## Count consecutive number of days with condition in R

Although R is mostly known for its capability in statistical analytics and data modeling but it has great capability to data preparation and query. Here I present a sample case which is very much required in our day to day analysis. So I came through a scenario when I have to figure out the exception ... Read moreCount consecutive number of days with condition in R

## R Fuzzy String Match

Here is very cool solution to detect fraud case which is related to same name or same address used to show different entry. While doing the risk consulting, due diligence I've come across the problem when we have to check: Genuine data vs dummy data Employee is also involved as vendor Some relative of employee ... Read moreR Fuzzy String Match

## Confusion Matrix and Cost Matrix

A Confusion Matrix is an important tool to measure accuracy of a classification algorithm. It compares predicted class of an outcome and actual outcome.  Some example of classification. Scenario 1: Credit Risk Based on a credit risk scorecard, application for credit card are classified as “Good” and “Bad”. “Good” indicates applicants paying back dues on ... Read moreConfusion Matrix and Cost Matrix

## Decision Tree: A statistical and analytical tool for effective decisions

A decision tree is a hierarchical or tree like representation of decisions. Decision Tree is a technique to iteratively break input data (or node) into two or more data samples (or nodes).  And this recursive partitioning of input data (or node) continue until it meets specified condition(s). Decision Tree is a method for objective segmentation. ... Read moreDecision Tree: A statistical and analytical tool for effective decisions

## Credit Underwriting: Minimize credit risk losses using Data Science and Analytics

Growth of customers and portfolios is important for any organization and no different for financial institutions such as bank. Banks and financial institutions take prudent measures to minimize the risk specifically at the time of acquisition. Credit underwriting is a process to verify (the document and information provided by the applicants) and assess risk involved ... Read moreCredit Underwriting: Minimize credit risk losses using Data Science and Analytics

## Credit Score: What is it and how is it developed?

When a customer applies for a credit facility (e.g. credit card, personal loan, car/vehicle loan, home/mortgage loan, home equity etc.) at a bank, the bank evaluates credit worthiness of the customer.  What do we mean by credit worthiness? It is assessment by the bank that the customer would be able to meet his/her financial obligations. ... Read moreCredit Score: What is it and how is it developed?

## A BOON but not a Baboon in Credit scoring landscape

Author: Tejasvi Addagada - Infosys Limited The credit scoring and underwriting landscape is undergoing a paradigm shift with the use of enterprise and social data. The banks are planning on utilising the current organizational capabilities including the infrastructure and skills to offset the credit risk associated with borrowers. Scoring models can now use customer consent ... Read moreA BOON but not a Baboon in Credit scoring landscape