Big Data Analytics

Bootstrapping in Statistics : A Powerful Tool for Inference

Bootstrapping in Statistics : A Powerful Tool for Inference

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Bootstrapping in statistics is a powerful technique that allows us to estimate the properties of a statistic (like its standard error or confidence interval) by repeatedly sampling from the original dataset. It is a resampling technique used to estimate the distribution of a sample statistic by repeatedly resampling with replacement from the original dataset. This […]

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Scorecard model

Scorecard Model in Banking: Enhancing Risk Management and Decision Making

Leave a Comment / Banking Analytics, Big Data Analytics /

A scorecard model is a statistical tool used to assess risk, often in loan applications. It analyzes borrower data like income and credit history, assigning points to different factors. These points are totaled to create a score that predicts the likelihood of loan repayment. Scorecards help lenders make objective decisions and streamline the approval process.

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Stress Testing in Banks in Predictive Model Building

Stress Testing in Predictive Model Building in Banks

Leave a Comment / Banking Analytics, Big Data Analytics /

Stress testing in banks is a technique used to evaluate the resilience of financial systems under adverse conditions. In today’s ever-evolving financial landscape, banks rely heavily on predictive models to navigate risk, optimize operations, and inform strategic decisions. However, the efficacy of predictive models in banking hinges on their ability to withstand adverse conditions and

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Data Wrangling

Data Wrangling : Understanding, Why its Important

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Data wrangling has become the primary process to remain competitive for organizations. Data is the backbone of the digital age, and with growing volume leading to data explosion, the need for effective data handling becomes paramount. Among the essential processes in the realm of data science is Data Wrangling. This article delves into the intricacies

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probability of default

Estimation of Probability of Default

Leave a Comment / Banking Analytics, Big Data Analytics /

Probability of default (PD) offers a glimpse into the borrower’s future: how likely are they to miss payments and ultimately default on their debt? Understanding PD is crucial for banks and investors to individuals making personal loans. It’s the backbone of informed decision-making, helping assess risk, price loans fairly, and allocate capital wisely. When economic

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Zero ETL: A Revolution in Data Integration

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The process of extracting, transforming and loading (ETL) is a fundamental aspect of modern data integration. ETL is used to consolidate data from multiple sources, transform it into a format that can be used for analysis and load it into a target system. However, the ETL process can be time-consuming, complex and error-prone. In recent

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prescriptive analytics

Prescriptive Analytics – toward best solutions

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Prescriptive Analytics may be defined as the branch of analytics which provides guidance on how to make optimal use of data and gain maximum output from it. It is related to both descriptive analytics and predictive analytics, but it helps users to determine the best solution among various possibilities. Descriptive analytics offers BI insights into

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