Xlend
"The main idea of the product is the technological transfer of profits from banks to individual and institutional investors.
But we have a chance to create a decacorn if we solve the main problem - an excess of employees. There are two points. Firstly, entering a new market is very difficult and expensive due to the language barrier.
Secondly, there are too many underwriters and sales managers on traditional crowdlending platforms.
For example, the world's largest crowd-lending platform from the UK, Funding Circle, has more than 300 underwriters and more than 400 sales managers. This is the main reason why they have been unprofitable for a long time. From our point of view, they have an extra 70% of the staff. Automating through AI will lead to a significant increase in competitiveness and can make us a market leader.
We are going to create a fully automated platform that can work in any market from France to the USA, Brazil, Thailand, etc. We will use machine learning to increase investors profits by 10 times, reduce the average loan approval time by 360 times and reduce operating costs by 6 times.
There are two core problems in terms of scalability: sales team and Underwriters team. In Xlend we are going to address both of these problems.
Automatisation of Sales is simpler, we are planning to implement automatic communication with our clients using E-mail and SMS messaging, building chatbots and automatic calling systems which would provide information to our clients.
Automatisation of Risks is much more challenging. Currently risk system is semi-automatic which means that (scoring, underwriting).
We are planning to make it fully automated. After scoring the borrower is taking a completely automated interview and then we use machine learning to analyse all the information."
But we have a chance to create a decacorn if we solve the main problem - an excess of employees. There are two points. Firstly, entering a new market is very difficult and expensive due to the language barrier.
Secondly, there are too many underwriters and sales managers on traditional crowdlending platforms.
For example, the world's largest crowd-lending platform from the UK, Funding Circle, has more than 300 underwriters and more than 400 sales managers. This is the main reason why they have been unprofitable for a long time. From our point of view, they have an extra 70% of the staff. Automating through AI will lead to a significant increase in competitiveness and can make us a market leader.
We are going to create a fully automated platform that can work in any market from France to the USA, Brazil, Thailand, etc. We will use machine learning to increase investors profits by 10 times, reduce the average loan approval time by 360 times and reduce operating costs by 6 times.
There are two core problems in terms of scalability: sales team and Underwriters team. In Xlend we are going to address both of these problems.
Automatisation of Sales is simpler, we are planning to implement automatic communication with our clients using E-mail and SMS messaging, building chatbots and automatic calling systems which would provide information to our clients.
Automatisation of Risks is much more challenging. Currently risk system is semi-automatic which means that (scoring, underwriting).
We are planning to make it fully automated. After scoring the borrower is taking a completely automated interview and then we use machine learning to analyse all the information."
