Customer recognition may be considered by obligors as the identification of customer identification information. However, customer identification goes beyond this; it includes recognising the real beneficiary by focusing on the transactions carried out by the customer, obtaining information about the financial profile of the customer, establishing customer acceptance policies, monitoring customer accounts as long as the business relationship continues, and controlling the compliance of the transactions with the purpose of the transactions.
Whether the transactions performed by their customers are compatible with the information on their customers' profession, commercial activities, business history, financial status, risk profile and fund sources;
* Monitor continuously within the scope of continuous business relationship,
* They are also obliged to take necessary measures to monitor transactions conducted outside the continuous business relationship with a risk-based approach.
Customer identification is a critical step for financial institutions in terms of security and service quality. This process goes beyond customer authentication and enables financial institutions to better understand their customers, assess risks and personalise their services. In this blog post, beyond the important steps in the customer identification process, topics such as customer segmentation, customer behaviour analysis and data analytics will be discussed.
Customer segmentation is a strategy that aims to provide better service by dividing customers into different groups. Financial institutions segment their customers according to criteria such as demographic characteristics, income level, lifestyle, preferences and needs. Through this segmentation, financial institutions can offer more customised products and services to customers, plan marketing strategies more effectively and increase customer satisfaction. Customer segmentation is an important step in the process of customer identification, as more effective measures can be taken by identifying the risks and needs specific to each segment.
Customer Behaviour Analysis
Customer behaviour analysis is a process of examining and understanding customers' financial movements, preferences and tendencies. Through customer behaviour analysis, financial institutions can better understand customers' habits, spending habits, risk tolerance and financial goals. Through this analysis, financial institutions can make better recommendations to customers, offer appropriate products and make risk assessments more accurately. Customer behaviour analysis is an important step in the process of customer identification, because by monitoring customers based on predetermined patterns or anomalies, suspicious or potentially fraudulent activities can be identified.
Data Analytics and Advanced Analysis
Data analytics and advanced analysis methods play an important role in the customer recognition process for financial institutions. These methods enable a better understanding of customers' behaviours and tendencies by analysing large amounts of data. With data analytics and advanced analysis methods, financial institutions can examine customers' past transactions, risk profiles, shopping preferences and other important data. In this way, the customer identification process can be carried out more effectively and suspicious activities can be detected faster. Supported by data analytics, algorithms and artificial intelligence, abnormal behaviour patterns or risky transaction patterns can be identified and more precise results can be achieved in the customer identification process.
Customer identification is important for financial institutions in terms of security, service quality and risk management. In addition to identity verification, steps such as customer segmentation, customer behaviour analysis and data analytics also improve the customer identification process. These steps enable financial institutions to better understand their customers, provide services tailored to their needs and detect criminal activities. The use of technological innovations and data analytics in the customer identification process helps financial institutions to identify their customers effectively and securely.
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