"Loan sharks" are often difficult to identify because of their covert modus operandi, and the courts need to be prepared quickly to identify suspected cases when faced with such cases;

When the court is dealing with the case at hand, it needs to search for a large number of previously decided facts in similar cases to form a standard of judgement to assist in the decision; and

Through the deep learning of a large number of cases, the Document Check builds an intelligent algorithmic model for false lawsuits, and from the two dimensions of parties and cases, it establishes information monitoring points such as case information, party information, evidence information, etc., and applies semantic analysis of adjudicative documents to identify suspected false lawsuits.

Through the deep learning of a large number of cases, through the judgement of multiple factors in the case, quickly filtering and pushing out similar cases, and forming a decision recommendation;.

Quickly identify "loan" false lawsuits and remove the camouflage coat of P2P enterprises.

Big data research on historical cases can effectively form decision criteria and contribute to standardisation and rigour of decisions.