Introduction to Data Aggregation
Data is the lifeblood of the financial industry. Without reliable, accurate, and timely data, lenders, financial institutions, and insurance brokers simply cannot function effectively.
Data aggregation enables financial organizations to make more informed decisions by providing access to data that’s outside of their organization. We’ve all seen examples of financial organizations who make decisions based on information that exists in their organization to come up short every time. Have you ever received an offer for a new mortgage loan when you already have a mortgage loan with another lender? This is why aggregated data has become so important to provide financial organizations with a 360-degree view of their customers.
Data aggregation involves the process of gathering information from different sources into one unified dataset. By accessing data from many sources in a single database, financial organizations can get a much clearer, more comprehensive picture of their customers. This process of gathering data combined with some strong statistical analysis can lead to some competitive advantages.
What Are Data Aggregators?
A data aggregator is an organization that provides connections to external data sources necessary to collect, store, and organize information from many different sources. Data provided by a data aggregator can be used for a variety of purposes, including analyzing trends, making predictions, or providing insights.
Data aggregators work by consolidating information from a multiple sources and organizing it into a single, easily accessible location thus, making it easy to identify patterns and trends and draw meaningful insights from the data values. Data aggregators are often used in fields such as finance, healthcare, marketing, insurance, and real estate for the analysis of large amounts of data spread across a number of different data silos.
Provides a visual and explanation of data aggregation from four different data sources.
For example, a business may use a data aggregator to analyze customer insights and identify correlations between their demographics and spending habits. Similarly, a healthcare provider may use a data aggregator to analyze patient information and identify correlations between health outcomes and treatments. Lastly, a lender may use a data aggregator to verify information necessary to approve a loan.
Why Is Data Aggregation Important For Me?
Data aggregation is becoming more critical for businesses today. Previously, businesses had a limited dataset to understand their customers because the 360-degree view of their customers required them to access outside data sources. Today, data aggregation makes this possible by providing accurate and real-time data from various different sources.
According to Statista, world data creation and replication are expected to reach a staggering 181 zettabytes by 2025. With such an immense volume of information being generated, it becomes challenging for businesses to sort through the noise and find the data points that are most relevant to their needs.
A graph of the volume of data information created, captured, copied, and consumed (e.g., aggregated data) wordwide from 2010 to 2020.
Solving the Problem with Data Aggregation
This is where data aggregation comes into play! Through the process of data aggregation, financial organizations can access data in various data silos to get a 360-degree view of their customers. This data aggregation process is extremely helpful in determining effective cross-sell opportunities, credit decisions, personal-financial management, payments, and other impactful use cases.
Truv recognizes this growing demand for accurate and real-time data from data aggregation, thus Truv empowers businesses with an innovative data aggregation platform. Truv enables businesses to gain a competitive advantage by making quick, data-driven decisions.
Learn more about the value of Truv’s consumer-permissioned data aggregation platform here.
Use Cases for Data Aggregation
There are countless data aggregation plays where a data aggregation tool focuses on aggregating data for a specific purpose. Three of the main use cases are outlined below.
The fastest growing use case for data aggregation today is lending verifications. In the mortgage industry, over ten different verifications need to take place to underwrite a loan. While in personal lending, more providers are focusing on verifications to reduce their risk. However, the pain point has always been that manual aggregation increases time to close (e.g., average age of the loan application) and increases applicant churn. Now with automated data aggregation tools, these concerns can be alleviated.
Data aggregators enable lenders to reduce their risk from approved loans without compromising on speed or quality.
Data aggregation tools extract data from data silos to complete the following lending verifications: identity, income, employment, assets, cash flow, home insurance, auto insurance, and more.
Specific to income and employment data aggregation, instant databases exist that purchase data from employers and payroll providers to resell this data at a high premium. This form of data aggregation is instant, however, prices for this data have skyrocketed as vendors like The Work Number increase prices by 20% every six months. This has caused lenders to look elsewhere for income and employment verification or even stop doing these verifications all together.
Personal Financial Management
Digital banking providers have been focused on personalized financial management for years, because driving customer engagement increases the financial institution’s share of wallet for that customer. Data aggregation is essential for personal financial management because without aggregated data, consumers cannot get a 360-degree view of their finances and the tool would be useless.
In this use cases, the data aggregation process is slightly different. Consumers aggregate data from their various financial relationships (e.g., checking account, wealth account, credit card). After this process, the data collected is sent to the financial organization’s customer-relationship management tool to be stored in various data sets. After this, presenting aggregate data is the unique step in this use case where customers are able to view a summary form of their aggregated data. This allows customers to analyze a 360-degree view of their finances and even conduct further data analysis as needed.
For financial organizations who offer personal financial management tools, they’re able to collect information on their customers from different platforms that enable them to understand their customers at a much deeper level.
The data aggregator MX empowers best-in-class personal financial management solutions for financial institutions.
Another data aggregation use case is payments, where customers need to send payments from one financial organization to another. In this industry, manual data aggregation involves writing a paper check or completing micro-deposits after inputting an account number and routing number. These processes are extremely manual and full of friction, which lead to customer frustration and decrease satisfaction scores.
However, today through data aggregation tools, financial organizations can instantly verify a customer’s account and routing number of an external depository institution to complete a payment. This happens instantly and drives significant operations optimization for financial organizations. For example, American Express is able to aggregate data on account and routing numbers in order to facilitate credit card payments from depository institutions.
Data aggregation empowers use cases such as payments with the ability to connect two depository institutions.
Truv’s Mission to Aggregate Data and Put Data Back in the Hands of Consumers
Consumers today are conversant with instant access to information and expect businesses to provide them with quick, personalized responses. Think about the movie recommendations you receive from Netflix or the shopping recommendations you receive from Amazon. However, when it comes to financial data, a significant challenge remains – data silos.
Data silos are repositories of data that are held in separate, incompatible systems, making it difficult to access, analyze, and integrate data. As a result, businesses have to rely on manually inputted financial data, which can be time-consuming and prone to both errors and fraudsters.
Truv stamps out this barrier and provides seamless access to four consumer-permissioned financial data sources. Truv empowers businesses and consumers alike with a comprehensive view of consumer financial profiles by consolidating data from every available source.
Truv’s mission is to put data back in the hands of consumers by providing a single platform for accessing financial information. This mission aligns with the broader trend towards greater transparency and consumer empowerment in the financial services industry, paving the way for a more inclusive and innovative future. Learn more about the Truv’s mission here.
Income and Employment Verification with Truv
Verifying income and employment is a critical step in the lending process to ensure that lenders are reducing their risk by approving loans to applicants with the highest likelihood and ability to repay. The verification industry has previously relied on the process of aggregating data from multiple sources manually to reduce risk. Unfortunately, manual aggregation methods are slow, expensive, prone to human error, and result in greater fraud. Five percent loans that manually gather verification data from multiple sources are fraudulent. On the other hand, automated data aggregation allows for a more efficient data collection process.
Truv’s automated data aggregation platform uses consumer-permissioned data to provide real-time and verified identity, income, and employment data points. After a connection is successfully established to aggregate data, Truv provides a summarized format of the identity, income, and employment data points necessary to underwrite the loan.
Image of Truv’s payroll aggregation capabilities that enable income and employment verification.
With Truv’s consistent and transparent pricing relative to instant databases, you can enjoy proven ROI and cost savings while streamlining your income and employment verification processes driving greater efficiencies throughout your business.
Benefits of Using Truv
Truv’s income and employment verification solution is proven to create immediate business value and return on investment through market-leading data quality.
Proven ROI & Cost Savings
Unlike other providers in the industry, Truv’s pricing is consistent, transparent, and empowers you to provide lower fees and interest rates to your customers.
Reduced Risk & Fraud
Receive real-time data directly from the source, while instant databases may have stale data that’s inaccurate causing you to approve unqualified applicants for loans.
Increased Employee Efficiency
Truv’s platform boasts 90% fill rates for over 200 unique income and employment data points, enabling employees to work more efficiently and focus on higher-value tasks.
Improved Turnaround Times
With Truv, you can verify income, employment, and identity in less than 45 seconds, significantly reducing delays and streamlining the overall verification process.
Learn more about the Truv’s income and employment verification solution here.
Enterprise-Ready and FCRA Compliant
FCRA compliance allows lenders to use aggregated data for credit decisions.
Truv is enterprise-ready to support the needs of large-scale organizations with seamless integration and scalability.
SOC 2 TYPE II COMPLIANT
As table-stakes in the data collection industry, Truv is SOC 2 Type II compliant. This certification provides validation from an outside third party that Truv has the necessary controls and security that is essential for data aggregators.
Truv is one of the only software tools in the data aggregation industry that is FCRA compliant. This provides confidence that any data provided by Truv can be used to drive more informed lending decisions.
Learn more about the Truv’s security and compliance posture here.
Truv’s Commitment to Protecting Aggregated Data
At Truv, we believe that consumers own their data and should be in control of who has access to their data. We understand that protecting payroll data is crucial, and we take many measures to ensure that consumers’ sensitive information remains safe.
We take multiple steps to safeguard consumers’ payroll data which includes
- Implementing strict access controls and granting access to consumer data only on a need-to-know basis and ensuring that unauthorized parties cannot access sensitive information.
- Adhering to industry-leading data protection standards to maintain the highest level of data privacy and security.
This commitment to data protection is essential for data aggregation, because in the end, consumers should own their data and data aggregators are responsible protect consumers’ data. Otherwise, data aggregation providers may be subject to future legal issues due to their lack of responsibility over data security and privacy.
Future Trends with Data Aggregation Tools
Data Aggregation for All Data Sources
Here at Truv, we’re big believers in providing data aggregation to collect comprehensive data sets for financial organizations. For 10+ years, the data aggregation industry has been hyper-focused on aggregating transactional data from a consumer’s financial institution. This was because the primary use case for aggregated data was personal financial management. However, the true power of data aggregation comes from extracting data from multiple databases.
Currently at Truv, we pull data together from large databases through data aggregation of payroll data, tax data, financial account data, and insurance data. However, there are data silos containing other personal data that data aggregators will look to consolidate to provide a clearer view into individual consumers. For example, health care data aggregation is an area that has not been matured and could lead to impactful business insights.
An overview of Truv’s data aggregation platform allowing lenders to reduce risk, increase efficiency, reduce costs, and approve more loans.
Data Analytics on Raw Data
The business world today is buzzing with artificial intelligence after the release of ChatGPT. As we think about the future of data aggregation, it’s impossible to think about the future without diving into the role of machine learning and artificial intelligence in big data from data aggregation. More effective data analysis will be the focus of data aggregation in the short-term.
While data aggregation is the process by which data from different sources is combined into a single database, financial organizations are seeking to understand how to organize that raw data into a format that drives actionable insights. Collecting data is the first essential step, while the ability to transform data is the step that will truly drive impactful business decisions for financial organizations.
Artificial intelligence will allows organizations to combine big data and data analytics.
The next wave of innovation will come from organizations that take aggregated data from a data warehouse and make that data actionable for financial organizations today. This can include greater segmentation for marketing strategies and marketing channels, providing real time visibility into financial wellness for an individual customer, statistical analysis to provide predictive analytics on future spending behaviors and other valuable information, and more.
Combining Financial Data with Other Insights
Organizations such as Google, Amazon, and Facebook are incredible at their ability to understand customer behavior more deeply through gathering as much data on consumers as they can. For example, Amazon combines browsing history with data from other information providers to understand behavioral variables such as products to recommend to their customers.
However, data that these organizations have not been able to effectively access have been financial data. Imagine the insights from combining all of these sources with financial data for data analysis and the insights that could be derived. As these organizations seek to understand how to access financial data, financial organizations with this information today are in a strong position to aggregate data from financial sources that they have today with other sources to understand their customers at a much deeper level.
Get Started With Truv Today
Truv’s mission is to put data back in the hands of consumers by providing a cutting-edge data aggregation platform focused on market-leading data quality. Our platform enables financial organizations to streamline and automate the income and employment verification process by consolidating data from four unique sources to automate this verification process. This ensures quick and reliable access to real-time data, allowing lenders to make decisions that decrease risk and increase profitability.
The future of income and employment verification is through consumer-permissioned data. Truv’s data aggregation platform provides an efficient and secure solution for businesses to access data from multiple sources in just 45 seconds.
Let’s Chat About Data Aggregation
Get started with Truv’s data aggregation platform today and witness the power of accurate, real-time data firsthand. Chat with us to learn more about how Truv can drive cost savings, reduce risk, increase efficiency, and help you approve more loans.