The Results

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The Execution

Our client is a global leader in consumer electronics, home appliances, and mobile communications. One of its subsidiaries, Hi-Care Solutions, specialises in providing maintenance services to customers who have contracted rental services of various LG electronics products, such as air purifiers, water purifiers, and more. Periodic customer management and routine visits are conducted to ensure the seamless operation of all related services following the rental contract agreement.

Recently, a challenge surfaced as several sales representatives unintentionally received bonuses through the contractual process. This has resulted in financial discrepancies and losses for our client. 

Upon conducting a thorough review to identify instances of fraud, it became evident that the manual process was too time-consuming and could not efficiently cover all cases. There was a pressing need for automation to effectively detect fraudulent activities within the workplace.

ADA automated the fraud detection process by building specialised dashboards and implementing AI, resulting in a reduction of fraud incidents.

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The Approach

ADA developed a three-phased solution to effectively address the identified challenges.

In the initial phase, ADA aided in the transformation by constructing custom dashboards and transitioning fraud detection from a manual to an automated process. These dashboards were seamlessly integrated with the client’s base system data, utilising the existing detection logic. 

Next, the detection logic underwent expansion, addressing complexities and volumes of data processing that were beyond the capabilities of human intervention.

In the final and ongoing phase, ADA introduced specialised artificial intelligence (AI) to enhance fraud detection, leveraging the insights derived from the collected data. This approach ensures a robust and adaptive solution to counteract potentially fraudulent activities.

Following that, the PDCA (Plan – Do – Check – Analyse) cycle was initiated. A series of interviews and workshops were held to optimise the solution. This proactive approach allowed for the rapid collection of feedback, facilitating the continuous improvement of both the detection logic and dashboards. The iterative process ensured that adjustments were made swiftly, leading to an increasingly accurate and effective solution.

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