Challenge    I had the problem of developing a working, effective and efficient tool for predicting whether a  prospective customer is likely to default on a loan facility or not, using a Machine Learning algorithm.  Knowing very well that management had series of meetings, seminars and presentations every now  and then where figures and data were hurled at them, I had the duty to arouse their interests,  sustain those interests and finally get their buy-in into my idea of predicting customer default  probability.    Selection    To do this I fell on story telling. The idea was to not just put across a convincing argument for my  proffered solution to the problem, but to connect the data and result to the values, characters and  emotions  of management through story telling. Additionally, through story telling, I sought to solve  the problem in accordance with corporate ideals as well as integrating other stakeholders’  interests.    Application    Historic data on client credit history was available and so I started with that. I pointed to  management the outstanding reasons why clients come to contract loans and explained to them  how each of us who find ourselves in similar situation are very likely to seek financial assistance like  the clients do.  Also, as per the data analytics results, I pointed out to management  the key causes  of defaults on credit facilities. I also commented on the Machine Learning algorithm I used and its  efficiency in predicting default on loans, given information about the client. Finally, i told  management that it turned out that among clients who defaulted were those who were at lower  levels of the socio-economic strata and actually sought  to address very basic and essential needs  that everyone should have access to. In as much as management was determined to making profits  they were also empathic about their clients. So I suggested to them that for such clients who will  not qualify for credit facilities based of the algorithm, management should still go ahead to extend  the credit to them with a little premium for insurance cover against default. In this way everybody  wins!      Insight    When I finished the presentation, management was wowed by the fact that I didn’t only provide  a  working algorithm for solving the problem of predicting defaults on loans but I was empathetic  about the vulnerable and I was thinking systemically and holistically in a way that benefits all  stakeholders; customers, managers, shareholders as well as external stakeholders like the insurance  company. According to them, I stretched the limit of providing an efficient and effective algorithm  but altogether a lop-sided solution, where just management would have won.          Approach

I feel story telling for this project was effective and efficient but there’s room for a blended  approach. I envisage the possibility and the potency of using story telling with visualization as well.  With this we could achieve connecting the information with the emotions and ideals of  management while incorporating the interests of other stakeholders plus presenting a pictorial flow  of concepts, ideas and solutions, which is what Machine Learning and Data Sscience is about.


Challenge I had the problem of developing a working , effective and efficient tool for predicting whether a prospective customer is likely to default on a loan facility or not , using a Machine Learning algorithm . Knowing very well that management had series of meetings , seminars and presentations every now and then where figures and data were hurled at them , I had the duty to arouse their interests , sustain those interests and finally get their buy - in into my idea of predicting customer default probability . Selection To do this I fell on story telling . The idea was to not just put across a convincing argument for my proffered solution to the problem , but to connect the data and result to the values , characters and emotions of management through story telling . Additionally , through story telling , I sought to solve the problem in accordance with corporate ideals as well as integrating other stakeholders ’ interests . Application Historic data on client credit history was available and so I started with that . I pointed to management the outstanding reasons why clients come to contract loans and explained to them how each of us who find ourselves in similar situation are very likely to seek financial assistance like the clients do . Also , as per the data analytics results , I pointed out to management the key causes of defaults on credit facilities . I also commented on the Machine Learning algorithm I used and its efficiency in predicting default on loans , given information about the client . Finally , i told management that it turned out that among clients who defaulted were those who were at lower levels of the socio - economic strata and actually sought to address very basic and essential needs that everyone should have access to . In as much as management was determined to making profits they were also empathic about their clients . So I suggested to them that for such clients who will not qualify for credit facilities based of the algorithm , management should still go ahead to extend the credit to them with a little premium for insurance cover against default . In this way everybody wins ! Insight When I finished the presentation , management was wowed by the fact that I did n’t only provide a working algorithm for solving the problem of predicting defaults on loans but I was empathetic about the vulnerable and I was thinking systemically and holistically in a way that benefits all stakeholders ; customers , managers , shareholders as well as external stakeholders like the insurance company . According to them , I stretched the limit of providing an efficient and effective algorithm but altogether a lop - sided solution , where just management would have won . Approach I feel story telling for this project was effective and efficient but there ’s room for a blended approach . I envisage the possibility and the potency of using story telling with visualization as well . With this we could achieve connecting the information with the emotions and ideals of management while incorporating the interests of other stakeholders plus presenting a pictorial flow of concepts , ideas and solutions , which is what Machine Learning and Data Sscience is about .