Credit Scoring

Understanding the importance and mechanics of credit scoring in managing credit risk. — Buy now, pay later. This is a tempting offer made by many financial and retail firms to their customers to increase their customer base. However, both parties need to be aware of the risks when making such credit decisions. It is important for both the lender and the customer that…

Credit score software has become essential to the lending industry in recent years. It allows financial institutions to assess the creditworthiness of potential borrowers quickly and accurately, enabling them to make informed decisions on loan approvals and interest rates. Credit risk decisioning is based on analyzing objective data: an individual’s…

Credit Risks Scoring Using ML-Part 2 Rational/Reasons For Choosing Modeling algorithm? The 5 algorithms are selected for the simple reasons that I am dealing with classification problems. I intend to address the problem of non linearity in credit scoring. In addition the datasets are expected to contain both numeric and…

Nowadays, one can invest in other people’s loans using online peer-to-peer lending platforms such as, for example, Lending Club. In the Lending Club, borrowers with higher credit scores (more trustworthy and less risky) earn lower interest rates on their loans. In comparison, borrowers with lower credit scores (less trustworthy…

Hello everyone!! Welcome to my blog. Today we will be exploring some use cases of the exciting and rapidly evolving world of Machine learning (ML), in the fields of Banking, Finance, and Insurance. …

We’re excited to close out what has been a momentous year for crypto and we’re looking forward to getting into 2023, but before we make the leap, we wanted to look back on what we’ve accomplished and thank you for your continuing interest and support! We’re on a mission to…

“Democracy is the worst form of government — except for all the others that have been tried.” ~ Winston Churchill Options for lenders to adopt custom credit scoring models have never been more prevalent. Today, fully automated credit decisions powered by predictive models (or “AI”) are accessible for organizations of…

Risk-based scorecards measure a person’s probability of defaulting on an unsecured lending product, which creates the basis for credit scoring models. Although these have been well established in the financial system, there is no “silver bullet” for scoring. Risk-based approaches, underwriting policies, and procedures differ from organisation to organisation, and…

Artificial intelligence (AI) has pervaded almost every industry, and banking and financial services stand as no exception. Institutions in the financial sector are employing AI to facilitate data-driven decision-making, automate repetitive tasks, improve data processing speed and accuracy, minimize operational expenses, refine customer service, and more. According to a recent…