{"title":"Process Approach and Construction of the Database for Non-Core Asset Management in Credit Organizations","authors":"M. K. Shakirov","doi":"10.26907/1562-5419-2021-24-4-710-753","DOIUrl":null,"url":null,"abstract":"A method for building end-to-end management accounting in a division of the Bank’s subdevision specializing in working with non-core assets is proposed. Has been proposed the process approach, an algorithm for building a database for the formation of key performance and control indicators.\nHas been described the key stages of the department's work, the attribute composition of entities (set) arriving, enriched and transmitted at each stage of the department's work. By modeling the process has been built a role model, access and editing rights for employees. Data sources (reference books) for optimization and unification of the process of filling the database (tuple) are proposed. A method of accessing the database in the Power Query Microsoft Excel add-in is proposed, which allows you to collect data from files of all basic data types, process and refine the received data. In the interactive programming environment Jupyter Notebook, mathematical and financial models for data analysis (logistic regression, decision tree and discounted cash flow method) were built based on data in order to predict costs, the timing of asset exposure and make a decision on the optimal cost of putting property on the Bank's balance sheet and selling price. Based on ready-made libraries (matpotlib, seaborn, plotly), options for data visualization for management are proposed. Using the example of the Bank's division, the author describes the positive effects and opportunities that open up to the management of different levels in solving day-to-day tasks and planning the activities of the division. A technical task was proposed for the development of a showcase for the sale of non-core assets on the Bank's website as an environment for the accumulation of external data for making flexible management decisions.","PeriodicalId":262909,"journal":{"name":"Russian Digital Libraries Journal","volume":"105 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Digital Libraries Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26907/1562-5419-2021-24-4-710-753","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A method for building end-to-end management accounting in a division of the Bank’s subdevision specializing in working with non-core assets is proposed. Has been proposed the process approach, an algorithm for building a database for the formation of key performance and control indicators.
Has been described the key stages of the department's work, the attribute composition of entities (set) arriving, enriched and transmitted at each stage of the department's work. By modeling the process has been built a role model, access and editing rights for employees. Data sources (reference books) for optimization and unification of the process of filling the database (tuple) are proposed. A method of accessing the database in the Power Query Microsoft Excel add-in is proposed, which allows you to collect data from files of all basic data types, process and refine the received data. In the interactive programming environment Jupyter Notebook, mathematical and financial models for data analysis (logistic regression, decision tree and discounted cash flow method) were built based on data in order to predict costs, the timing of asset exposure and make a decision on the optimal cost of putting property on the Bank's balance sheet and selling price. Based on ready-made libraries (matpotlib, seaborn, plotly), options for data visualization for management are proposed. Using the example of the Bank's division, the author describes the positive effects and opportunities that open up to the management of different levels in solving day-to-day tasks and planning the activities of the division. A technical task was proposed for the development of a showcase for the sale of non-core assets on the Bank's website as an environment for the accumulation of external data for making flexible management decisions.
提出了在世行专门处理非核心资产的分支机构的一个部门建立端到端管理会计的方法。提出了过程方法,一种建立数据库的算法,形成关键绩效和控制指标。描述了部门工作的关键阶段,实体的属性组成(集)在部门工作的各个阶段到达、丰富和传递。通过对流程进行建模,为员工建立了角色模型、访问权限和编辑权限。提出了用于优化和统一填充数据库(元组)过程的数据源(参考书)。提出了一种在Power Query Microsoft Excel外接程序中访问数据库的方法,该方法允许您从所有基本数据类型的文件中收集数据,并对接收到的数据进行处理和细化。在交互式编程环境Jupyter Notebook中,基于数据建立了用于数据分析的数学和财务模型(逻辑回归、决策树和贴现现金流法),以预测成本、资产暴露时间,并决定将资产纳入银行资产负债表的最优成本和销售价格。在现有库(matpotlib、seaborn、plotly)的基础上,提出了用于管理的数据可视化选项。作者以世行部门为例,描述了在解决日常任务和规划部门活动方面为不同级别的管理人员提供的积极影响和机会。提议了一项技术任务,在世界银行网站上为非核心资产的出售开发一个展示橱窗,作为积累外部数据以作出灵活管理决策的环境。