Intelligent case division method based on case prediction value and specialist portrait

Abstract

The invention discloses an intelligent case division method based on case prediction values and specialist portraits. The method comprises the following steps: evaluating the value of each to-be-allocated case; conducting portrayal evaluation on the specialists based on the influence factors, and then obtaining the appropriate collection case value of each specialist; and according to the value of the to-be-allocated cases and the suitable collection case value of each specialist, allocating the cases to each specialist, specifically, sequentially allocating several cases with the highest value in the to-be-allocated cases to each specialist, distributing several cases with the lowest value in the cases to be distributed to each specialist in an inverted order, distributing several cases with the highest value in the remaining cases to be distributed to each specialist in an inverted order, sequentially distributing several cases with the lowest value in the remaining cases to be distributed in the step S3 to each specialist, and repeating the above steps until the to-be-allocated cases are allocated. The case value, the specialist ability and the unique case division system are combined, the case distribution efficiency is effectively improved, and the case operation income is maximized.

Description

technical field [0001] The invention relates to the field of computer application technology, in particular to an intelligent case division method based on case prediction value and commissioner portrait. Background technique [0002] Collection is a way for the lending industry to recover overdue non-performing assets, usually by the creditor itself or entrusting a third party to recover the arrears. Standardized debt collection is a product of the maturing financial market and an important part of financial risk control. One of the core processes of collection is case division, that is, assigning a batch of cases to the operating specialist team. [0003] At present, the collection and division of cases in the industry is relatively simple, and the average distribution or distribution based on proportion is generally adopted. This distribution method is too extensive and cannot accurately evaluate the value of the case and the defects of the commissioner's ability. Some ...

AI Technical Summary

Problems solved by technology

[0003] At present, the industry's relatively simple collection and division of cases generally adopts average distribution or distribution based on proportion. This distribution method is too extensive and cannot accurately evaluate the value of the case and the defects of the commissioner's ability.

Some complex systems use multiple dimensions to set divisional policy rules. For example, the divisional policy dimensions include: overdue periods / days, account age, business type, city / region, commissioned case amount, etc. Dimensions, but this classification The case method does not fully consider the matching of the specialist's ability. Therefore, the existing collection methods generally have the defects of being unable to refine and quantify matching cases and specialists, effectively using resources and maximizing collection benefits.

Images