AI-based Recommender Engine Qorus-NTT DATA Innovation in Insurance Awards 2026

In an era where digitalization is redefining customer expectations, personalization has become a critical success factor. To address this shift, our company pioneered an AI-powered Recommendation Engine within our mobile application in the insurance and private pension sector. The project’s core objective is to deliver real-time, context-aware financial and non-financial offers tailored to each customer, enhancing engagement and maximizing digital channel performance.

The initiative was driven by the limitations of traditional rule-based and static campaigns, which failed to meet rising personalization demands. We developed a scalable, learning-based decision support system that analyzes customers’ financial history, behavioral tendencies, and digital interactions. By combining machine learning algorithms with similarity scoring models, the engine dynamically recommends actions such as contribution increases, lump-sum payments, early maturity closure, online pension sales, and digital fund management usage.

Unlike many market solutions relying on predefined rules, our AI model continuously adapts, optimizing both content and timing. The system was deployed on-premise to ensure full data security and regulatory compliance, a critical requirement in the financial services industry.

The project was executed through close collaboration between Marketing, Analytics, and IT teams. Data engineering, AI modeling, real-time integrations, and automated decision mechanisms were key enablers.

Within the first month of launch, the system achieved a 10% conversion rate and generated over 150 million TL in financial contribution. It also successfully activated previously low-value customer segments. As the sector’s first end-to-end AI-powered recommendation system deployed through digital channels, the project delivers measurable revenue growth while significantly enhancing customer satisfaction and digital maturity.