{"id":453,"date":"2022-12-15T14:35:17","date_gmt":"2022-12-15T14:35:17","guid":{"rendered":"https:\/\/nasaff.com\/?page_id=453"},"modified":"2023-01-02T18:34:08","modified_gmt":"2023-01-02T18:34:08","slug":"prevent-errors-and-fraud-with-anomaly-detection","status":"publish","type":"page","link":"https:\/\/nasaff.com\/en\/prevent-errors-and-fraud-with-anomaly-detection","title":{"rendered":"Avoid errors and fraud with anomaly detection"},"content":{"rendered":"<p>Machine learning-based anomaly detection understands your data, identifies anomalies, and helps you avoid damage.<\/p>\n\n\n\n<p>Be it errors in entering invoice numbers or amounts, misallocation of charges on invoices, or fraudulent activities such as credit card or voucher fraud.<\/p>\n\n\n\n<p>Anomaly detection systems:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Analyze large volumes of transactional data to detect anomalies in underlying patterns<\/li>\n\n\n\n<li>Can respond in real time to detected fraud with user suspensions, transaction cancellations or notifications<\/li>\n<\/ul>\n\n\n\n<p>Examples of anomaly detection techniques include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Analyze multiple ID or credit card parameters using machine learning algorithms to prevent fake ID and credit card transactions.<\/li>\n\n\n\n<li>Prevent abuse of promo codes and loyalty programs by detecting users who use multiple accounts or proxy servers to make unlawful purchases and gain benefits<\/li>\n\n\n\n<li>Examine and interpret the components of supporting documents to identify errors and discrepancies and avoid erroneous entries<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Die auf maschinellem Lernen basierende Anomalie-Erkennung versteht Ihre Daten, identifiziert Anomalien und hilft Ihnen, Sch\u00e4den zu vermeiden. Seien es Fehler bei der Eingabe von Rechnungsnummern oder -betr\u00e4gen, die falsche Zuordnung von Geb\u00fchren auf Rechnungen oder betr\u00fcgerische Aktivit\u00e4ten wie Kreditkarten- oder Gutscheinbetrug. Systeme zur Erkennung von Anomalien: Beispiele f\u00fcr Techniken zur Erkennung von Anomalien sind:<\/p>","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"_themeisle_gutenberg_block_has_review":false,"footnotes":""},"class_list":["post-453","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/nasaff.com\/en\/wp-json\/wp\/v2\/pages\/453","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nasaff.com\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/nasaff.com\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/nasaff.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/nasaff.com\/en\/wp-json\/wp\/v2\/comments?post=453"}],"version-history":[{"count":2,"href":"https:\/\/nasaff.com\/en\/wp-json\/wp\/v2\/pages\/453\/revisions"}],"predecessor-version":[{"id":532,"href":"https:\/\/nasaff.com\/en\/wp-json\/wp\/v2\/pages\/453\/revisions\/532"}],"wp:attachment":[{"href":"https:\/\/nasaff.com\/en\/wp-json\/wp\/v2\/media?parent=453"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}