There’s an old adage about data analysts — they’re known for spending much more time preparing data than actually studying it. Sadly, this jab can be an unfortunate truth for many businesses entering the big data game.
But for any company that offers lending or financing options to its customers, it’s imperative that the data collected is fully understood. That’s the only way to make good decisions about customer lending. Just as importantly, it can help build trust with customers who have to provide their personal information.
Connecting the data dots
At its core, lending is all about linking inputs to outcomes. The most important outcome, of course, is whether the customer pays you back. But there are many other situations to consider, including the potential for repeat business, the likelihood of customers contacting customer service, or even the completion of the initial application.
The inputs you collect — such as employment status, income level, and credit score — will help you make decisions that impact everything from the quality of service to the profitability of your lending. It’s important to make sure that your process is seamless and gathers enough information to enable you to make a sound decision about the applicant.
With the tools currently available, studying and using the data is the easy part. You drop your information into Excel, and presto — you have the potential for instant insight on display. But aggregating, structuring, and cleaning up data to discover those insights can get incredibly difficult and time-intensive without a solid management plan.
Building the best data management for your customers
According to a recent report by The Economist Intelligence Unit, nearly 60 percent of senior executives already use data to guide financial decisions and generate revenue, while 83 percent believe big data makes current products and offerings more profitable.
Proper warehousing of data can feel like a huge predicament. If you run a small business, odds are good that your data is simply a messy collection of spreadsheets on your laptop. Perhaps it’s floating about aimlessly in somebody’s cloud drive. Either scenario can leave a lot of room for error.
But for companies dealing with sensitive customer data — like small business lenders — it’s imperative that you get it right. Proper handling of data not only inspires trust, but it also helps businesses make lending decisions and provide high-quality customer service.
Lenders who analyze the data gathered during the application process can more thoroughly understand specific pain points: Why did the customer abandon the application? What questions need reworking? Is the flow confusing?
Plus, properly analyzed data can help customer service representatives provide better assistance when a customer contacts them with a question. With easy access to more information, customer service reps can provide more personalized service, resolving issues quickly and efficiently.
For lenders looking to incorporate a big data strategy, here are six tips to get started:
#1. Gather the right data
The most important practice is to make sure you’re pulling the right data on your customers to make lending decisions. As long as the data is clean and well-structured, it doesn’t matter whether it comes from one of the credit bureaus or an alternative provider. The key is ensuring that you’re building insights based on the most accurate and applicable information available.
If that data isn’t going into some kind of data infrastructure warehouse where analysts can work with it, stop what you’re doing and focus on building that piece first.
#2. Design data structures through collaboration
Don’t just let your IT people design the database in a manner that makes the most sense for them. Your analysts should be involved in how the database is built — after all, they’re the ones who are going to be using the data to make your business better. The final product will be more effective if the design process is collaborative.
Start a dialogue between your database engineers and your business intelligence analysts to determine how information should be grouped and displayed. The more your engineers understand how the business uses data to make decisions — and the more your analysts understand how data is collected and stored — the bigger the advantage your firm will have.
Building a rich, vibrant data culture at your firm and getting the whole organization excited about data will save time, avoid setbacks, and boost engagement.
#3. Store your data somewhere safe and easily accessible
If you’re involved or thinking about getting involved in finance and lending, you don’t have a choice: Your data has to be protected and secured. This means a proper database that is firewalled, encrypted, and regularly backed up to keep customer data safe.
There are quite a few flavors of database to choose from. SQL Server and MySQL are common and integrate easily with just about any website or app. If you’re working with extremely large data sets, Hadoop is a framework that allows massive amounts of unstructured data to be stored, processed, and managed. By splitting files into nodes and clusters, companies are able to store and examine enormous files that a single server couldn’t support. This framework also helps improve speed and analysis. If a company’s data volume increases, it simply adds additional cluster nodes.
#4. Aim for automation
In a practical sense, the more you can automate, the better. Gather everything digitally, and store it in a database. Assign unknown or outlier values upfront. Make sure there are checks within your processes to ensure the data coming in is clean and that any data that’s inaccurate or corrupted is quickly scrubbed out. Don’t give your customers the opportunity to enter garbage data. Remember, garbage in leads to garbage out.
#5. Install a real analytics or business intelligence suite
Only through great data is great analysis possible. To transform complicated data sets into digestible information for decision makers, you need some sort of analytics or intelligence software on your side.
Some of the well-known software, such as SAS Analytics Pro, may not be worth the cost of a full license. But there are other tools that are free or relatively inexpensive for small businesses, such as IBM Watson Analytics, Cortana Analytics, or Microsoft Power BI. Tableau has several flexible usage configurations, depending on your firm’s budget and size. None of these options are all that expensive compared to the potential profit margins you could gain based on data insights.
#6. Understand your customers — inside and out
There are countless programs designed specifically for taking in customer feedback and understanding the behavior of your target audience — yet another important data point to keep in mind. From tracking return on investment with Google Analytics to managing surveys with SurveyMonkey to adding CRM solutions like Zendesk for handling customer interactions, it’s never been easier to understand the people your business was built to serve.
Gathering more data will help you make better decisions regarding your customers and give you an edge over your competitors. But the cleaner that data is and the more rigorously that data is structured, the easier it will be to work with — and the more quickly you can make decisions.
Images: ” Close up of businessman holding virtual graph in palm /Shutterstock.com“
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