What Is Data Enrichment, and Why Is It Pivotal for the Financial Stability of Private Organizations

1. What Is Data Enrichment, and Why Is It Pivotal for the Financial Stability of Private Organizations? Taking into account the recent developments in the financial markets and the accelerated international expansion of domestic business, the security of your customer’s data will only be achievable through a complex data enrichment process. What does this term mean? In the context of financial fraud prevention, data enhancement is a comprehensive and ongoing process by which the confidential information you have about your users can be enhanced with the help of external sources. Data enhancement is a means by which you can link the information you already have about your users, identify patterns in the transactional data recorded by your systems, and prevent fraudulent activities before they affect the profitability of your businesses. How does it work? For the most part, the process is based on filling in missing information that may be relevant to fraud prevention purposes. The AI-based tool you use will search external databases, cross- reference your original data with the internally recorded transactional information present on your servers, and perform verifications, in which carefully selected patterns will be analyzed.

2. A Technique to Detect Financial Anomalies Enhanced data is an essential tool in anti-fraud measures, as it provides additional context to recorded data that would usually have passed the vigilance of human operators. Let's say, for example, that one of your clients has placed an order with a higher value than transactions recorded in the past. So far, there's nothing unusual. However, by enriching the transactional data with the help of external databases, it is possible to identify discrepancies indicative of financial fraud. Does the enhanced data now show a mismatch between the user's IP address and its location? If so, the transaction might now be flagged for additional reviews. Enhanced data can increase fraud detection accuracy, significantly reduce the number of false positives, and encourage the identification of the behavioral elements necessary for profiling your users. The more accurate and complex the data to which you have access, the more precise the fraud prevention program you use will be. In addition, data enhancement is necessary to respect AML and KYC regulations and monitor transactions that have been flagged in the past by external governmental entities. Digital data enrichment allows fraud detection programs to make split-second decisions in real-time, can streamline the internal data processing measures implemented by your staff, and, if you are a financial entity, offers a way to respect the regulations imposed by the Bank Secrecy Act. What Is the Primary Role of Enhanced Data? Fraud prevention tools can use enhanced digital data to understand the context and details behind recorded transactions. Data is crucial for the detection of fraud in the public, private, or financial sectors. However, by definition, it is limited and constrained by the time available to decide whether your client’s requests can be approved or not. Data enhancements allow AI- based applications to understand the behavioral elements surrounding transactions and peel back the layers of information that can provide clues as to their legitimacy. Plus, enriched data can be used to fine-tune AI-based AML and KYC algorithms based on specific user and transactional information. Enriched data allows for a more personalized approach to online financial protection, enhances interoperability between the internal tools and systems utilized by your employees, and is a tool to identify emerging threats, even before they are included in the definitions of conventional fraud prevention applications. Data enrichment is all about the continuous update of transactional information based on external database sources. So, it's a crucial tool to be one step ahead of fraudsters and supply machine learning models with new and comprehensive training sets.

3. What Enhanced Data Can Be Used by Fraud Prevention Tools? 53% of online customers want to receive personalized offers tailored to their specific requirements. However, for this to be possible, brands need to utilize enhanced data and create customer profiles that include personalized preference sorting criteria. Are you a company that sells online products? Are you a financial institution? If that's the case, enriched data will be a crucial element in your fight against wide-scale financial fraud. Enriched data has many forms and can be used both for creating custom user profiles and for comparing local information. Plus, it is helpful in determining transactional risk scores. What data can be used for data enhancement? First, the program you are using could make use of internal or external databases to obtain demographic and socioeconomic information relevant to determining the risk score of the transactions analyzed. The AI-based application in use could leverage the name, address, previous income data, and user’s past transactional information to find anomalies in the recorded patterns. Plus, it might use geolocation data and device information to compare the metadata of past transactions with the ones analyzed in the present. Not least, AI-based fraud prevention tools can enhance existing data with information about the user's IP data. A Quintessential Activity for Present-Day Organizations The application you use will update your recorded data in real-time, using information gathered from internal or external sources. It will update the risk score of your service’s users based on changes in transactional behaviors and constantly check if the IP address of the clients matches the location of the transactions. Data enrichment is essential for national or international businesses as it's a way to improve the accuracy and relevance of the financial and transactional information they have at their disposal. AI-based fraud prevention tools are accurate and have a lower false positive rate than conventional tools that do not make use of machine learning. However, to perform as expected, they will need high-quality, comprehensive data.

4. Data enrichment is a necessary process for modern companies and large-scale financial institutions because it enhances the complexity and quality of locally stored transactional information, which can lead to better customer insights, prevent fraud, and improve the quality of commercialized services. In the context of fraud prevention and AML/ KYC regulations, data enhancement is crucial, as it's the only way by which you can improve the accuracy of the utilized anti-fraud tools and keep up-to-date with the financial protection legislation active in your field. Data enhancement is a way to ensure that your transactional information is reliable and up-to-date. It has, therefore, become a procedure used by most companies active on a national level.