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    <title>topic credit scorecard problems in SAS Risk Management</title>
    <link>https://communities.sas.com/t5/SAS-Risk-Management/credit-scorecard-problems/m-p/416020#M205</link>
    <description>&lt;P&gt;Hi, guys.&lt;/P&gt;&lt;P&gt;My goal is to get a new scorecard better than the old one. But on test month it has higher bad rate and lower approval...&lt;/P&gt;&lt;P&gt;What am I doing wrong?&lt;/P&gt;&lt;P&gt;I try to build a scorecard model in Enterprise Miner:&amp;nbsp;&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="diagram" style="width: 600px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16839i049DD735DBF9E891/image-size/large?v=v2&amp;amp;px=999" role="button" title="11.jpg" alt="diagram" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;diagram&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;I keep the only non-correlating predictors:&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="variable correlation" style="width: 600px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16844i2CC0D79CE2CADAA6/image-size/large?v=v2&amp;amp;px=999" role="button" title="15.jpg" alt="variable correlation" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;variable correlation&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;It seems my variables are pretty valuable:&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="from scorecard results before reject inference" style="width: 579px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16845iC69AFC4D8E7A4DBD/image-size/large?v=v2&amp;amp;px=999" role="button" title="16.jpg" alt="from scorecard results before reject inference" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;from scorecard results before reject inference&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="from interactive grouping before reject inference" style="width: 600px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16846i13A28C85ED6EA098/image-size/large?v=v2&amp;amp;px=999" role="button" title="17.jpg" alt="from interactive grouping before reject inference" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;from interactive grouping before reject inference&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;And I meet several problems:&lt;/P&gt;&lt;P&gt;1) very few target events:&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="def_6_30  - overdue 30+ on 6 months" style="width: 474px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16840iAF73467B91271B41/image-size/large?v=v2&amp;amp;px=999" role="button" title="12.jpg" alt="def_6_30  - overdue 30+ on 6 months" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;def_6_30  - overdue 30+ on 6 months&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;to overcome this limitaion I involved frequency variable, but I suspect model to bias:&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="13.jpg" style="width: 479px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16841i409F81595F8E2CC2/image-size/large?v=v2&amp;amp;px=999" role="button" title="13.jpg" alt="13.jpg" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&lt;SPAN&gt;2) cannot get stable model&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-left" image-alt="before reject inference" style="width: 400px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16838iEF118FA11D88D3B7/image-size/medium?v=v2&amp;amp;px=400" role="button" title="image.png" alt="before reject inference" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;before reject inference&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;3) train / validation gini varies drastically: before reject inference, data partition 50/50 stratified, train gini=0.52, validation gini=0.49&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="before reject inference" style="width: 600px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16843iB594BE2A19FA3A2D/image-size/large?v=v2&amp;amp;px=999" role="button" title="14.jpg" alt="before reject inference" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;before reject inference&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;And some questions:&lt;/P&gt;&lt;P&gt;1) How to estimate bad rate and approval of scorecard model?&lt;/P&gt;&lt;P&gt;All I need &amp;nbsp;- is to improove old scorecard model, to archive this I tried to exclude predictors (start from the lowest information value) and add new ones (with high IV) . Honestly speaking have no other ides of doing that.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;P.s. I used Naim Siddiqui's &amp;nbsp;book and "developing credit scorecards using credit scoring for sas"&lt;/P&gt;</description>
    <pubDate>Fri, 24 Nov 2017 14:22:08 GMT</pubDate>
    <dc:creator>ManOfHonor</dc:creator>
    <dc:date>2017-11-24T14:22:08Z</dc:date>
    <item>
      <title>credit scorecard problems</title>
      <link>https://communities.sas.com/t5/SAS-Risk-Management/credit-scorecard-problems/m-p/416020#M205</link>
      <description>&lt;P&gt;Hi, guys.&lt;/P&gt;&lt;P&gt;My goal is to get a new scorecard better than the old one. But on test month it has higher bad rate and lower approval...&lt;/P&gt;&lt;P&gt;What am I doing wrong?&lt;/P&gt;&lt;P&gt;I try to build a scorecard model in Enterprise Miner:&amp;nbsp;&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="diagram" style="width: 600px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16839i049DD735DBF9E891/image-size/large?v=v2&amp;amp;px=999" role="button" title="11.jpg" alt="diagram" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;diagram&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;I keep the only non-correlating predictors:&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="variable correlation" style="width: 600px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16844i2CC0D79CE2CADAA6/image-size/large?v=v2&amp;amp;px=999" role="button" title="15.jpg" alt="variable correlation" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;variable correlation&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;It seems my variables are pretty valuable:&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="from scorecard results before reject inference" style="width: 579px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16845iC69AFC4D8E7A4DBD/image-size/large?v=v2&amp;amp;px=999" role="button" title="16.jpg" alt="from scorecard results before reject inference" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;from scorecard results before reject inference&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="from interactive grouping before reject inference" style="width: 600px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16846i13A28C85ED6EA098/image-size/large?v=v2&amp;amp;px=999" role="button" title="17.jpg" alt="from interactive grouping before reject inference" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;from interactive grouping before reject inference&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;And I meet several problems:&lt;/P&gt;&lt;P&gt;1) very few target events:&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="def_6_30  - overdue 30+ on 6 months" style="width: 474px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16840iAF73467B91271B41/image-size/large?v=v2&amp;amp;px=999" role="button" title="12.jpg" alt="def_6_30  - overdue 30+ on 6 months" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;def_6_30  - overdue 30+ on 6 months&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;to overcome this limitaion I involved frequency variable, but I suspect model to bias:&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="13.jpg" style="width: 479px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16841i409F81595F8E2CC2/image-size/large?v=v2&amp;amp;px=999" role="button" title="13.jpg" alt="13.jpg" /&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&amp;nbsp;&lt;SPAN&gt;2) cannot get stable model&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;BR /&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-left" image-alt="before reject inference" style="width: 400px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16838iEF118FA11D88D3B7/image-size/medium?v=v2&amp;amp;px=400" role="button" title="image.png" alt="before reject inference" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;before reject inference&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;3) train / validation gini varies drastically: before reject inference, data partition 50/50 stratified, train gini=0.52, validation gini=0.49&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;span class="lia-inline-image-display-wrapper lia-image-align-center" image-alt="before reject inference" style="width: 600px;"&gt;&lt;img src="https://communities.sas.com/t5/image/serverpage/image-id/16843iB594BE2A19FA3A2D/image-size/large?v=v2&amp;amp;px=999" role="button" title="14.jpg" alt="before reject inference" /&gt;&lt;span class="lia-inline-image-caption" onclick="event.preventDefault();"&gt;before reject inference&lt;/span&gt;&lt;/span&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;And some questions:&lt;/P&gt;&lt;P&gt;1) How to estimate bad rate and approval of scorecard model?&lt;/P&gt;&lt;P&gt;All I need &amp;nbsp;- is to improove old scorecard model, to archive this I tried to exclude predictors (start from the lowest information value) and add new ones (with high IV) . Honestly speaking have no other ides of doing that.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;P.s. I used Naim Siddiqui's &amp;nbsp;book and "developing credit scorecards using credit scoring for sas"&lt;/P&gt;</description>
      <pubDate>Fri, 24 Nov 2017 14:22:08 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Risk-Management/credit-scorecard-problems/m-p/416020#M205</guid>
      <dc:creator>ManOfHonor</dc:creator>
      <dc:date>2017-11-24T14:22:08Z</dc:date>
    </item>
    <item>
      <title>Re: credit scorecard problems</title>
      <link>https://communities.sas.com/t5/SAS-Risk-Management/credit-scorecard-problems/m-p/416027#M206</link>
      <description>&lt;P&gt;Your bad percent is too small. I think your Logistic model would suffer Overdisperse Problem.&lt;/P&gt;
&lt;P&gt;Why not using Oversample like good:bad= 1:1&amp;nbsp; &amp;nbsp; or 2:1&amp;nbsp; .&lt;/P&gt;</description>
      <pubDate>Fri, 24 Nov 2017 14:20:02 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Risk-Management/credit-scorecard-problems/m-p/416027#M206</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2017-11-24T14:20:02Z</dc:date>
    </item>
    <item>
      <title>Re: credit scorecard problems</title>
      <link>https://communities.sas.com/t5/SAS-Risk-Management/credit-scorecard-problems/m-p/416030#M207</link>
      <description>&lt;P&gt;What node do I use to implement this?&lt;/P&gt;</description>
      <pubDate>Fri, 24 Nov 2017 14:25:55 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Risk-Management/credit-scorecard-problems/m-p/416030#M207</guid>
      <dc:creator>ManOfHonor</dc:creator>
      <dc:date>2017-11-24T14:25:55Z</dc:date>
    </item>
    <item>
      <title>Re: credit scorecard problems</title>
      <link>https://communities.sas.com/t5/SAS-Risk-Management/credit-scorecard-problems/m-p/416132#M208</link>
      <description>&lt;P&gt;Sorry . I never use EM. but the following could oversample.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;proc surveyselect data=have sampsize=(1000 1000) out=data_oversample;&lt;/P&gt;
&lt;P&gt;strata good_bad;&lt;/P&gt;
&lt;P&gt;run;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Note: assuming you have 1000 bad obs.&lt;/P&gt;</description>
      <pubDate>Sat, 25 Nov 2017 09:38:12 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Risk-Management/credit-scorecard-problems/m-p/416132#M208</guid>
      <dc:creator>Ksharp</dc:creator>
      <dc:date>2017-11-25T09:38:12Z</dc:date>
    </item>
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