The iBooking Platform is a low-code, highly configurable solution designed to streamline the management of external insurance data. It replaces custom coding with dynamic configuration, enabling rapid and flexible integration with diverse data sources from partners and channels.

Core Architecture

The platform features two independent, highly configurable modules:

Input Processing Module

This module handles the ingestion and parsing of incoming data files (CSV, TSV, etc.) from external sources. Key features include:

• Low-Code Configuration: File parsing logic is defined through dynamic configuration, eliminating hardcoded development
• Flexible Execution: Files uploaded to Amazon S3 can be processed via manual triggers or scheduled automated batch jobs
• Automated Processing: Files placed in date-based directories are automatically processed the following day

Output Generation Module

Operating independently from input processing, this module generates standardized reports and data extracts:

• Configuration-Driven Logic: Output rules are set up administratively without code changes
• Dual Trigger Modes: Output batch jobs run on defined schedules (daily/monthly) or can be executed manually
• Multiple Formats: Supports CSV, XLSX, and API-based PDF/Word generation
• Flexible Distribution: Files can be sent via email, SFTP/FTP, or stored in CloudDisk (S3) with download tracking

Key Business Value

The iBooking Platform provides flexibility and efficiency. It empowers insurers to quickly adapt to changing data formats and reporting requirements, significantly reducing development time and operational overhead.

Step-by-Step Guide

Overview

iBooking Platform is a configurable data processing system for insurance companies to handle external partner data and generate reports efficiently through configuration-based operations.

Applicable Roles: Insurance enterprise data administrators, operation managers, claim review specialists.

Step 1: Log in to the Platform

• Operation: Open Chrome 90+, enter platform address, input username/password, click Login

• Goal: Successfully access platform homepage

• Key Node: Check VPN connection if login fails; contact operation team for password reset

  contact: [operation-team-email@insuremo.com]

Step 2: Configure File Parsing Rules

• Operation: Navigate to System → File Parsing Configuration

• Goal: Define how different file formats should be parsed

• Configuration Options:

  • File Format: Select CSV, TSV, or XLSX

  • Delimiter: Configure field separator (comma, tab, etc.)

  • Header Row: Specify if file contains header row

  • Column Mapping: Map file columns to database fields

  • Validation Rules: Set data validation criteria

• Key Node: Test configuration with sample files before production use

Step 3: Upload Input Files

• Operation: Navigate to Data → File Upload

• Supported Formats: CSV, TSV, XLSX

• File Naming Conventions: Follow specific naming patterns (e.g., AUKC.csv, CWF_受付一覧.csv, There are no special rules for file naming)

• Upload Location: S3 bucket, Configurable for different S3 or directory structures, for example: clouddisk://[bucket-name]/[path]/

• Goal: Upload compliant data files to designated location

• Key Node: Ensure files are uploaded to correct date directory for automatic processing

Step 4: Configure Batch Processing Jobs

• Operation: Navigate to System → Batch Job Configuration

• Job Types:

  • Input Jobs (Input01-Input08): Process uploaded files

  • Output Jobs (Output01-Output08): Generate output reports

• Scheduling Options:

  • Manual Trigger: Execute jobs on-demand

    • Scheduled: Set daily/monthly execution times

    • Event-Driven: Trigger based on file upload events

• Notification Settings: Configure email alerts for job completion/failure

• Goal: Set up automated data processing workflows

• Key Node: Test job configurations in test environment before production deployment

Step 5: Monitor Processing Status

• Operation: Navigate to System → Batch History

• View Options:

  • Execution Status: Success, failure, in-progress

  • Processing Times: Job duration and performance metrics

  • Error Details: View detailed error messages for troubleshooting

    To view errors, you can log in to portal → search for monitor → use traceid to query error log

• Goal: Monitor batch job execution and identify issues

• Key Node: Set up proactive monitoring for critical jobs

Step 6: Configure Output Generation

• Operation: Navigate to System → Output Configuration

• Data Sources:

  • DataMO Subjects: Select datasets with CUST_ prefix

  • DataMO Topics: Choose topics with domain_ or mart_ prefix

• Output Options:

  • File Format: CSV, XLSX, or PDF via API integration

  • Column Selection: Choose which columns to include

  • Formatting: Configure date, number, and text formats

  • Filtering: Apply business-specific filters

  • Sorting: Set output sorting order

• Distribution Channels:

  • Email: Send to specified recipients
  • File Transfer: SFTP/FTP/FTPS to external servers
  • Cloud Storage: Store in CloudDisk (S3)

• Goal: Configure automated report generation and distribution

• Key Node: Test output formats and distribution channels

Step 7: Access and Download Output Files

• Operation: Navigate to Output → Output Files

• Search Options: Filter by date, file type, job type

• Download: Click Download to save files locally

• Download History: View complete audit trail of file access

• Goal: Retrieve generated output files for business use

• Key Node: Classify and archive reports according to enterprise regulations

Step 8: Data Search and Management

• Operation: Navigate to Policy → Policy Info Enquiry

• Search Criteria: Policy Number, Campaign Code, Policyholder Name, etc.

• Data Validation: Review and manage pending policies requiring attention

• Administrative Actions: Correct or drop invalid records

• Goal: Access and manage policy data

• Key Node: Regular data quality checks to maintain system integrity

Key Configuration Points

File Path Conventions

Input Configuration Example:
clouddisk://[bucket-name]/[path]/

where clouddisk is the protocol and [bucket-name] is the bucket name.

Output Configuration Example:
clouddisk://[bucket-name]/[path]/[subdirectory]

Batch Job Types

• Input01-Input08: File processing jobs (daily/monthly)

• Output01-Output07: Monthly report generation (runs on 2nd day of month)

• Output08: Daily data output (runs daily at 06:00)

Business Date Handling

• Monthly outputs process previous month’s data

• Claims outputs (Output02-Output03) use only month-end data

Common Tasks

Daily Operation

1. Upload previous day’s partner files to S3

2. Verify automatic processing completed successfully

3. Download and distribute required output reports

4. Monitor for any data quality issues

Monthly Reporting

1. Ensure all daily files for previous month are processed

2. Trigger monthly output batches on 2nd of month

3. Distribute monthly reports to stakeholders

Support Resources

• Batch History: Track all processing jobs

• Download History: Monitor file access

• Error Logs: Troubleshoot processing issues

• User Manual: Detailed feature documentation

Permission Control (URP)

• Each output configuration can be individually controlled with permissions
• Configure OutputConfig permissions: Log in to insuremo → url → permission
• PermissionCode rule: report type + Config Code (for example, if the code for a configuration is 1001, the permissionCode needs to be defined as: [report_type]_[config_code])

Customization Development Guide

Development Environment Setup

Prerequisites

• Install IntelliJ IDEA (recommended version 2023 or above)
• JDK 17 or higher
• Install git
• Install Maven
• Install Node.js (18.12.1 or higher)
• Install Yarn 1.22.5
• Pull the latest main branch code from the iBooking code repository
• Use the command git checkout -b feature/[feature-name] to create a development branch

Node Service Startup

Configure npm Registry

Create .npmrc file in user home directory:

registry=http://repo.insuremo.com/artifactory/api/npm/npm-all
_auth=[your-auth-token]
always-auth=true
email=[your-email@domain.com]

To create _auth token for .npmrc, use:

curl -u [username]:[password] http://repo.insuremo.com/artifactory/api/npm/auth

Initialize Workspace

yarn install

If timeout occurs, try:

yarn install --network-timeout 1000000000

Start Services

# Start node service
cd node-service
yarn start

# Start web application
cd web
yarn start

Backend Service Startup

Configure Maven

1. Add the bin directory under Maven installation directory to PATH environment variable
2. Verify installation: mvn -v
3. Modify the settings.xml file in the conf folder under Maven installation directory
4. Configure Maven in IntelliJ IDEA

Set VM Parameters

-Dinsuremo_access_token="Bearer [YourPAT]"
-Dinsuremo_gw_url=https://ptdev-gw.insuremo.com
-DTENANT_CODE=[tenantCode]
-Dnode_service_url=http://localhost:3721
-Dcontext_path=/api/[tenantCode]/ibooking-service

Run Startup Class

Execute the main application class in IntelliJ IDEA.

Code Development Standards

REST API Standards

Path Naming Convention

API Return Format

API Exception Handling

Transaction Management

Pagination Query

API Authorization

Service Layer Standards

Service Exception Handling

Data Access Object (DAO) Standards

Unified Query Solution

Recommended to use JPA Specification:

Specification<EntityClass> spec = new Specification<EntityClass>() {
    @Override
    public Predicate toPredicate(Root<EntityClass> root, CriteriaQuery<?> query, CriteriaBuilder criteriaBuilder) {
        List<Predicate> predicates = new ArrayList<>();
        if (StringUtils.hasText(fieldName)) {
            Predicate predicate = criteriaBuilder.equal(
                criteriaBuilder.upper(root.get("fieldName")),
                fieldName.toUpperCase()
            );
            predicates.add(predicate);
        }
        return criteriaBuilder.and(predicates.toArray(new Predicate[0]));
    }
};

Page<EntityClass> results = repository.findAll(spec, pageable);

For simple queries (1-2 parameters), use JPA native SQL:

@Entity
interface Repository extends JpaRepository<Entity, Long>, JpaSpecificationExecutor<Entity> {
    @Query(value = "SELECT column1, column2 FROM table_name", nativeQuery = true)
    public List<Object[]> customQuery();
}

For complex cross-table queries, use JdbcTemplate:

public Page<ResultSet> query(String fileName, Long ruleId, PageRequest pageable) {
    StringBuilder dynamicSql = new StringBuilder();
    dynamicSql.append("SELECT t1.col1, t2.col2 FROM table1 t1, table2 t2 WHERE t1.id = t2.id");

    List params = new ArrayList();
    if (StringUtils.hasText(fileName)) {
        dynamicSql.append(" AND upper(t1.file_name) LIKE ?");
        params.add("%" + fileName.toUpperCase() + "%");
    }

    // Execute query and return paginated results
    // ...
}

JPA Null Value Handling