ThinCats reveals how data science is boosting lending decisions
THINCATS has revealed how it is using data science and analytics when making lending decisions.
The peer-to-peer business lender has developed a system called the ‘propensity and risk model’ or PRISM.
It takes data from financial performance, business demographics, market positioning and macroeconomics a well as alternative sources such as behavioural and growth indicators, peer-group outperformance and digital footprints to provide a credit grade from weakest to strongest, or one to five.
The model also identifies the likelihood of a business having a funding need over the next 12 months.
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“Data science and analytics is embedded deep within ThinCats’ business principles,” the platform said.
“It is the company’s aim to develop some of the industry’s most predictive models to identify and fund the under-served companies that ultimately drive our economy.
“Information wealth is only valuable when coupled with robust analytics that empowers informed yet fair business decisions.
“ThinCats’ evolutionary statistical models combine a depth of small– and medium-sized enterprise knowledge which stems from decades of industry experience in building risk systems, together with frontier machine learning techniques.”
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