Data Aggregation and It's Crucial Role in Lending

Data is a valuable asset that provides essential insights, drives informed decisions, and allows businesses to innovate. By analyzing data, organizations can identify trends, optimize processes, and enhance customer experiences, ultimately leading to improved performance and competitiveness in today's data-driven world. But without the proper means of compiling the information, it can be hard to understand what to do with it. That's where data aggregation comes in. 

Data aggregation involves collecting and collating data from multiple sources to draw high-level insights for better decision-making. This is particularly useful for lenders where data overload is common. In fact, by cracking open access to consumers' financial data, financial data aggregators have made open banking and open finance possible.

Continue reading to learn more about the basics of data aggregation, how it works, why you should use it, and how to automate it easily.

What is data aggregation?

Data aggregation is the process of collecting and summarizing information from different sources to provide a comprehensive view or dataset. This practice is commonly used in various fields, such as business, finance, health care, and research, to analyze trends, make informed decisions, and derive insights that might not be apparent from isolated data sets.

In essence, data aggregation involves the following steps:

1. Data Collection: Gathering information from various sources, including internal databases, external datasets, social media platforms, sensors, etc.
2. Data Processing: Cleaning and transforming the collected data to ensure consistency, accuracy, and reliability.
3. Data Summarization: Organizing and summarizing the processed data into a structured format that can be easily analyzed.
4. Data Analysis: Applying statistical or other analytical methods to extract insights and trends from the aggregated data.

Data aggregation can be performed manually or through automated tools and software. The aggregated data can then be used for reporting, visualization, and analysis, providing a holistic view of the examined topic or issue.

By consolidating information from multiple sources, data aggregation allows for more comprehensive analysis and can lead to more informed decision-making, improved operational efficiency, and enhanced strategic planning.

When should you use data aggregation?

Data aggregation can be used in a variety of ways to simplify what can otherwise be a tedious and impossible amount of information. Here are some situations when data aggregation is particularly useful:

1. Reporting and Visualization: To provide a consolidated view of data from different sources, making it easier to generate reports and visualize information for better understanding and communication.
2. Performance Analysis: To assess the performance of a business or a specific process by aggregating data from different departments or systems.
3. Trend Analysis and Forecasting: To identify trends and make future predictions by combining historical data from various sources.
4. Customer Insight: To gain a deeper understanding of customer behavior and preferences by aggregating data from customer touchpoints, such as sales, customer service, and social media interactions.
5. Market Research: To gather comprehensive market insights by aggregating data from various market research sources, competitor analysis, and industry reports.
6. Risk Management: To assess and mitigate risks by aggregating data from internal assessments and external risk factors.
7. Compliance and Regulation: To ensure compliance with industry regulations and standards by aggregating data for audit and reporting purposes.
8. Enhanced Decision-Making: To make more informed decisions by analyzing aggregated data that provides a holistic view of a situation or problem.

Getting data aggregation right

With such clear-cut value, the only real question lenders need to address is how to best pursue data aggregation solutions.

When it comes down to it, the biggest factor to look for is also the most obvious: the financial data itself. The scope and type of information a given fintech firm leverages will determine just how useful the insights produced prove to be.

Different data aggregation fintech firms vary greatly in terms of the amount and quality of data sources they use. Some firms may only have access to data from as few as ten financial institutions, which may still provide valuable insights but is far from ideal. By comparison, Microbilt's Instant Bank Verification solution offers real-time access to data from more than 20,000 financial institutions across the globe. That provides a much more thorough, reliable insight for lenders eager to know more about their customers and potential clients. That, in turn, ensures that these businesses can make the most informed lending decisions possible.