash, and the response time of all operations is less than 1.5 seconds. <strong>sub-1ms<\/strong>The<\/div><div class=\"ace-line ace-line old-record-id-B9jodFyiRoCtXdxNCTPc9bjnn1e\"><strong>ArangoDB's division of labor:<\/strong> When the Redis score triggers the \"medium-high risk\" threshold, transaction events are written to the event stream, triggering ArangoDB's correlation analysis process; Redis is not tasked with in-depth investigations and remains focused on real-time decision making.<\/div><div class=\"ace-line ace-line old-record-id-HRjIdZTQuokWIbxHIo2cgS4dnUd\"><strong>The effectiveness of the campaign:<\/strong> The official Redis case study shows that credit card organizations around the world are backed by Redis every second. <strong>700,000<\/strong> Real-time scoring of transactions, inference speed enhancement <strong>60 times<\/strong>The company is also committed to ensuring that scores are always ahead of trade releases.<\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cc549d9 elementor-widget elementor-widget-heading\" data-id=\"cc549d9\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">Value 2: ArangoDB for deep correlation, Redis for caching heatmap results<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eb06299 elementor-widget elementor-widget-text-editor\" data-id=\"eb06299\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div data-page-id=\"WpsfdxhNToS4KtxinlycnzfUnuC\" data-lark-html-role=\"root\" data-docx-has-block-data=\"true\"><div class=\"ace-line ace-line old-record-id-JCI4dQN9ho8KFxxC1zwcO9TsnXb\"><strong>Response: Purchasing Checklist (8 items)<\/strong> Each of the items in the table below corresponds to \"what the board will ask\" and \"what the HKMA\/Internal Controls will look for,\" which you can take directly to the RFP and score sheet.<\/div><div class=\"old-record-id-TxWMdOKH6oeXzRxh4NycQpaknEe\" data-type=\"sheet\"><div data-page-id=\"CrVId1JAwoKvX2xe4HVcwX2CnSW\" data-lark-html-role=\"root\" data-docx-has-block-data=\"false\"><div class=\"ace-line ace-line old-record-id-AAmCdzS7Fo3SQ6xwKW6cTePwnze\"><strong>Pain Points:<\/strong> AML investigations often need to answer the question of \"how many associates are behind this account, where did the funds go, and which merchants did they interact with?\" Traditional SQL requires complex JOIN or recursive queries with query times ranging from seconds to minutes, which is not able to satisfy the timeliness requirements of regulatory reports or account freezes.<\/div><div class=\"ace-line ace-line old-record-id-PVVydmbGeovJGixUbCDcPvhjnEf\"><strong>ArangoDB response:<\/strong> ArangoDB's AQL (ArangoDB Query Language) graph traversal enables multi-hop correlation analysis in a single query, e.g., \"Find all associated accounts, devices, IPs, merchants, and money flows within 3 hops of a suspicious account\"; ArangoDB Official Fraud Detection Example The official ArangoDB fraud detection case shows that graph ML can identify patterns of collusion that cannot be detected by traditional rules.<\/div><div class=\"ace-line ace-line old-record-id-Hw8YdidKnosbv6xjMLMcNsNbneb\"><strong>Redis division of labor:<\/strong> ArangoDB analyzes the \"high-risk association groups\" and \"hot graph query results\" and caches them to Redis, so that the predicted association risk scores can be read directly when making real-time decisions, avoiding the need to repeatedly execute graph queries during peak trading hours.<\/div><div class=\"ace-line ace-line old-record-id-LTykdYr0hoWYb5xCsNcc29Henhd\"><strong>The effectiveness of the campaign:<\/strong> The application of ArangoDB in financial fraud detection can reduce the correlation query time from <strong>Compression from tens of seconds to hundreds of milliseconds<\/strong>It also improves the accuracy of the model in detecting new forms of money laundering behavior through graph embeddings.<\/div><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fcd2a62 elementor-widget elementor-widget-heading\" data-id=\"fcd2a62\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">Value #3: Add Decisions platform to automate high-risk investigation processes<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-845e4af elementor-widget elementor-widget-text-editor\" data-id=\"845e4af\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div data-page-id=\"WpsfdxhNToS4KtxinlycnzfUnuC\" data-lark-html-role=\"root\" data-docx-has-block-data=\"true\"><div class=\"ace-line ace-line old-record-id-UNsIdrf5xoHWZUx6EwscgL4gnFB\"><strong>Pain Points<\/strong> Open Source may seem cheap, but the bank's \"cheapness\" is often eaten up by three things: shift labor, incident time, and compliance evidence costs. Conversely, Enterprise may seem expensive, but if it takes your SEV1 recovery time from hours to minutes a few times a year, reduces your upgrade failure rate, and automates your audit evidence, the TCO may be even lower.<\/div><div>\u00a0<\/div><div class=\"ace-line ace-line old-record-id-GP7qdtYVvosXYAx1XZicyHh9nVT\"><strong>Response: 3-year TCO Demonstration Model (can be changed directly to your numbers)<\/strong> The following are \"sample scenarios\" that you can replace with your host count, data volume, region count, and SLO goals:<\/div><ul class=\"list-bullet1\"><li class=\"ace-line ace-line old-record-id-LNVLdYbt5oTP9MxZsm3cmXtgn7c\" data-list=\"bullet\"><div>Scope: 6 production clusters (with different business domains), each with 3 masters and 3 slaves across 2 AZs; 2 major version upgrades and 12 minor version\/configuration changes per year.<\/div><\/li><li class=\"ace-line ace-line old-record-id-TVcJdzgfDoMBo7xwy0cc9SQKnYf\" data-list=\"bullet\"><div>Team: 2 SREs (shift), 1 Platform Engineer, 0.5 Safety\/Compliance Support (input ratio).<\/div><\/li><li class=\"ace-line ace-line old-record-id-Z5t0dIJ3VoOUXOxJSRuc72oanzf\" data-list=\"bullet\"><div>Incident: 2 SEV1s per year (with spike jitter\/failover\/upgrade rollback) with an average of 6 hours of cross-departmental input each time (conservative estimate).<\/div><\/li><\/ul><div class=\"old-record-id-SM5TdbboNoqSNBxEdK5cMEvjnlh\" data-type=\"sheet\"><div data-page-id=\"CrVId1JAwoKvX2xe4HVcwX2CnSW\" data-lark-html-role=\"root\" data-docx-has-block-data=\"false\"><div class=\"ace-line ace-line old-record-id-IHbNdOSQooqQhkxcJD9cvBwLntD\"><strong>Pain Points:<\/strong> Even with good scoring and correlation analysis, the last mile - the \"follow-up of high-risk transactions\" - is often stuck in a bottleneck of manual reviews: notifying the customer, freezing the account, filing a SAR (Suspicious Activity Report), and launching an internal investigation, each requiring cross-departmental coordination. Each step of the process requires cross-departmental coordination, and delays can easily result in regulatory fines or capital outflows.<\/div><div class=\"ace-line ace-line old-record-id-JDNddhIQ4omlpXxlQsvcfrC9nuc\"><strong>The response of the complete framework:<\/strong><\/div><ul class=\"list-bullet1\"><li class=\"ace-line ace-line old-record-id-LTg6dykxwoKAPexfAPkcLs4dnvc\" data-list=\"bullet\"><div><strong>Redis<\/strong>: Score immediately before trading \u2192 Mark \"High Risk\".<\/div><\/li><li class=\"ace-line ace-line old-record-id-Qmr6deCoSoljdyxNNI1cO3qonRf\" data-list=\"bullet\"><div><strong>ArangoDB<\/strong>: Trigger correlation analysis \u2192 Generate survey maps<\/div><\/li><li class=\"ace-line ace-line old-record-id-FDGWdMUWLoGlNLx3MvycPKLNngb\" data-list=\"bullet\"><div><strong>Decisions<\/strong>Automatic scheduling of follow-up processes, including customer notifications (SMS\/Email), account freezes, SAR auto-generation, and survey assignments to AML teams.<\/div><\/li><\/ul><div class=\"ace-line ace-line old-record-id-O9LFddMiMoWffaxsklEcuGEwnbg\"><strong>The effectiveness of the campaign:<\/strong> This automated process allows high-risk transactions to be minimized. <strong>Compressed end-to-end processing time from hours to minutes<\/strong>It meets the HKMA's requirements for \"real-time monitoring and rapid response\" while significantly reducing labor costs and operational risks.<\/div><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-302cdab elementor-widget elementor-widget-heading\" data-id=\"302cdab\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">Customer Testimonial: RegTech Transformation at an Asian Bank<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c5c631 elementor-widget elementor-widget-text-editor\" data-id=\"3c5c631\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div data-page-id=\"CrVId1JAwoKvX2xe4HVcwX2CnSW\" data-lark-html-role=\"root\" data-docx-has-block-data=\"false\"><div class=\"ace-line ace-line old-record-id-MlV3dumWkoxUd7xvNQKcLcc5nUc\"><strong>Background:<\/strong> A large commercial bank in Asia, facing peak FPS traffic (tens of thousands of transactions per second) and increasingly stringent AML regulatory pressure, the traditional risk control system was experiencing bottlenecks in both real-time decision-making and in-depth investigation.<\/div><div class=\"ace-line ace-line old-record-id-ZUOBdHzPHonELIxR1qEcTbz0nxh\"><strong>Challenge:<\/strong> During peak trading hours, the fraud scoring latency often exceeded 200ms, resulting in some high-risk transactions being downgraded and released; the AML team's investigation was inefficient, as it took several hours to analyze the association of a suspicious account, and it was even more time-consuming to manually write a SAR report.<\/div><div class=\"ace-line ace-line old-record-id-FFjgdrFvDoTCpQxaN0vcGYnxnRe\"><strong>Redis + ArangoDB + Decisions driven transformation:<\/strong><\/div><ol class=\"list-number1\" start=\"1\"><li class=\"ace-line ace-line old-record-id-AdwodGTTho2rjkxud39cfSWTnje\" data-list=\"number\"><div><strong>Phase 1 (Redis Instant Layer):<\/strong> Centralize the hot features and risk scores required for pre-transaction decision making into Redis to ensure that FPS transactions are sub-100ms scored before authorization; blacklists and velocity checks are all in-memory.<\/div><\/li><li class=\"ace-line ace-line old-record-id-CnmcdYll4o6twhxXdiNcZ1Bmnxc\" data-list=\"number\"><div><strong>Phase 2 (ArangoDB Associative Layer):<\/strong> High-risk transactions trigger ArangoDB's graph analytics, automatically generating reports on account networks, money flow mapping, and group identification; AQL queries compress multi-hop correlation times from tens of seconds to hundreds of milliseconds.<\/div><\/li><li class=\"ace-line ace-line old-record-id-N7CVd5e9yoreGIxpFtScBCqynie\" data-list=\"number\"><div><strong>Stage 3 (Decisions process level):<\/strong> Automate follow-up with the Decisions platform: real-time customer notifications, account freezes, automatic SAR generation and assignment of investigative tasks; the entire process takes less than 5 minutes from trigger to completion.<\/div><\/li><\/ol><div class=\"ace-line ace-line old-record-id-QSsAdRpjwo41buxeVUoclDc3naf\"><strong>Transformation results:<\/strong> Pre-transaction Intercept Rate Increase <strong>35%<\/strong>AML investigates efficiency gains <strong>4 times<\/strong>The potential loss and penalty costs avoided each year are more than $10,000 per year. <strong>Tens of millions of dollars.<\/strong>The auditability of the framework is also fully compliant with HKMA Regtech requirements.<\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-548c287 elementor-widget elementor-widget-image\" data-id=\"548c287\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1024\" height=\"544\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1.png\" class=\"attachment-large size-large wp-image-34919\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1.png 1024w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-300x159.png 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-768x408.png 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-18x10.png 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-600x319.png 600w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-214b8c8 elementor-widget elementor-widget-heading\" data-id=\"214b8c8\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-small\">Conclusion: Act Now to Launch the Blueprint Presentation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7498895 elementor-widget elementor-widget-text-editor\" data-id=\"7498895\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div data-page-id=\"CrVId1JAwoKvX2xe4HVcwX2CnSW\" data-lark-html-role=\"root\" data-docx-has-block-data=\"false\"><div class=\"ace-line ace-line old-record-id-RicMdXwG1oqeBtxYo7acDDKBn6d\">As HKMA continues to promote AML\/CFT Regtech and network analytics, it is no longer possible to rely on a rules engine or a single database to meet the dual demands of real-time decision making and deep correlation. the Redis + ArangoDB + Decisions division of labor architecture is not a theoretical concept, but a field-tested and proven RegTech. It is a tried and tested RegTech blueprint:<strong>Redis guarantees that transactions will not be missed, ArangoDB guarantees that investigations will not be missed, and Decisions guarantees that the process will not be interrupted.<\/strong>The<\/div><div class=\"ace-line ace-line old-record-id-LN0VdbJ7FozCFhx4On3cT7hnnac\"><strong>You have only two choices:<\/strong><\/div><ol class=\"list-number1\" start=\"1\"><li class=\"ace-line ace-line old-record-id-PObxdxMLDohMzpxkeVsc4avYnPe\" data-list=\"number\"><div><strong>Passive waiting:<\/strong> Continue to use traditional structures to meet increasingly stringent regulatory requirements and wait until the next AML trial or fraud comes to light to remedy the situation.<\/div><\/li><li class=\"ace-line ace-line old-record-id-B2uLdBj01oCOrVxOJtDcuW7Ynkg\" data-list=\"number\"><div><strong>Active Defense:<\/strong> Let's take a position. <strong>Blueprint Presentation<\/strong>In addition, the program spends 60 minutes answering three key questions:<\/div><ol class=\"list-number2\"><li class=\"ace-line ace-line old-record-id-AAXoddaCWo1xvrxh0hBcJPoXnlg\" data-list=\"bullet\"><div>How many milliseconds is your pre-trade risk rating delay?<\/div><\/li><li class=\"ace-line ace-line old-record-id-Ws3NdS3LroraWkxexZ0c9oTWnuf\" data-list=\"bullet\"><div>How long does it take to analyze the association of a suspicious account?<\/div><\/li><li class=\"ace-line ace-line old-record-id-XG3PdHximo3Aj8x6pykc6DCknMh\" data-list=\"bullet\"><div>Has the post-processing of high-risk transactions been automated?<\/div><\/li><\/ol><\/li><\/ol><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-45ed7c8 elementor-widget elementor-widget-button\" data-id=\"45ed7c8\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/aiportek.com\/redis-enterprise-database\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Go to the Redis Product Page<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t<div class=\"elementor-element elementor-element-cfcf4de e-flex e-con-boxed e-con e-parent\" data-id=\"cfcf4de\" data-element_type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-dbc1b58 elementor-widget elementor-widget-heading\" data-id=\"dbc1b58\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-xl\">Other Articles<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-74adc8f elementor-posts--align-left elementor-grid-3 elementor-grid-tablet-2 elementor-grid-mobile-1 elementor-posts--thumbnail-top elementor-card-shadow-yes elementor-posts__hover-gradient elementor-widget elementor-widget-posts\" data-id=\"74adc8f\" data-element_type=\"widget\" data-settings=\"{&quot;cards_row_gap&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:100,&quot;sizes&quot;:[]},&quot;cards_columns&quot;:&quot;3&quot;,&quot;cards_columns_tablet&quot;:&quot;2&quot;,&quot;cards_columns_mobile&quot;:&quot;1&quot;,&quot;cards_row_gap_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;cards_row_gap_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]}}\" data-widget_type=\"posts.cards\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-posts-container elementor-posts elementor-posts--skin-cards elementor-grid\" role=\"list\">\n\t\t\t\t<article class=\"elementor-post elementor-grid-item post-34998 post type-post status-publish format-standard has-post-thumbnail hentry category-18 tag-redis tag-36\" role=\"listitem\">\n\t\t\t<div class=\"elementor-post__card\">\n\t\t\t\t<a class=\"elementor-post__thumbnail__link\" href=\"https:\/\/aiportek.com\/en\/redis-aigc-feed-optimization\/\" tabindex=\"-1\" target=\"_blank\"><div class=\"elementor-post__thumbnail\"><img decoding=\"async\" width=\"1024\" height=\"544\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1.png\" class=\"attachment-full size-full wp-image-34919\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1.png 1024w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-300x159.png 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-768x408.png 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-18x10.png 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-600x319.png 600w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/div><\/a>\n\t\t\t\t<div class=\"elementor-post__badge\">Hongke Case<\/div>\n\t\t\t\t<div class=\"elementor-post__text\">\n\t\t\t\t<h3 class=\"elementor-post__title\">\n\t\t\t<a href=\"https:\/\/aiportek.com\/en\/redis-aigc-feed-optimization\/\" target=\"&quot;_blank&quot;\">\n\t\t\t\tRainbow Solutions] Ali's Thousand Questions: How Redis Stream can tame tens of millions of streams in milliseconds?\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t<div class=\"elementor-post__excerpt\">\n\t\t\t<p>AIGC has spawned a huge amount of information and news, and it is difficult for traditional message queues to support the high concurrency of tens of millions of information streams. This article explains how to combine Bloom Filter, Consumer Groups, and Vector Retrieval with Redis Stream to realize milliseconds content de-weighting, priority distribution, and real-time recommendation, which can solve the problems of feed stream delay and content homogenization.<\/p>\n\t\t<\/div>\n\t\t\n\t\t<a class=\"elementor-post__read-more\" href=\"https:\/\/aiportek.com\/en\/redis-aigc-feed-optimization\/\" aria-label=\"Read more about How Redis Stream can tame tens of millions of information streams in milliseconds?\" tabindex=\"-1\" target=\"_blank\">\n\t\t\tRead more\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-post__meta-data\">\n\t\t\t\t\t<span class=\"elementor-post-author\">\n\t\t\tHongKeTechnology\t\t<\/span>\n\t\t\t\t<span class=\"elementor-post-date\">\n\t\t\tMay 28, 2026\t\t<\/span>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/article>\n\t\t\t\t<article class=\"elementor-post elementor-grid-item post-34917 post type-post status-publish format-standard has-post-thumbnail hentry category-12 tag-redis tag-36\" role=\"listitem\">\n\t\t\t<div class=\"elementor-post__card\">\n\t\t\t\t<a class=\"elementor-post__thumbnail__link\" href=\"https:\/\/aiportek.com\/en\/redis-graph-database-bank-aml-regtech\/\" tabindex=\"-1\" target=\"_blank\"><div class=\"elementor-post__thumbnail\"><img decoding=\"async\" width=\"1024\" height=\"544\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1.png\" class=\"attachment-full size-full wp-image-34919\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1.png 1024w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-300x159.png 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-768x408.png 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-18x10.png 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/05\/72bc546a-0851-480a-a589-1f4ed5a5bc0b-1024x544-1-600x319.png 600w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/div><\/a>\n\t\t\t\t<div class=\"elementor-post__badge\">Hongke Dry Goods<\/div>\n\t\t\t\t<div class=\"elementor-post__text\">\n\t\t\t\t<h3 class=\"elementor-post__title\">\n\t\t\t<a href=\"https:\/\/aiportek.com\/en\/redis-graph-database-bank-aml-regtech\/\" target=\"&quot;_blank&quot;\">\n\t\t\t\tRedis + Graph Database: Bank AML and Anti-fraud Real-Time Risk Control Architecture\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t<div class=\"elementor-post__excerpt\">\n\t\t\t<p>Banks dealing with AML and anti-fraud often face the tension between real-time decision-making and in-depth investigation. In this paper, we analyze how Redis (real-time scoring) and ArangoDB (graph database correlation analysis) can be perfectly divided into different roles and combined with Decisions to automate the process to meet the HKMA compliance guidelines and create a millisecond RegTech defense.<\/p>\n\t\t<\/div>\n\t\t\n\t\t<a class=\"elementor-post__read-more\" href=\"https:\/\/aiportek.com\/en\/redis-graph-database-bank-aml-regtech\/\" aria-label=\"Read more about Redis + Graph Database: Bank AML and Anti-fraud Real-time Risk Control Architecture\" tabindex=\"-1\" target=\"_blank\">\n\t\t\tRead more\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-post__meta-data\">\n\t\t\t\t\t<span class=\"elementor-post-author\">\n\t\t\tHongKeTechnology\t\t<\/span>\n\t\t\t\t<span class=\"elementor-post-date\">\n\t\t\tMay 27, 2026\t\t<\/span>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/article>\n\t\t\t\t<article class=\"elementor-post elementor-grid-item post-34445 post type-post status-publish format-standard has-post-thumbnail hentry category-12 tag-redis tag-36\" role=\"listitem\">\n\t\t\t<div class=\"elementor-post__card\">\n\t\t\t\t<a class=\"elementor-post__thumbnail__link\" href=\"https:\/\/aiportek.com\/en\/redis-finance\/\" tabindex=\"-1\" target=\"_blank\"><div class=\"elementor-post__thumbnail\"><img loading=\"lazy\" decoding=\"async\" width=\"2560\" height=\"1707\" src=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d.jpeg\" class=\"attachment-full size-full wp-image-34451\" alt=\"\" srcset=\"https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d.jpeg 2560w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-300x200.jpeg 300w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-1024x683.jpeg 1024w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-768x512.jpeg 768w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-1536x1024.jpeg 1536w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-2048x1366.jpeg 2048w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-18x12.jpeg 18w, https:\/\/aiportek.com\/wp-content\/uploads\/2026\/04\/\u91d1\u878d-600x400.jpeg 600w\" sizes=\"(max-width: 2560px) 100vw, 2560px\" \/><\/div><\/a>\n\t\t\t\t<div class=\"elementor-post__badge\">Hongke Dry Goods<\/div>\n\t\t\t\t<div class=\"elementor-post__text\">\n\t\t\t\t<h3 class=\"elementor-post__title\">\n\t\t\t<a href=\"https:\/\/aiportek.com\/en\/redis-finance\/\" target=\"&quot;_blank&quot;\">\n\t\t\t\tRainbow Solutions] 2026 Procurement Committee Must-Have: Hong Kong Bank Redis Procurement Checklist (Open Source vs Enterprise Decision Framework)\t\t\t<\/a>\n\t\t<\/h3>\n\t\t\t\t<div class=\"elementor-post__excerpt\">\n\t\t\t<p>The HKMA has repeatedly emphasized risk-based and principle-driven requirements in recent years, and has brought the risk of third-party IT solutions to the forefront, meaning that it's fine to turn on Maintenance or Redis Enterprise, but you have to prove that the \"controls work\" rather than that the \"tool is famous\".<\/p>\n\t\t<\/div>\n\t\t\n\t\t<a class=\"elementor-post__read-more\" href=\"https:\/\/aiportek.com\/en\/redis-finance\/\" aria-label=\"Read more about HongKong Solutions] 2026 Procurement Committee Must-Have: Hong Kong Bank Redis Procurement Checklist (Open Source vs Enterprise Decision Framework)\" tabindex=\"-1\" target=\"_blank\">\n\t\t\tRead more\t\t<\/a>\n\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-post__meta-data\">\n\t\t\t\t\t<span class=\"elementor-post-author\">\n\t\t\tHongKeTechnology\t\t<\/span>\n\t\t\t\t<span class=\"elementor-post-date\">\n\t\t\tApril 27, 2026\t\t<\/span>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/article>\n\t\t\t\t<\/div>\n\t\t\n\t\t\t\t<div class=\"e-load-more-anchor\" data-page=\"1\" data-max-page=\"33\" 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href=\"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/34917\/page\/2\/\">\"<\/a>\t\t<\/nav>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>Banks dealing with AML and anti-fraud often face the tension between real-time decision-making and in-depth investigation. In this paper, we analyze how Redis (real-time scoring) and ArangoDB (graph database correlation analysis) can be perfectly divided into different roles and combined with Decisions to automate the process to meet the HKMA compliance guidelines and create a millisecond RegTech defense.<\/p>","protected":false},"author":1,"featured_media":34919,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[12],"tags":[40,36],"class_list":["post-34917","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-12","tag-redis","tag-36"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/34917","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/comments?post=34917"}],"version-history":[{"count":8,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/34917\/revisions"}],"predecessor-version":[{"id":34926,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/posts\/34917\/revisions\/34926"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/media\/34919"}],"wp:attachment":[{"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/media?parent=34917"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/categories?post=34917"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aiportek.com\/en\/wp-json\/wp\/v2\/tags?post=34917"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}