Small and Medium Enterprises(SMEs) make up a large portion of businesses around the world, over two third of these don’t have ready access to financing or credit. Over the years there has been considerable effort made to solve this problem through the means of peer to peer lending, crowd funding etc but the credit gap left still remain at $2 trillion dollars.

Generally the common pain points reported by SME owners are:

Paperwork: post 2008 and the global financial crisis, lending has gotten stricter, with more rigid documentation requirements. Banks want to assess each and every single detail and as such no stone goes unturned. And as such It is usually timely to collect the necessary documentation.

Credit Score Requirements: in recent times there has been an increase in the use of a FICO SBSS score, this is a small business credit score used for loans up to $1 Million. These scores can be a useful means of assessing credit worthiness for preexisting businesses with a history of borrowing and repaying loans but for newer businesses especially those with no credit history. A lot of banks even set SBSS minimums meaning your loan application can get automatically rejected.

Personal Guarantee: a majority of lenders require a personal gurantee on business loans, this means holding you responsible for the debt if your business is not able to repay it. This may mean using things like your house, your car etc as collateral for your business loan. This requirement serves to deter a lot of SMEs looking to take out a line of credit, or get a loan as it significantly increases the risks associated as a borrower.

Approval time: when it comes to lending for SMEs banks are known to take a long time to decide whether to extend the loan, sometime to the tune of 30 days. This can be especially costly when the capital need is time sensitive.

Now that we’ve seen the issues faced by SMEs, any solution trying to address the funding needs of SMEs needs to at a basic level address the pain points above.

There have been attempts at devising different solutions to address this problem but a common barrier lies within regulation and borders, regular lending solutions aren’t necessarily border less and as such need to operate within a set jurisdiction or region. As opposed to cryptocurrencies which are at this moment border less and lawless, not bound to any jurisdiction, region or country specific regulation.

AI and Blockchain Driven Lending

Matrix blockchain can be used to enable blockchain backed p2p lending with low transaction times and speeds. Intelligent smart contracts can be used to set out terms and loan conditions, and then instantaneously release funds to the borrower.

By using Matrix’s blockchain the need for lengthy forms and folders of documentation can also be removed, by storing all necessary information such as preexisting transactions and on the blockchain lenders can readily access and view the details of the borrower in the click of a button.

Matrix’s AI algorithm not only be used to create a new type of lending service, it can also be used to improve upon existing banking and lender structures. Matrix’s AI algorithm can be used to automate front to back end workflow. By automating common repetitive tasks we can increase the efficiency as well as the effectiveness of loan providers, making sure that it can be a quick and smooth experience for small and medium enterprises looking for a loan.

Data is the driving force for good AI systems, and as such Matrix’s Artificial Intelligence algorithm can make use of big data to determine and create more comprehensive borrower credit profile per loan requested. This can not only prove beneficial for SMEs, but for lenders as well as it can allow for better decision and risk management. Matrix’s Bayesian inference algorithm can also be leveraged to determine the risk of credit events occurring for different types of SMEs.

The combination of these features allows for lenders to have a better understanding of a SME’s credit worthiness and risk, by significantly improving the detection of credit defaults and non repayments in a timely manner, these systems can overall result in fewer loan rejections as well as improved credit decisions.