Data aggregation is combining data from various sources and putting them in a single dataset. One common use case for data aggregation is when one organization needs to analyze the results of a survey or another large-scale study conducted by another. A researcher at one organization can take the raw results from the survey and combine them with other datasets to get a better picture of the overall attitudes and behaviors of people in that group. Data aggregation can be done manually by merging multiple datasets or automatically using machine learning algorithms.
The data aggregation and analytics platform are an AI-based software that helps aggregate, organize, analyze and visualize data. This platforms can be used by organizations such as government agencies, private companies, non-profit organizations, etc. It can be used for data collection purposes such as data mining and can also be used for data analysis purposes such as data visualization and business intelligence. Data aggregation platforms can be used by various users, including data scientists, analysts, and researchers. They can use a data aggregation platform to create visualizations and dashboards, which will help them get insights from the data and make better decisions.
What are its features?
- Extraction and curation of data – Data aggregation and analytics platforms help aggregate and curate data from multiple data sources for analysis. It helps to remove redundancies and inconsistencies in the data and provides a comprehensive view of all the relevant information in one place. It can be used across various industries such as healthcare, finance, government, and more..
- In-depth analysis is a critical element of any data aggregation and analytics platform. It allows companies to mine data for insights and gain helpful knowledge about their business operations. In the world of big data, in-depth analysis is critical because it helps companies understand their data’s true meaning. By analyzing data in its original form, you can gain insights that can’t be achieved by only looking at aggregate numbers.
- Real-time decisioning refers to the ability to react quickly and informally to a situation. This is critical for organizations that need to make decisions in real-time, such as emergency services, retail, healthcare and financial services. Real-time decisioning can be facilitated by data aggregation and analytics that provide continuous insight into the data being collected, making it possible for business leaders to react to situations and make informed decisions immediately. In this way, real-time decisioning can drive improved customer experience, lower costs, and increase efficiency.
How it helps to improve risk management for the lender?
- Data aggregation improves risk management by enabling lenders to detect financial distress earlier, thus avoiding costly errors and losses.
- It also helps lenders understand their customers’ financial behavior and improve their lending decisions. As banks face increasing competition, data aggregation has become increasingly important. By analyzing multiple data sources, they can better identify patterns that might indicate problems in their customer base. For example, if several new customers are signing up for credit cards in one neighborhood, it might indicate an increase in credit card fraud in that area.
- Data aggregation helps banks better understand their customers by analyzing social media posts or online reviews. This allows them to determine which customers are likely to default on loans and which are potential loyal customers.
- The platform can help lenders improve their customer service and engagement metrics. It also helps them identify opportunities for additional revenue streams and new business models.
- It is also critical for long-term residential mortgage loans (loans for homes). While most types of loans, such as auto and student loans, tend to have higher default rates, these loans tend to be short-term. And so, lenders must evaluate customer financial history before extending a long-term loan.
PERFIOS data aggregation platform provides a new and powerful way to analyze existing datasets, combining them into one unified view that can help improve risk management. By analyzing trends across multiple datasets, you can better understand which data points most accurately reflect the current state of your business and what areas are most likely to be affected by future changes. In addition, aggregated data can also be used for benchmarking purposes, allowing you to identify areas performing well against competitors and identify opportunities for improvement. By comparing results from different sources, you can identify patterns and trends that may not have been apparent when looking at individual datasets.