{"id":55,"date":"2013-07-20T17:51:47","date_gmt":"2013-07-20T12:21:47","guid":{"rendered":"http:\/\/ucanalytics.com\/blogs\/?p=55"},"modified":"2016-09-12T13:32:28","modified_gmt":"2016-09-12T08:02:28","slug":"credit-scorecards-advanced-analytics-part-4","status":"publish","type":"post","link":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/","title":{"rendered":"Credit Scorecards – Advanced Analytics (part 4 of 7)"},"content":{"rendered":"
\n

Modeling in Advanced Analytics<\/span><\/h2>\n
\"Advanced<\/a>

Advanced Analytics: Model Development – by Roopam<\/p><\/div>\n

The room, full of Analysts, erupts with a loud round of laughter when a young business analyst narrates to us an incident from his recent trip back home. A distant aunt inquired about his new profession. His response \u2013 I am into modeling. She got all excited and asked \u2013 is it just on the ramp or will I see you on the television? Jokes apart, this left me wondering about the roots of the word modeling or model. What is a model?<\/p>\n

A model is defined as a simplified representation of reality. A representation of reality, hmmm, a photograph is a representation of reality \u2013 a moment of reality capture on the reel \u2013 does that makes it into a model. I think yes. Similarly, a newspaper reporter covering an incident and makes it into breaking news is also a model \u2013 a descriptive model. Now, let us try to link models with Analytics.<\/p>\n

Data warehouse, Business Intelligence and Advanced Analytics<\/span><\/h2>\n

Analytics has received a massive boost because of the emergence of information technology. We are living in the era of big data. A plethora of data collected at every stage of the business process had created a need to extract knowledge out of the information. This overall process has three aspects to it<\/p>\n

1. Data warehouse or data marts:<\/strong> transactional data is extracted-transformed and loaded (ETL) into a data model \/ schema for the purpose of analysis
\n2. Business Intelligence or dashboards:<\/strong> \u201cas is\u201d business reports
\n3. Predictive Analytics or Advanced Analytics:<\/strong> high-end statistical and data mining exercise<\/p>\n

As the quantum of data is exponentially increasing, Hadoop and big data technologies are replacing the data warehouses. However, the thought process for business intelligence and predictive analytics \u2013 the focus of this article \u2013 will not change much. Let me try to distinguish between business intelligence and predictive Analytics using something I learned at a professional theater.<\/p>\n

5Ws for business intelligence & predictive Analytics – Lessons from\u00a0<\/span>Theater<\/span><\/h4>\n
\"5<\/a>

5 Ws for Data Warehouse, Business Intelligence, and Advanced Analytics – by Roopam<\/p><\/div>\n

I joined a professional theater group a few years ago. To understand the nuances of acting we started with improv or improvisation theater. This form of theater does not have a predefined script but the actors built the story while performing. Most people thought I was a good improv actor. However, the style of remembering dialogue while performing did not work very well for me and hence it was the end of my theater gig. However, I learn some good lessons from the whole experience. One of them was the five-Ws of deciphering a character to build the drama.<\/p>\n

1. What had happened?
\n2. When did it happen?
\n3. Where did it happen?
\n4. Who was part of this?
\n5. Why did it happen?<\/p>\n

Clearly, the first four questions are trying to report an as-is version of the reality – a descriptive model. This is exactly what the business intelligence professionals try to achieve through the fancy reporting platforms & software. The fifth question is the trickiest of the lot. The question that keeps scientists and inquisitive minds awake late at night.<\/p>\n

Newton’s Legacy<\/span><\/h4>\n

An apple falls from a tree. How difficult is it to answer the first four questions? Most of us can answer them with a help of a clock and a map. However, Isaac Newton answered the fifth question and his answer \u2013 Gravity. If he had stopped there, nobody would have remembered him after close to four hundred years since his birth. He gave a mathematical model to explain this phenomenon.<\/p>\n

\"4<\/a><\/p>\n

Replace apple and earth with any other objects and you have the general equation for the model. Albert Einstein did shatter the Newtonian notion of Gravity. However, this model still holds good for all problems of practical purposes and used extensively in rocket science.<\/p>\n

Advanced analytics tries to facilitate the answer to the fifth question of why did something happen using predictive modeling. \u00a0The combination of high-end statistical and data mining techniques along with analysts\u2019 business acumen produces models that help organizations make informed decisions.\u00a0Remember, this is just the beginning and causality is still a fair distance!<\/p>\n

Credit Scoring Models<\/span><\/h2>\n

Credit scorecards are models to predict the probability of a borrower default on his\/her loan. The following is a simplified version of credit score with three variables<\/p>\n

Credit Score = Age + Loan to Value Ratio (LTV) + Installment (EMI) to Income Ratio (IIR)<\/p>\n

\"4.<\/a><\/p>\n

A 28-year-old man with the LTV of 75 and the IIR of 60 will have the score of 10+50+5 =65 and hence is a high credit risk<\/em>.<\/pre>\n
\"4<\/a>
Classification of good & bad loans using two variables – LTV & IIR – by Roopam<\/p><\/div>\n
Now the question is, how did we arrive at the bucket-wise score points and associated risk tables? By now, after going through the previous three articles of the series, you must have some idea how we will go about it. We have a historical list of good \/ bad borrowers (article 2<\/a>) that we want to distinguish using predictor variables (article 3<\/a>). There are several statistical & data mining techniques that could help us achieve our object such as<\/p>\n
1. Decision tree
\n2. Neural Networks
\n3. Support Vector Machines
\n4. Probit Regression
\n5. Linear discriminant analysis
\n6. Logistic Regression<\/p>\n
Logistic regression is the most commonly used technique for the purpose. We will explore more about logistic regression in the next article.<\/p>\n
Sign-off Note<\/span><\/h4>\n
I must conclude this article by saying that the good analysts find a good mathematical model as beautiful as the model walking on the catwalk ramp.<\/p>\n
References<\/strong>\r\n1. Credit Risk Scorecards: Developing and Implementing Intelligent Credit Scoring \u2013 Naeem Siddiqi<\/span>\r\n2. <\/span>Credit Scoring for Risk Managers: The Handbook for Lenders \u2013 Elizabeth Mays and Niall Lynas<\/span><\/pre>\n","protected":false},"excerpt":{"rendered":"
Modeling in Advanced Analytics The room, full of Analysts, erupts with a loud round of laughter when a young business analyst narrates to us an incident from his recent trip back home. A distant aunt inquired about his new profession. His response \u2013 I am into modeling. She got all excited and asked \u2013 is<\/p>\n
Read More…<\/a><\/p>\n","protected":false},"author":1,"featured_media":106,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_newsletter_tier_id":0,"jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[55,54],"tags":[8,7,69,6,10],"jetpack_publicize_connections":[],"yoast_head":"\nCredit Scorecards : Advanced Analytics - YOU CANalytics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Credit Scorecards : Advanced Analytics - YOU CANalytics\" \/>\n<meta property=\"og:description\" content=\"Modeling in Advanced Analytics The room, full of Analysts, erupts with a loud round of laughter when a young business analyst narrates to us an incident from his recent trip back home. A distant aunt inquired about his new profession. His response \u2013 I am into modeling. She got all excited and asked \u2013 isRead More...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/\" \/>\n<meta property=\"og:site_name\" content=\"YOU CANalytics |\" \/>\n<meta property=\"article:author\" content=\"roopam\" \/>\n<meta property=\"article:published_time\" content=\"2013-07-20T12:21:47+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2016-09-12T08:02:28+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/4-Classification-1.jpg?fit=342%2C270&ssl=1\" \/>\n\t<meta property=\"og:image:width\" content=\"342\" \/>\n\t<meta property=\"og:image:height\" content=\"270\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Roopam Upadhyay\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Organization\",\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#organization\",\"name\":\"YOU CANalytics\",\"url\":\"https:\/\/ucanalytics.com\/blogs\/\",\"sameAs\":[],\"logo\":{\"@type\":\"ImageObject\",\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#logo\",\"inLanguage\":\"en-US\",\"url\":\"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2015\/11\/YOU-CANalytics-Logo.jpg?fit=607%2C120\",\"contentUrl\":\"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2015\/11\/YOU-CANalytics-Logo.jpg?fit=607%2C120\",\"width\":607,\"height\":120,\"caption\":\"YOU CANalytics\"},\"image\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#logo\"}},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#website\",\"url\":\"https:\/\/ucanalytics.com\/blogs\/\",\"name\":\"YOU CANalytics |\",\"description\":\"Explore the Power of Data Science\",\"publisher\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/ucanalytics.com\/blogs\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"},{\"@type\":\"ImageObject\",\"@id\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#primaryimage\",\"inLanguage\":\"en-US\",\"url\":\"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/4-Classification-1.jpg?fit=342%2C270&ssl=1\",\"contentUrl\":\"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/4-Classification-1.jpg?fit=342%2C270&ssl=1\",\"width\":342,\"height\":270},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#webpage\",\"url\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/\",\"name\":\"Credit Scorecards : Advanced Analytics - YOU CANalytics\",\"isPartOf\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#primaryimage\"},\"datePublished\":\"2013-07-20T12:21:47+00:00\",\"dateModified\":\"2016-09-12T08:02:28+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/ucanalytics.com\/blogs\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Credit Scorecards – Advanced Analytics (part 4 of 7)\"}]},{\"@type\":\"Article\",\"@id\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#webpage\"},\"author\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#\/schema\/person\/55961a1cea272ecdf290cb387be069b6\"},\"headline\":\"Credit Scorecards – Advanced Analytics (part 4 of 7)\",\"datePublished\":\"2013-07-20T12:21:47+00:00\",\"dateModified\":\"2016-09-12T08:02:28+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#webpage\"},\"wordCount\":917,\"commentCount\":14,\"publisher\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#organization\"},\"image\":{\"@id\":\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/4-Classification-1.jpg?fit=342%2C270&ssl=1\",\"keywords\":[\"Banking and Insurance Analytics\",\"Business Analytics\",\"Credit Risk\",\"Predictive Analytics\",\"Roopam Upadhyay\"],\"articleSection\":[\"Credit Risk Analytics Series\",\"Risk Analytics\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#respond\"]}]},{\"@type\":\"Person\",\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#\/schema\/person\/55961a1cea272ecdf290cb387be069b6\",\"name\":\"Roopam Upadhyay\",\"image\":{\"@type\":\"ImageObject\",\"@id\":\"https:\/\/ucanalytics.com\/blogs\/#personlogo\",\"inLanguage\":\"en-US\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/dd1aa0b0e813f7639800bcfad6a554f1?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/dd1aa0b0e813f7639800bcfad6a554f1?s=96&d=mm&r=g\",\"caption\":\"Roopam Upadhyay\"},\"description\":\"This blog contains my personal views and thoughts on predictive Analytics and big data. - Roopam Upadhyay\",\"sameAs\":[\"roopam\"],\"url\":\"https:\/\/ucanalytics.com\/blogs\/author\/roopam\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Credit Scorecards : Advanced Analytics - YOU CANalytics","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/","og_locale":"en_US","og_type":"article","og_title":"Credit Scorecards : Advanced Analytics - YOU CANalytics","og_description":"Modeling in Advanced Analytics The room, full of Analysts, erupts with a loud round of laughter when a young business analyst narrates to us an incident from his recent trip back home. A distant aunt inquired about his new profession. His response \u2013 I am into modeling. She got all excited and asked \u2013 isRead More...","og_url":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/","og_site_name":"YOU CANalytics |","article_author":"roopam","article_published_time":"2013-07-20T12:21:47+00:00","article_modified_time":"2016-09-12T08:02:28+00:00","og_image":[{"width":342,"height":270,"url":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/4-Classification-1.jpg?fit=342%2C270&ssl=1","type":"image\/jpeg"}],"twitter_misc":{"Written by":"Roopam Upadhyay","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Organization","@id":"https:\/\/ucanalytics.com\/blogs\/#organization","name":"YOU CANalytics","url":"https:\/\/ucanalytics.com\/blogs\/","sameAs":[],"logo":{"@type":"ImageObject","@id":"https:\/\/ucanalytics.com\/blogs\/#logo","inLanguage":"en-US","url":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2015\/11\/YOU-CANalytics-Logo.jpg?fit=607%2C120","contentUrl":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2015\/11\/YOU-CANalytics-Logo.jpg?fit=607%2C120","width":607,"height":120,"caption":"YOU CANalytics"},"image":{"@id":"https:\/\/ucanalytics.com\/blogs\/#logo"}},{"@type":"WebSite","@id":"https:\/\/ucanalytics.com\/blogs\/#website","url":"https:\/\/ucanalytics.com\/blogs\/","name":"YOU CANalytics |","description":"Explore the Power of Data Science","publisher":{"@id":"https:\/\/ucanalytics.com\/blogs\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/ucanalytics.com\/blogs\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"},{"@type":"ImageObject","@id":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#primaryimage","inLanguage":"en-US","url":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/4-Classification-1.jpg?fit=342%2C270&ssl=1","contentUrl":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/4-Classification-1.jpg?fit=342%2C270&ssl=1","width":342,"height":270},{"@type":"WebPage","@id":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#webpage","url":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/","name":"Credit Scorecards : Advanced Analytics - YOU CANalytics","isPartOf":{"@id":"https:\/\/ucanalytics.com\/blogs\/#website"},"primaryImageOfPage":{"@id":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#primaryimage"},"datePublished":"2013-07-20T12:21:47+00:00","dateModified":"2016-09-12T08:02:28+00:00","breadcrumb":{"@id":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/ucanalytics.com\/blogs\/"},{"@type":"ListItem","position":2,"name":"Credit Scorecards – Advanced Analytics (part 4 of 7)"}]},{"@type":"Article","@id":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#article","isPartOf":{"@id":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#webpage"},"author":{"@id":"https:\/\/ucanalytics.com\/blogs\/#\/schema\/person\/55961a1cea272ecdf290cb387be069b6"},"headline":"Credit Scorecards – Advanced Analytics (part 4 of 7)","datePublished":"2013-07-20T12:21:47+00:00","dateModified":"2016-09-12T08:02:28+00:00","mainEntityOfPage":{"@id":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#webpage"},"wordCount":917,"commentCount":14,"publisher":{"@id":"https:\/\/ucanalytics.com\/blogs\/#organization"},"image":{"@id":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#primaryimage"},"thumbnailUrl":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/4-Classification-1.jpg?fit=342%2C270&ssl=1","keywords":["Banking and Insurance Analytics","Business Analytics","Credit Risk","Predictive Analytics","Roopam Upadhyay"],"articleSection":["Credit Risk Analytics Series","Risk Analytics"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/ucanalytics.com\/blogs\/credit-scorecards-advanced-analytics-part-4\/#respond"]}]},{"@type":"Person","@id":"https:\/\/ucanalytics.com\/blogs\/#\/schema\/person\/55961a1cea272ecdf290cb387be069b6","name":"Roopam Upadhyay","image":{"@type":"ImageObject","@id":"https:\/\/ucanalytics.com\/blogs\/#personlogo","inLanguage":"en-US","url":"https:\/\/secure.gravatar.com\/avatar\/dd1aa0b0e813f7639800bcfad6a554f1?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/dd1aa0b0e813f7639800bcfad6a554f1?s=96&d=mm&r=g","caption":"Roopam Upadhyay"},"description":"This blog contains my personal views and thoughts on predictive Analytics and big data. - Roopam Upadhyay","sameAs":["roopam"],"url":"https:\/\/ucanalytics.com\/blogs\/author\/roopam\/"}]}},"jetpack_featured_media_url":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/4-Classification-1.jpg?fit=342%2C270&ssl=1","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p3L0jT-T","jetpack-related-posts":[{"id":309,"url":"https:\/\/ucanalytics.com\/blogs\/seven-advanced-analytics1-0-solutions-loan-portfolios\/","url_meta":{"origin":55,"position":0},"title":"7 Advanced-Analytics Solutions for Loan Portfolios","author":"Roopam Upadhyay","date":false,"format":false,"excerpt":"Year-One of Analytics - A Crucial Juncture I am a big fan of the graphic novel \u2013 Batman: the Dark Knight Returns \u2013 by Frank Miller. I almost lost my faith in Batman after watching the utterly ridiculous television series from the 60s \u2013 based on camp aesthetic. Batman was\u2026","rel":"","context":"In "Analytics Graffiti"","block_context":{"text":"Analytics Graffiti","link":"https:\/\/ucanalytics.com\/blogs\/category\/analytics-graffiti\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/08\/1-Batman-225x300.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":8,"url":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-part-1\/","url_meta":{"origin":55,"position":1},"title":"Credit Scorecards – Introduction (part 1 of 7)","author":"Roopam Upadhyay","date":false,"format":false,"excerpt":"Credit Scorecards in the Age of Credit Crisis This incident took place at a friend\u2019s party circa 2009, in the backdrop of the worst financial crisis the planet has seen for a long time. The average Joe on the street was aware of terms such as mortgaged-backed securities (MBS), sub-prime\u2026","rel":"","context":"In "Credit Risk Analytics Series"","block_context":{"text":"Credit Risk Analytics Series","link":"https:\/\/ucanalytics.com\/blogs\/category\/risk-analytics\/credit-risk-analytics-series\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2015\/12\/Slide7.jpg?fit=290%2C210&ssl=1&resize=350%2C200","width":350,"height":200},"classes":[]},{"id":281,"url":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-predictive-analytics-part-7\/","url_meta":{"origin":55,"position":2},"title":"Credit Scorecards –  Business Integration of Predictive Analytics (part 7 of 7)","author":"Roopam Upadhyay","date":false,"format":false,"excerpt":"Columbus - A lesson in Leadership Christopher Columbus \u2013 I have adored this man for various reasons at various stages of my life. At seven, I adored him because his mistakes were applauded and became part of history \u2013 Columbus mistook Native Americans for Indians because he thought he had\u2026","rel":"","context":"In "Credit Risk Analytics Series"","block_context":{"text":"Credit Risk Analytics Series","link":"https:\/\/ucanalytics.com\/blogs\/category\/risk-analytics\/credit-risk-analytics-series\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/7-Leader-225x300.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":2783,"url":"https:\/\/ucanalytics.com\/blogs\/in-conversation-with-eric-siegel-author-predictive-analytics\/","url_meta":{"origin":55,"position":3},"title":"In Conversation with Eric Siegel: Author ‘Predictive Analytics’","author":"Roopam Upadhyay","date":false,"format":false,"excerpt":"In Conversation with.. Today we are starting a new series on YOU CANalytics called 'in conversation with'. In this series we will talk to the leaders and experts of predictive analytics and big data to gain deeper insight into the field. Dr. Eric Siegel Our first guest for the series\u2026","rel":"","context":"In "Events & Interviews"","block_context":{"text":"Events & Interviews","link":"https:\/\/ucanalytics.com\/blogs\/category\/events-and-interviews\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2015\/12\/Slide15.jpg?fit=290%2C210&ssl=1&resize=350%2C200","width":350,"height":200},"classes":[]},{"id":230,"url":"https:\/\/ucanalytics.com\/blogs\/credit-scorecards-model-validation-part-6\/","url_meta":{"origin":55,"position":4},"title":"Credit Scorecards – Model Validation (Part 6 of 7)","author":"Roopam Upadhyay","date":false,"format":false,"excerpt":"There are only two ways to live your life. One is as though nothing is a miracle. The other is as though everything is a miracle. \u2013 Albert Einstein A Commentary on Curiosity\u00a0 I think the best way to appreciate and enjoy the trivial is to travel. When I say\u2026","rel":"","context":"In "Credit Risk Analytics Series"","block_context":{"text":"Credit Risk Analytics Series","link":"https:\/\/ucanalytics.com\/blogs\/category\/risk-analytics\/credit-risk-analytics-series\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2013\/07\/6-Travel-272x300.jpg?resize=350%2C200","width":350,"height":200},"classes":[]},{"id":8107,"url":"https:\/\/ucanalytics.com\/blogs\/conversation-naeem-siddiqi-author-credit-risk-scorecards-credit-scoring-guru\/","url_meta":{"origin":55,"position":5},"title":"In Conversation with Naeem Siddiqi – Author Credit Risk Scorecards and Credit Scoring Guru","author":"Roopam Upadhyay","date":false,"format":false,"excerpt":"Predictive analytics is\u00a0considered one\u00a0of the sexiest professions\u00a0of our times. But where did it all start? What was the first business application of predictive analytics? It is hard to pin down one particular application but one of the earliest and highly successful applications is certainly credit risk models and retail credit\u2026","rel":"","context":"In "Events & Interviews"","block_context":{"text":"Events & Interviews","link":"https:\/\/ucanalytics.com\/blogs\/category\/events-and-interviews\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2016\/04\/Naeem-Siddiqi.jpg?fit=604%2C508&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2016\/04\/Naeem-Siddiqi.jpg?fit=604%2C508&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/ucanalytics.com\/blogs\/wp-content\/uploads\/2016\/04\/Naeem-Siddiqi.jpg?fit=604%2C508&ssl=1&resize=525%2C300 1.5x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/posts\/55"}],"collection":[{"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/comments?post=55"}],"version-history":[{"count":0,"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/posts\/55\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/media\/106"}],"wp:attachment":[{"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/media?parent=55"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/categories?post=55"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ucanalytics.com\/blogs\/wp-json\/wp\/v2\/tags?post=55"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}