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76 detect patterns in data and identify when anything strays from that pattern, which is a sign of potential fraud. We see these tools used often to mitigate fraud, as, in the past, fraud detection has been a tedious process. Technology not only makes it simpler but also helps catch fraud faster. It does not stop with fraud control, however. Organizations can use data for nearly any other process automation they can imagine. Lenders can easily automate underwriting or other workstreams in order to make the overall business more efficient. ere is an incredible number of ways that any business can put their data to work for them. With so many options for how to use it, each organization must determine what is most important to them. e companies should look at their practices, systems, and processes and identify what may need improvement. e first and most important factor in successfully implementing data-driven decisions is not the content of data itself or data evaluation methods. It's the ability to accurately identify and formulate the business challenges you are trying to solve with the data. If the price tag is a concern, it's best to focus on competitors and market analysis in order to find areas in which your company can improve and better compete in the marketplace. If the product or service itself is a concern, it would be better to focus on using data to understand the customer's needs. is will help evaluate current product and service offerings to improve customer satisfaction. If efficiency is a concern, automating with data and technology can help decrease operational costs. If fraud is a concern, of course, it's a good next step to develop fraud models and put them to use. Once lenders, servicers, and other mortgage professionals know how and where to use the data, then it can go to work and bring the organization the benefits it's looking for. THE CHALLENGES OF DATA e advantages of attaining and using data strategically outweigh any risks or disadvantages, but it's important to understand how using data can be a challenge. It's essential to know the "3 Vs of Big Data": volume, variety, and velocity. » Volume—understanding how much data you have. » Variety—the format of data: traditional formats like Excel, comma-separated values, or nontraditional formats such as video or pdf. » Velocity—the speed of data collected and processed, which could vary from small periodic updates to a large amount of real time data. e capacity and technology required to handle this amount of data could be time-consuming and costly. In order to fully take advantage of the data a company has on hand, the data must be housed using a unified data access platform. Otherwise, the organization faces the risk of the data becoming siloed, which results in a disjointed view. is could lead to the implementation of inconsistent solutions in various functions across the business. ere also are a host of regulations that require protection of customer data and privacy, which can be challenging to keep up with, Feature By: Alex Kudman The advantages of attaining and using data strategically outweigh any risks or disadvantages, but it's important to understand how using data can be a challenge.