Bank customer manager point processing method and system based on performance model

Abstract

The invention discloses a bank customer manager point processing method and system based on a performance model. The processing method comprises the following steps: collecting performance data of a customer manager; performing cleaning and normalization processing on the performance data, and extracting key performance features; constructing and training a performance model for estimating performance points of the customer manager; capturing and processing performance data in real time, and dynamically calculating points of a customer manager; summarizing credits obtained by the customer manager from the plurality of business lines to obtain a total credits; and providing a personalized reward scheme for a customer manager according to the total points and personal preferences. Based on the flexibility of a large language model, the assessment indexes are dynamically adjusted to adapt to market changes and customer demands.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to a method and system for processing bank account manager points based on a performance model. Background Art

[0002] In the current financial industry, account managers are the key link between banks and customers, and their work performance has a direct and profound impact on the bank's service quality and market competitiveness. With the continuous development of the financial industry, banks are paying more and more attention to the performance appraisal and incentive mechanism of account managers. More and more banks are beginning to explore new performance appraisal methods, such as introducing key performance indicators (KPIs) and 360-degree feedback evaluations, in order to more comprehensively evaluate the work performance of account managers, promote the further expansion of banking business and improve customer satisfaction. Today, with the rise and maturity of big data analysis and big language model technology, new ideas and methods are provided for the performance appraisal of bank account managers.

[0003] Traditional methods of evaluating the performance of account managers rely on subjective evaluations, such as the impression of superiors, feedback from colleagues, and evaluations from customers. Although this method can reflect the service attitude and ability of account managers to a certain extent, it lacks objective and quantifiable standards, which often leads to doubts about the fairness and accuracy of the evaluation results. For example, in some cases, the performance evaluation of account managers may be affected by their relationship with superiors or colleagues, rather than being based entirely on their work performance.

[0004] The existing performance appraisal system often focuses too much on short-term results, such as sales and new account openings, while ignoring the long-term investment and performance of account managers in maintaining customer relationships, mastering product knowledge, understanding market trends, etc. This short-sighted appraisal method may cause account managers to pursue short-term goals too much and ignore the importance of establishing long-term and stable relationships with customers.

[0005] The performance evaluation of bank account managers is mainly done by manually collecting performance data of account managers, such as the number of customers, business volume, customer satisfaction, etc., and then calculating and evaluating them according to pre-set evaluation indicators. Points rewards are usually calculated manually, which lacks accuracy and timeliness. Summary of the invention

[0006] In view of the above problems, the present invention is proposed to provide a method and system for processing bank account manager points based on a performance model to overcome the above problems or at least partially solve the above problems.

[0007] According to one aspect of the present invention, a method for processing bank account manager points based on a performance model is provided, the processing method comprising:

[0008] Collect performance data from account managers;

[0009] Cleaning and normalizing the performance data and extracting key performance features;

[0010] Build and train a performance model to estimate the account manager's performance score;

[0011] Capture and process performance data in real time and dynamically calculate account managers’ points;

[0012] Summarize the points earned by the account manager from multiple business lines to obtain the total points;

[0013] Provide account managers with a personalized rewards program based on said point totals and personal preferences.

[0014] Optionally, the collecting of the account manager's performance data specifically includes: collecting the account manager's performance data from multiple business systems of the bank and external data sources.

[0015] Optionally, the collecting of the account manager's performance data from the bank's multiple business systems and external data sources specifically includes:

[0016] Integrate the core data of multiple business areas of the bank, including core business systems, customer relationship management systems (CRM) and financial management systems, support real-time and periodic data extraction, and cover key dimensions such as account managers’ sales performance, customer satisfaction feedback, number of new customers and business growth rate;

[0017] Through a rigorous data cleaning and verification process, advanced algorithms are used to identify and eliminate duplicate, erroneous and invalid data.

[0018] Optionally, the cleaning and normalizing of the performance data and extracting key performance features specifically include:

[0019] Use data cleaning techniques to remove noise and outliers from raw data;

[0020] Normalization is performed to eliminate the dimensional differences between different performance indicators and ensure the comparability of various indicators on the same dimension;

[0021] In the key performance feature extraction stage, statistical principles, machine learning algorithms and business knowledge are comprehensively applied to identify the core features that are closely related to account managers' performance.

[0022] Optionally, the step of constructing and training a performance model for estimating the performance points of the account manager specifically includes:

[0023] Model framework to build performance models;

[0024] By comparing the performance of multiple machine learning algorithms, we tailor performance models for various business scenarios and use neural networks to achieve customer segmentation and personalized recommendations for wealth management services;

[0025] During model training, multiple rounds of iteration and optimization are performed using deeply processed performance data;

[0026] Introduce regularization technology to prevent model overfitting;

[0027] Establish a performance model evaluation and optimization mechanism, and timely adjust the performance model parameters and structure through regular evaluation and verification.

[0028] Optionally, the real-time capture and processing of performance data and dynamic calculation of the account manager's points specifically include:

[0029] Establish real-time integral feedback and dynamic adjustment mechanism;

[0030] The mechanism can instantly capture new performance data and input it into the score prediction model to calculate the latest score value of the account manager, which directly reflects the performance of business activities;

[0031] Relying on efficient data processing capabilities and accurate model algorithms;

[0032] A strict points review and adjustment process has been established to check and handle abnormal points to ensure the fairness of the points results and customer satisfaction;

[0033] A scientific, efficient and fair bank account manager points management system has been established.

[0034] A bank account manager points processing system based on a performance model, using the bank account manager points processing method based on a performance model, the points processing system includes:

[0035] Data receiving module, used to collect performance data of account managers;

[0036] The score prediction module is used to clean and normalize the performance data and extract key performance features; build and train a performance model to estimate the performance score of the account manager; capture and process the performance data in real time and dynamically calculate the score of the account manager;

[0037] The points summary module is used to summarize the points obtained by the account manager from multiple business lines to obtain the total points;

[0038] The total points application module is used to provide personalized reward programs for account managers based on the total points and personal preferences.

[0039] The present invention provides a bank account manager score processing method and system based on a performance model, the processing method comprising: collecting the account manager's performance data; cleaning and normalizing the performance data, and extracting key performance features; building and training a performance model for estimating the account manager's performance score; capturing and processing the performance data in real time, and dynamically calculating the account manager's score; summarizing the points obtained by the account manager from multiple business lines to obtain the total score; and providing the account manager with a personalized reward plan based on the total score and personal preferences. Based on the flexibility of the large language model, the assessment indicators are dynamically adjusted to adapt to market changes and customer needs.

[0040] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0042] Figure 1 A flow chart of a method for processing bank account manager points based on a performance model provided by an embodiment of the present invention;

[0043] Figure 2 A block diagram of a bank account manager points processing system based on a performance model provided by an embodiment of the present invention;

[0044] Figure 3 A schematic diagram of the device structure of the hardware operating environment of the terminal device involved in the implementation scheme provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0046] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0047] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0048] like Figure 1 As shown, the present invention proposes a bank account manager points processing method based on a performance model, which motivates and retains high-performance account managers by refining the performance data of account managers, thereby improving the overall business efficiency of the bank. The core of this method is to build a points issuance prediction model, which acts on the performance data of account managers to achieve accurate issuance and allocation of points.

[0049] Comprehensive collection of performance data, including:

[0050] In building a bank account manager score management system based on performance evaluation, the first task is to comprehensively gather comprehensive performance data. This step involves integrating the core data of multiple business areas of the bank, including but not limited to core business systems, customer relationship management systems (CRM) and financial management systems, to ensure the comprehensiveness and accuracy of performance indicators. To achieve this goal, we have deployed an efficient data collection mechanism to support real-time and periodic data extraction to cover key dimensions such as account managers' sales performance, customer satisfaction feedback, number of new customers and business growth rate. In addition, through a strict data cleaning and verification process, advanced algorithms are used to identify and eliminate duplicate, erroneous and invalid data to ensure data purity and consistency.

[0051] Fine feature extraction and preprocessing, including:

[0052] Advanced data cleaning technology is used to remove noise and outliers in the original data to improve data accuracy; at the same time, normalization is implemented to eliminate the dimensional differences between different performance indicators to ensure the comparability of various indicators in the same dimension. In the key performance feature extraction stage, statistical principles, machine learning algorithms and business knowledge are used in combination to successfully identify the core features closely related to the performance of account managers, providing strong support for the construction and optimization of the score prediction model.

[0053] Build and train performance models, including:

[0054] In order to meet the actual needs of various business lines of the bank, a suitable model framework was selected to build a performance model. By comparing the performance of multiple machine learning algorithms, performance models were tailored for different business scenarios, and neural networks were used to achieve customer segmentation and personalized recommendations for wealth management business. During the model training process, multiple rounds of iteration and optimization were performed using deeply processed performance data to improve the model's prediction accuracy and generalization ability. At the same time, regularization and other technologies were introduced to prevent model overfitting and ensure the stability of prediction results. A performance model evaluation and optimization mechanism was established, and through regular evaluation and verification, performance model parameters and structure were adjusted in a timely manner to adapt to business development and market changes.

[0055] Real-time integral calculation and dynamic adjustment, including:

[0056] In order to ensure the timeliness and flexibility of the points management system, a real-time points feedback and dynamic adjustment mechanism has been established. This mechanism can instantly capture newly generated performance data and input it into the points prediction model to quickly calculate the latest points value of the account manager, which directly reflects the performance of their business activities. This goal relies on efficient data processing capabilities and accurate model algorithms. At the same time, a strict points review and adjustment process has been established to verify and handle abnormal points to ensure the fairness of the points results and customer satisfaction. The innovation and application of this series of mechanisms have jointly built a scientific, efficient and fair bank account manager points management system, providing strong support for the bank's performance evaluation and business development.

[0057] like Figure 2 As shown, the bank account manager points processing device includes:

[0058] The data receiving module comprises:

[0059] The data receiving module is the core entrance of the device of the present invention, which is responsible for collecting the performance data of the account manager from various business lines of the bank. The module has high compatibility, real-time processing capability and data security guarantee, ensuring the integrity and timeliness of the data.

[0060] The integral prediction module includes:

[0061] The points prediction module uses a performance model formed by a deep learning model and an optimization algorithm to process and analyze the performance data of the account manager and predict the points he or she should receive. This module is the core link in the points processing process, ensuring the fairness and accuracy of the points.

[0062] Points summary module, including:

[0063] The points summary module is responsible for summarizing the points data from different business lines and calculating the total points of the account manager. This module ensures the accuracy and timeliness of the points summary through efficient data processing and algorithm support.

[0064] Points application module, including:

[0065] The points application module intelligently recommends personalized reward plans based on the total points value and personal preferences of the account manager, and provides an instant reward distribution interface. This module is the export of the points management system, ensuring that the points can be effectively converted into incentives for the account manager.

[0066] like Figure 3 As shown, the bank account manager points processing device includes:

[0067] In terms of computer equipment, the configuration requirements required by the present invention mainly focus on processing power, storage capacity and network connection speed. Given that the present invention involves a large amount of data collection, model training and real-time calculation, the computer equipment needs to have a powerful central processing unit (CPU) and graphics processing unit (GPU) to support efficient mathematical operations and deep learning model training. At the same time, large-capacity memory and high-speed solid-state drives (SSDs) are essential for fast reading and writing of data, especially when processing massive performance data of bank account managers.

[0068] In the present invention, the role of the computer device is not limited to data processing and model training. It is also a key tool for achieving real-time integral calculation and dynamic adjustment of model parameters. Through efficient computing power, the device can instantly respond to the latest performance data of the bank account manager, thereby quickly updating the integral value and dynamically adjusting the parameters and weights of the model according to the preset algorithm.

[0069] Beneficial effects:

[0070] The present invention improves the automation level of data processing and reduces human errors by introducing advanced algorithms and models, thereby ensuring the efficiency and accuracy of integration processing.

[0071] The present invention ensures that the performance points of each account manager can be fairly and accurately calculated and rewarded by constructing an open and transparent points processing system.

[0072] The system of the present invention needs to make use of the flexibility of the large language model to dynamically adjust the assessment indicators according to market changes and customer needs, so that the performance assessment is more targeted, can comprehensively and accurately reflect the work performance of the account manager, and effectively motivate them to improve their business level.

[0073] The system of the present invention can realize automatic calculation and verification of points, so that account managers can timely understand their own points and obtain corresponding rewards, improve the incentive effect of point rewards, and enhance the work enthusiasm of account managers.

[0074] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A bank account manager points processing method based on a performance model, characterized in that: The processing method comprises: Collect performance data from account managers; Cleaning and normalizing the performance data and extracting key performance features; Build and train a performance model to estimate the account manager's performance score; Capture and process performance data in real time and dynamically calculate account managers’ points; Summarize the points earned by the account manager from multiple business lines to obtain the total points; Provide account managers with a personalized rewards program based on said point totals and personal preferences.

2. A method for processing bank account manager points based on a performance model according to claim 1, characterized in that: The collecting of the account manager's performance data specifically includes: collecting the account manager's performance data from multiple business systems of the bank and external data sources.

3. A method for processing bank account manager points based on a performance model according to claim 2, characterized in that: The collection of account manager performance data from multiple business systems and external data sources of the bank specifically includes: Integrate the core data of multiple business areas of the bank, including core business systems, customer relationship management systems (CRM) and financial management systems, support real-time and periodic data extraction, and cover key dimensions such as account managers’ sales performance, customer satisfaction feedback, number of new customers and business growth rate; Through a rigorous data cleaning and verification process, advanced algorithms are used to identify and eliminate duplicate, erroneous and invalid data.

4. A method for processing bank account manager points based on a performance model according to claim 1, characterized in that: The cleaning and normalization of the performance data and the extraction of key performance features specifically include: Use data cleaning techniques to remove noise and outliers from raw data; Normalization is performed to eliminate the dimensional differences between different performance indicators and ensure the comparability of various indicators on the same dimension; In the key performance feature extraction stage, statistical principles, machine learning algorithms and business knowledge are comprehensively applied to identify the core features that are closely related to account managers' performance.

5. A method for processing bank account manager points based on a performance model according to claim 1, characterized in that: The construction and training of a performance model for estimating the performance score of the account manager specifically includes: Model framework to build performance models; By comparing the performance of multiple machine learning algorithms, we tailor performance models for various business scenarios and use neural networks to achieve customer segmentation and personalized recommendations for wealth management services; During model training, multiple rounds of iteration and optimization are performed using deeply processed performance data; Introduce regularization technology to prevent model overfitting; Establish a performance model evaluation and optimization mechanism, and timely adjust the performance model parameters and structure through regular evaluation and verification.

6. A method for processing bank account manager points based on a performance model according to claim 1, characterized in that: The real-time capture and processing of performance data and dynamic calculation of account manager points specifically include: Establish real-time points feedback and dynamic adjustment mechanism; The mechanism can instantly capture new performance data and input it into the score prediction model to calculate the latest score value of the account manager, which directly reflects the performance of business activities; Relying on efficient data processing capabilities and accurate model algorithms; A strict points review and adjustment process has been established to check and handle abnormal points to ensure the fairness of the points results and customer satisfaction; A scientific, efficient and fair bank account manager points management system has been established.

7. A bank account manager score processing system based on a performance model, using a bank account manager score processing method based on a performance model as described in any one of claims 1 to 6, characterized in that: The points processing system comprises: Data receiving module, used to collect performance data of account managers; The score prediction module is used to clean and normalize the performance data and extract key performance features; build and train a performance model to estimate the performance score of the account manager; capture and process the performance data in real time and dynamically calculate the score of the account manager; The points summary module is used to summarize the points obtained by the account manager from multiple business lines to obtain the total points; The total points application module is used to provide personalized reward programs for account managers based on the total points and personal preferences.

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