⚫Machine Learning: Financial Scoring

The purchasing activities and haINVs of every user become available to all InRecommendations participants (in an encoded, anonymous, and de-personified way). Therefore, the financial scoring ultimately becomes available. It will be used for the following use cases:

• offering an after-payment of up to 100% or a loan to the users who service their liabilities in a reliable way, which can be derived from the historical data and stored in the blockchain;

• offering user-specific financial and insurance products;

• offering the incentivizing discounts only to those customers who are motivated by them;

• avoiding unnecessary discounts for those whose purchasing history suggests that they were buying in other stores without the discounts.

Application of the blockchain technology and the crowdsourced nature of the platform will allow the merchants to achieve a new level of intelligence and economic efficiency previously unaffordable for the small and medium-sized business.