Credit scoring using Machine Learning technologies simplifies complex credit risk decisions,
generates real-time predictions and reduces credit risks
The world is reaping the rewards of machine learning, big data, and artificial intelligence. AI-based credit scoring is perhaps the most promising sector for Machine Learning techniques implementation in the finance industry.
Credit scoring is a statistical analysis to determine a person’s or a small, owner-operated business’ creditworthiness. The traditional credit scoring model uses a scorecard method that weights various factors including payment history, debt burden, length of credit history, types of credit used, and recent credit inquiries.
SDK.finance credit scoring algorithm is based on artificial intelligence (AI) and machine learning (ML) technologies. AI scoring is a great solution for credit scoring using more data to an individualized credit score based on factors including current income, employment opportunity, recent credit history, and ability to earn in addition to older credit history. As a result, credit scoring using AI provides more sensitive, personalized credit score assessments based on an array of additional real-time factors.
SDK.finance credit scoring solution allows banks, financial institutions and credit unions to use credit scoring in risk-based pricing in which the terms of a loan, including the interest rate, offered to borrowers are based on the probability of repayment.
AI credit scoring software cuts the time to minutes to verify application and shortens the decision-making process
AI can reduce staff expenses by automating the whole credit risk management process
Prediction of delinquencies before they actually occur is one of the main goals of AI credit risk management software
AI-based credit scoring system continuously monitors the data of the customers. It can provide precise results of creditworthiness of a customer at any given point of time
AI can process a huge amount of information and detect patterns as much error-free as possible.
Intelligent analysis of transactional data help focus on the most pertinent customer information to offer a pre-selection of suitable credit products
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