Method and device for backfilling missing data in liquidity period management

Abstract

The invention discloses a method and equipment for backfilling missing data in liquidity period management, which are used for backfilling missing data of a financial business J in a reporting period T, including: dividing Z liquidity period time windows t1 to tZ, and respectively Set the first weight W corresponding to the liquidity period time window t1~tZ 1 ~W Z , wherein, Z≥2; according to whether the accounting dimension of the financial business J is complete and / or whether the management dimension is complete, the corresponding missing unit is set; different missing units are obtained in corresponding ways to obtain missing data, and backfilled to the corresponding Liquidity deadline time window. By applying the technical solution disclosed by the invention, the efficiency of backfilling missing values ​​in the financial system can be improved.

Description

technical field [0001] The invention relates to the technical field of computer applications, in particular to a method and equipment for backfilling missing values. Background technique [0002] Liquidity risk refers to the risk of loss or bankruptcy caused by a financial institution's inability to provide financing for a reduction in liabilities and / or an increase in assets. Liquidity risk is one of the important risks faced by financial institutions and is an important part of the comprehensive risk management system. Especially after the implementation of the Basel three systems, a series of liquidity period management indicators were introduced (liquidity period refers to various Assets and liabilities from the reporting date (data cut-off point) to the time interval to the maturity date) to quantify the liquidity risk of financial institutions. Each financial institution has also created a complete set of risk monitoring indicator system and supporting management tool...

AI Technical Summary

Problems solved by technology

However, this method is basically suitable for the prediction of missing certain (such as sales) data of the same product or commodity, and it is suitable for the situation where there is a certain time period missing in the complete time series, and it is impossible to predict that there are multiple items in the financial institution's account accounting system. The due amount and missing amount of similar products are concentrated, and the missing data may exist in other systems of financial institutions but have not been processed. In this case, if the regression method is used to predict, it will destroy the original authenticity of the management data

[0009] 3) The existing backfilling method for missing data does not yet involve the liquidity period management scenario. This scenario describes the remaining period of the due amount between the due date of the financial business and the reporting date. For financial products, the distribution function between the maturity frequency, maturity amount and time axis is still unknown

Under the existing system, there is no complete process of backfilling missing values ​​in management scenarios, and a method to quantify the missing pool. It is especially difficult to propose a more scientific method for measurement and backfilling of double-missing data in accounting and management dimensions.

At the same time, there will be potential regularity when the staff of financial institutions enter non-standard accounting subjects or product names, and the existing system cannot effectively identify them, and a lot of manpower is required to identify non-standard texts

In addition, the above-mentioned financial and accounting subsidiary period adjustment data also has the scenario of being downloaded offline and then transmitted to relevant personnel for manual processing, and the efficiency of backfilling data is low

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