The lending industry is one of the most volatile sectors of business in the United States. There are millions of people who need and want loans for everything from a new house to a business or an automobile. Credit scores tell you a lot about potential borrowers, but even credit history reports fail to tell the complete story, and that’s where business intelligence comes into play.

Unless you’ve been under a rock for the past 20 years, chances are that you’ve heard of big data and advanced analytics. Companies are using obscure, and even abstract, data to get real insights that help them with decision-making, marketing, and even supply chain management. So, just imagine what the right business intelligence (BI) tools can do for lenders. Continue reading to see some of the incredible ways loan companies across the U.S. are using business intelligence software to boost their profits.

1. Dashboards

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The process of getting a home loan is one of the most arduous lending processes there is. There are so many factors to consider that it can be head-spinning. You have to factor in an applicant’s credit report, employment status, employment history, income, and so much more.

With so much data to pour over before deciding to offer someone a mortgage loan, any tool that makes the process easier is well worth its weight in gold or Bitcoin. One of the things lenders run into when they’re considering data from multiple data sources is trying to connect and compare different metrics. With a centralized dashboard, you can access multiple data sets and integrate data from multiple sources, so you get a fuller picture of the applicant.

2. Data Visualization

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Data visualization is one of the most important BI tools your lending company will ever use. It’s great to be able to pull information from various sources and get obscure insights, but if you’re not a data analyst, those metrics won’t mean much to you. That’s where data visualization makes its money.

Data visualization is a BI tool that makes data more digestible for business users and turns confusing statistics into actionable insights. Data discovery, data mining, and data processing are all key functions of a powerful business intelligence platform, but without visualization to make the data make sense, most business users find themselves at a loss for solutions. However, with the right visualization tools, you can turn metrics into aesthetically captivating graphs and models.

3. Predictive Analytics

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There are few abilities that lenders value more than the ability to see things before they happen. When you’re considering whether to lend hundreds of thousands, or even millions, of dollars to potential homeowners, you want to know as much as possible about the likelihood that the applicants will make their monthly payments and pay the mortgage in full.

Predictive analytics is one of the key features of a potent business analytics platform. Predictive analytics is the process of using raw data to determine a future event, which allows lenders to make better decisions about the eligibility of applicants. Furthermore, by using prescriptive analytics, companies can take what they learn from predictive models and find insights into how to handle coming changes and events.

4. Data Warehouse

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Whether you run a small business or a large enterprise, having a data warehouse for data preparation and data management is critical to the safety and efficiency of your data. Data warehouses act as a data integration tool that allows quick, yet secure, access to sensitive data.

Data warehouses are like a supply chain for your business intelligence processes and are essential to the integrity and security of your databases and analytics solutions. It’s one of the BI tools to which all BI tools report their valuable insights.

As you can see, data analytics makes life much easier for lenders. They use analytics solutions for everything from customer service to determining loan eligibility. With this knowledge your financial institution can capitalize on the power of big data business processes.

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