New York, NY. September 14, 2017 — PIRS Capital, a leading alternative lender specializing in Merchant Cash Advances, has announced the release of their newest credit scoring model known as PIRScore.
Developed by an expert team of 3rd party data analysts and developers, PIRS’s new multi-variable credit model intends to more accurately measure credit risk by taking advantage of best-in-class modeling practices and new machine learning techniques.
“PIRScore opens up lending for more small businesses without raising credit risk” said Andrew Mallinger, COO of PIRS Capital. “PIRScore is working in conjunction with our previous models and lets us look at more data points per borrower than ever before.” Analyzing over fifty statistical algorithms and hundreds of proprietary data points the new model delivers unique insights and predictive behavioral analytics to accurately calculate risk when making funding decisions.
The model further distinguishes itself by leveraging new machine learning AI. PIRScore’s machine learning platform is continuously learning and adapting from live data. “The model improves with every deal, the more data we enter the less variance we see.” said Mallinger.
Over the past decade the Financial Services industry has been fueled by FinTech’s influence. Standard lending practices are being made more efficient via technology and with the release of PIRScore, PIRS Capital aims to be at the forefront of industry innovation.