Visual programming technology is reconstructing the methodology of actuarial work, promoting the digital transformation process of the industry by enhancing analysis efficiency and process automation level.

The insurance industry is undergoing a strategic upgrade in technological investment, particularly in the actuarial field. Faced with the dual pressure of complex product structure and cost control, the value of low threshold programming tools (LC/NC) is increasingly prominent. This type of tool effectively bridges the technological gap between actuaries and IT teams, enabling non-professional developers to independently build analytical models and becoming a key element in enhancing the digital competitiveness of enterprises.

Market research shows that current mainstream LC/NC platforms generally have the following core functions:

-Multi source data integration: supports plug and play of database formats such as SQL

-Visual modeling: Implementing complex computational logic through dragging and dropping components

-Process automation: preset standardized workflow templates

-Cloud scalability: Elastic deployment of computing resources

In actuarial practice, a typical application scenario has demonstrated significant benefits: a head analysis platform achieves automatic cleaning and feature extraction of actuarial data through pre-set data connectors. Operators only need to configure data source parameters, and the system can automatically complete format conversion and outlier detection, improving data processing efficiency by more than 60%. This technological paradigm is universal and suitable for iterative optimization of various actuarial models.

Analysis of Efficiency Improvement Path:

1. Innovation in data governance

In the traditional mode, 30% of the actuary's work time is spent on data preprocessing. LC/NC tools use intelligent data pipeline technology to automatically convert diverse heterogeneous data into standard formats, combined with visual quality monitoring dashboards, reducing the data preparation cycle to one-third of the original.

2. Breakthrough in Process Automation

Taking the monthly reserve assessment as an example, after deploying an automated workflow, a life insurance company reduced the report generation time from 72 hours to 8 hours. The system supports dynamic parameter adjustment. When regulatory requirements change, 90% of the model parameters can be updated instantly through the configuration interface without the need for code refactoring.

3. Cloud computing power empowerment

Faced with the pressure testing requirements of millions of policy data, a reinsurance group utilized the grid computing module of the LC/NC platform to reduce the single model computation time from 48 hours to 4 hours. The on-demand allocation mechanism of cloud resources reduces hardware investment costs by 45%.

4. Cross departmental collaborative upgrading

The visualization flowchart of actuarial models deconstructs the technical black box, allowing non-technical departments such as compliance and risk control to intuitively understand the model logic. The practice of a certain property insurance company shows that the model review cycle has been shortened by 40% and the efficiency of cross departmental communication has been improved by 65% as a result.

Industry application challenges and countermeasures:

-Model governance requirements: It is necessary to establish version control and change audit mechanisms

-Talent structure transformation: strengthening the digital thinking training of actuaries

-System integration risk: It is recommended to adopt a gradual implementation path

Prospects for Technological Evolution:

It is expected that in the next three years, functions such as intelligent code generation and natural language modeling will gradually become popular, achieving a breakthrough in the efficiency of actuarial model development. A certain experimental platform has achieved the construction of a survival analysis model through voice commands, with an accuracy rate of 92% of manual modeling.

Practical suggestions:

Enterprises should focus on:

1. Platform scalability and compatibility with existing IT architecture

2. Data security compliance guarantee mechanism

3. Manufacturer's ability to iterate technology and industry experience

4. Adaptability of internal talent development system

Industry observations indicate that institutions that are the first to deploy LC/NC technology have established competitive advantages in product pricing optimization, risk warning timeliness, and other aspects. With the development of regulatory technology, platforms with interpretability of models and audit tracking functions will become the mainstream choice in the market. The actuarial department should seize the technical window period and build a future oriented digital capability system.