A Data aggregation software is used to verify borrowers’ documents. Since such tools are connected to several public domains, verification of a borrower’s KYC documents, be it an individual or a Company becomes easily achievable through this tool. In the case of an MSME industry or a retail division of financial institutions, this tool comes handy in streamlining this process. The software aggregates data from a broad range of sources and provides the most useful one. It finds the solution and provides a clear alignment between the lender’s capabilities and the business objectives. This system can easily detect doctored documents which are a major concern for the lenders. Technology firms and Financial Institutions can select from a wide array of data aggregation methods. Following are the key points for which documents are verified by this software.
This system accesses the data of investments made by the borrowers, consolidates them, and provides a clear picture of the borrowers. It integrates with an account aggregator and then with a loan management technology before arriving at the final decision about lending. Lenders verify the borrower documents through this software by three key methods: Reliability, Adaptability, and Security.
That means the lenders thoroughly check how reliable is the borrower, what level of adaptability the borrowers have, and how secure will be the deal. Depending on the financial institutions or technology firms the implementation method of documents is applied. To sustain in a competitive market, being able to determine the financial health of a prospective borrower is paramount. The excellence with which Technology firms or financial institutions gather such data is a key factor that helps derive this.
Data aggregation is the process through which various data are accumulated and sorted scientifically and presented in a summarized format. The data are collected from various sources to combine these to be used in industries, be it in financial institutions or technological industries. In financial institutions, these are used for lending purposes, and in technological industries, these are used for borrowing and also for research and development purposes. This is a very crucial step and data analysis largely depends on the accuracy of data gathered. Therefore, it is highly important to gather high-quality and accurate data. Data aggregation is useful in industries or businesses for taking decisions, pricing, operation, and formulating marketing strategies. Different industries use different types of data. In today’s world of technological advancement, it is imperative that one uses suitable data aggregation software as deemed fit to one’s requirement. There are three integrated steps of data aggregation. These are Data Extraction, Data Transformation, and Data Analysis. Data aggregation also includes statistical data and customer demography. Aggregate data is also found in the data warehouse from which data can be extracted and analyzed as per requirement. While aggregating and using data, privacy, and security must be taken into prime consideration.
Data aggregation software is used to combine data from multiple sources into one to derive new insight and discover new patterns without losing source and lineage. It lays out capabilities for various aggregate measurements such as counting, sum, and average. Data aggregators usually provide the ability to track data lineage. It is not necessary for aggregate to be numeric. Data aggregation can leave a similar effect to independent data elements where commonly identifiable details are merged and replaced with a concise synopsis, singularly representing the data group. Before the aggregation of data, it is important to analyze the data for accuracy. Data aggregation software eases out the whole process of data aggregation.
Data aggregation is not advisable through a manual process as there is every chance of mistakes and wrong information. Quality of data is primal to reach concrete conclusions that enable key decision-making. Therefore, industries must use software for this process. Data aggregation through software helps to identify and extract the right information from multiple sources in real-time to support timely decision-making. Raw data makes analysis a difficult process whereas software transforms the data and makes it suitable for analysis with data normalization. The software can handle a huge volume of data which is not possible manually. Through software, the data aggregation process can be automated. For anything, but the simplest of systems today, one needs to configure data connected to multiple sources and that is possible if one has software at the disposal. Through software, a single connection to the data hub opens access to data from all connected platforms for efficient data management. Getting smarter is always a good thing. Taking advantage of opportunities and making informed decisions have always been a driving force for getting ahead of the line of commerce. Data aggregation software has been a boon for making this possible.
There are several benefits of using data aggregation software as evident below:
Data aggregation software exposed to the greatest number of variables will be the most successful in normalizing financial data across different institutions. Data aggregation software allows to intelligently aggregate, cleanse, augment and store consumer data.