Most people who aren’t in the industry don’t think about big data very much. What they don’t realize is what a powerful effect data and its related security concerns can have on our day-to-day lives.
In particular, big data has a great deal of correlation with personal finance. Accurate financial information, after all, is based on the collection of data, and it’s some of the most sensitive information a person has. Industries like credit scoring and banking have become ever more reliant on digital data, and digital security breaches have had disastrous consequences — not only for businesses. But also for the people whose data exists in large, vulnerable databases.
Databases and big data processing servers are, of course, not inherently vulnerable. As has been proven time and time again, without proactive and forward-thinking security, breaches happen to even the most technologically savvy businesses and organizations.
Big data and credit scores
Up until now, credit was based upon a single score calculation that aggregated the three major credit agencies. The agencies themselves, however, recently created their own competitor to the FICO score aggregator. This is called VantageScore, a technologically advanced system that uses machine learning to take your history into account, as well as your potential future actions. It’s a potentially disruptive force in a tightly controlled industry, and it could mean good things and bad things for consumers.
The machine learning technology behind VantageScore takes big data to look at credit. It performs many of the same functions as a FICO score — aggregating your financial history data across multiple lenders — but it does a lot more. By taking the data you generate and looking at it more like a tech company would a big data project, they developed predictive analytics to examine financial behavior. The algorithms can examine not just the history of your credit, but your behavior, notice patterns and extrapolate your likely actions in the future.
In general, this is good news! Competition makes industries better, and better accuracy means less hassle for you when it comes to credit. As Equifax proved, however, giants are not immune to data breaches. Banks and other financial institutions hold a great deal of data about all of their customers. If this technology proves vulnerable, identity thieves could gain access to much more than account numbers. With access to reports about your credit behavior, they could potentially steal identities with greater effect, imitating your spending habits to throw off automatic detection algorithms currently in use.
Do you know where your data lives?
Here’s the thing about big data. It’s often presented loftily, but at its core, it’s just… a lot of data. Data in such volume that it requires a lot of advanced know-how and technology to properly collect, store, and interpret. The more of something you have, the more work it takes to manage it.
So big data has a lot of overlap with the life of the layman. Any time an app asks for permission to access information on a phone, every time a credit application gets submitted, every time tags their location on social media, an ordinary person is interacting with big data. Anyone who’s interacted with a customer service chatbot is interacting with big data.
Taking steps to be informed about data and its use, as well as informing others, is becoming an important part of basic cyber and identity security. This goes for consumers and it also goes for employees of firms that handle data. Information management systems are often breached through phishing attacks that target employees of a company, or even through disgruntled employees who steal or release data that they had legitimate access to.
Data security is an exercise in individual responsibility and awareness as much as cloud algorithms and rooms full of buzzing servers. In this day and age, everyone collects data. Your personal financial data is particularly vulnerable, as it’s becoming easier for businesses that don’t have access to your accounts to nonetheless collect data about how you use them. What you buy, when, and how — your everyday financial decisions are likely being poured over by algorithms, so it’s important to stay mindful of who you allow access to your data, why, and what they will be doing with it.