Bigdata Analytics​

Big Data Analytics plays a crucial role in the domains of Telcos, Banking, Insurance, eCommerce, and Fintech by leveraging large volumes of data to extract valuable insights and drive business strategies. Empower your business with cutting-edge Big Data Analytics in Malaysia, unlocking actionable insights for strategic decision-making and growth. Enhance Bigdata Analytics rist management in Malaysia with advanced Big Data Analytics, ensuring data-driven insights for effective decision-making and business resilience. Services provided by Global Digital Solutions to each of the following domains:


    • Network Optimization: Analyzing network data to optimize network performance, predict failures, and allocate resources efficiently.
    • Customer Experience Management: Analyzing customer data to personalize offerings, improve customer satisfaction, and reduce churn.
    • Churn Prediction: Analyzing customer behaviour to identify potential churners and implement targeted retention strategies.
    • Revenue Assurance: Analyzing billing data to detect revenue leakages and prevent fraudulent activities


    • Risk Assessment: Analyzing credit data, transaction patterns, and market data to assess creditworthiness, manage risk, and make informed lending decisions.
    • Customer Segmentation: Analyzing customer data to segment customers, understand preferences, and offer personalized products and services.
    • Fraud Detection: Analyzing transactional data to identify fraudulent patterns and prevent financial fraud through advanced anomaly detection techniques.
    • Regulatory Compliance: Analyzing data to ensure compliance with regulatory requirements, implement anti-money laundering measures, and generate accurate reports.


    • Risk Assessment and Underwriting: Analyzing customer and claims data to assess risks, optimize underwriting processes, and determine accurate premiums.
    • Claims Management: Analyzing claims data to automate claims processing, detect fraudulent claims, and streamline settlements.
    • Customer Analytics: Analyzing customer data to understand behaviour, preferences, and improve cross-selling and upselling opportunities.
    • Predictive Analytics: Using historical data to build models for risk forecasting, estimating loss reserves, and optimizing pricing strategies.


    • Customer Analytics: Analyzing customer behaviour, preferences, and purchasing patterns to personalize recommendations and optimize marketing campaigns.
    • Inventory Management: Analyzing sales data, demand patterns, and supply chain data to optimize inventory levels and improve efficiency.
    • Pricing and Promotion Optimization: Analyzing pricing data, competitor data, and customer response to optimize pricing strategies and promotional campaigns.
    • Fraud Detection: Analyzing transactional data to detect fraudulent activities and implement measures to prevent online fraud.


    • Alternative Credit Scoring: Analyzing non-traditional data sources to assess creditworthiness and offer innovative lending solutions.
    • Robo-Advisory and Wealth Management: Analyzing financial data and customer profiles to provide personalized investment advice and automated wealth management.
    • Fraud Prevention: Analyzing transactional data and user behaviour to detect and prevent fraudulent activities in digital financial transactions.
    • Personalized Financial Services: Analyzing customer data and financial goals to offer tailored financial planning and customized financial products.