{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T04:42:33Z","timestamp":1667536953955},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"09","license":[{"start":{"date-parts":[[2020,4,3]],"date-time":"2020-04-03T00:00:00Z","timestamp":1585872000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.aaai.org"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AAAI"],"abstract":"<jats:p>This paper describes Cognitive Compliance - a solution that automates the complex manual process of assessing regulatory compliance of personal financial advice. The solution uses natural language processing (NLP), machine learning and deep learning to characterise the regulatory risk status of personal financial advice documents with traffic light rating for various risk factors. This enables comprehensive coverage of the review and rapid identification of documents at high risk of non-compliance with government regulations.<\/jats:p>","DOI":"10.1609\/aaai.v34i09.7105","type":"journal-article","created":{"date-parts":[[2020,6,29]],"date-time":"2020-06-29T18:04:46Z","timestamp":1593453886000},"page":"13636-13637","source":"Crossref","is-referenced-by-count":0,"title":["Cognitive Compliance: Assessing Regulatory Risk in Financial Advice Documents"],"prefix":"10.1609","volume":"34","author":[{"given":"Wanita","family":"Sherchan","sequence":"first","affiliation":[]},{"given":"Sue Ann","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Simon","family":"Harris","sequence":"additional","affiliation":[]},{"given":"Nebula","family":"Alam","sequence":"additional","affiliation":[]},{"given":"Khoi-Nguyen","family":"Tran","sequence":"additional","affiliation":[]},{"given":"Christopher J.","family":"Butler","sequence":"additional","affiliation":[]}],"member":"9382","published-online":{"date-parts":[[2020,4,3]]},"container-title":["Proceedings of the AAAI Conference on Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/7105\/6959","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/7105\/6959","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T01:01:03Z","timestamp":1667523663000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/7105"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,3]]},"references-count":0,"journal-issue":{"issue":"09","published-online":{"date-parts":[[2020,6,19]]}},"URL":"https:\/\/doi.org\/10.1609\/aaai.v34i09.7105","relation":{},"ISSN":["2374-3468","2159-5399"],"issn-type":[{"value":"2374-3468","type":"electronic"},{"value":"2159-5399","type":"print"}],"subject":[],"published":{"date-parts":[[2020,4,3]]}}}  <script>parent.window.postMessage('ixistenz.url:https://api.crossref.org/works/10.1609%2FAAAI.V34I09.7105', '*'); </script> <div id='browserdiffcontainer' style='position: fixed; right: 10px; top: 10vh; min-width: 60px;  border: 1px solid white; background: rgb(251, 189, 0);; opacity: 0.9; font-family: helvetica, arial, sans serif;  font-size: 12px; z-index: 20001; padding-bottom: 20px;'><div onclick="toggle('browserdiffcontainerlist'); return false;" style='background: rgb(151, 89, 0);; color: white; '><strong>&nbsp; <span class='glyphicon glyphicon-minus'></span> NODES</strong></div><div id='browserdiffcontainerlist' style='padding-left: 10px; padding-right: 5px; max-height: 50vh; overflow: auto; '><div><a href='#diffid883' style='color: white;' onClick="parent.window.postMessage('ixistenz.opendiff:883', '*');; return false;" style='text-decoration: none; '>Association </a> <a style='color: white;' href='#diffid883'><sup>1</sup></a></div></div></div>
<script>
function toggle( divname ) {
  var x = document.getElementById( divname );
  if (x.style.display === 'none') {
    x.style.display = 'block';
  } else {
    x.style.display = 'none';
  }
} </script>