- The Swedish Fintech is decoding the secret sauce of transactional data, democratising the financial system using advanced machine learning.
- Instantor launches new AI-product to increase efficiency, acceptance and boost profits. Gini uplift of up to 14 percentage points and reduced credit losses by 25 percent.
- Insight algorithms facilitate for risk teams to more precisely calculate a loan applicant’s probability to reimburse the credit applied for.
Instantor, the Swedish fintech company making financial decisions easy, announces Insight.A new product that will transform the way financial organisations assess risk for loan applicants. By using robust machine learning, Insight provides more than 70 predictive features which helps risk teams to identify and understand patterns in historical banking, and can be used to make better risk and opportunity decisions. Instead of having a risk team spending months testing risk models, Insight´s intelligent features will help building the most optimal risk model using the clients own data and can be up and running within a week. This is the first advanced plug and play insights product from the company targeting financial organisations.
Simon Edström, CEO of Instantor, comments: “With the new legislation, PSD2, this is a great way to extract more value for our customers. The big challenge doesn’t lie in accessing data any longer but in the ability to use and understand the data to stay competitive. We are proud to launch Insight as the first step in our new product offering, where focus is on presenting the data in a format optimized for risk assessments to make sure our clients continue to remain ahead of the game.”
As well as validating ID, Instantor´s Insight highlights often overlooked elements of the data that significantly affect risk levels. As a result, this enables faster and more precise scoring models
User tests show that Instantor’s Insight product can improve GINI significantly, up to 14 p.p. for new customers and 6 p.p. for a recurrent customer, boosting profits and reducing credit losses with 25 percent.
Simon Edström, CEO of Instantor, continues: “What is unique about our model is the ability to understand what different transactions mean. E.g., what does a withdrawal of cash from ATMs late at night mean, or if a person frequently gambles does it say they are more likely to default on a loan? With our customers we’ve reviewed millions of applications and together developed Insight to address their unique challenges and formulate how to manage their customers best using machine learning. We can experiment and build different data models, so our clients don’t have to.”
By using robust machine learning, Insight provides more than 70 predictive features and helps risk teams to identify insightful patterns in historical banking, and can be used to make better risk and opportunity decisions. Insight´s intelligent features will help clients to build the most optimal risk model using a client’s own data and can be up and running within a week. As a result, this enables clients to grant more secure credits, deny bad ones, and optimize net lending. User tests show that Instantor’s Insight product can improve GINI significantly, up to 14 p.p. for new customers and 6 p.p. for a recurrent customer, boosting profits and reducing credit losses with 25 percent.