Financial institutions have most if not all the data they need to make proper decisions, but accessing, categorizing, interpreting, securing and disposing of it are challenges.
That’s where BigID can help, explained Peggy Tsai, their vice president of data solutions.
Businesses in any sector, but especially financial services, have a range of issues they must address if they wish to see both maximum return from, and maximum efficiency with their data, she explained. For the unfamiliar, it is a surprisingly complex proposition.
“Our biggest strength is the ability to find and discover the required data for these type of decisions to be made,” Ms. Tsai explained. “We see ourselves as the first point in scaling and growing a data management program, scaling a privacy and security program and increasingly a lot of applications around compliance.”
The road to maximum effectiveness begins with having a single source of truth to rely on for making decisions, she added. And if you are going to hang your hat on that source it better be good.
Companies with limited technology could likely be basing key business decisions on incomplete data sets, with the funny part being they usually have the data somewhere within their reach. The kicker is to locate it, properly interpret it and then secure it.
If a company is attempting to profile a customer, they have to gather as much relevant data as possible, and that data is likely scattered over multiple tables in multiple locations, in many forms and under various labels. Once located it has to be correlated, interpreted and properly stored.
“This type of data has become very relevant in the data management space,” Ms. Tsai said.
In financial services this process can be increasingly frustrating because in the past different units within many institutions operating within their own silo, with their own (often incompatible) technology. As the need for connectivity was realized, they now had to link their own systems, a process many are only beginning today.
It gets worse. If they’re multinational they have to work with different regulatory regimes and local branch system preferences. Then there are acquisitions with their own unique systems.
“The challenges that a lot of our customers face is they are looking at it from an enterprise point of view, to bring these silos, these data sets together,” Ms Tsai said.
Consolidation reveals redundancies and duplications. Space is wasted and some data is in places where it should not be. These are growing issues as customers begin to get a handle on their structured data. More and more are hiring chief data officers who are charged with ensuring consistency across areas of the company. They create scalable solutions that are consistent across the company.
Data governance is often the starting point, Ms. Tsai said. Companies seek to make sure data is properly captured and documented when it first enters the organization so they know where it originated and where it should head. It also helps them prepare for ay changes in privacy regulations.
This is often accomplished by mapping the source location, tracing the users and where it is sent. While that has benefits, it is a defensive strategy, Ms. Tsai said. Why not be proactive by using your data to better know your customer so you can better segment them to conduct more efficient sales and marketing?
“The big question is how good is the quality of that data to give them the insights they need,” Ms. Tsai said.
When data enters your organization its quality dictates how it can then be used. When receiving that data companies should first ask what it is and if it is deemed important transfer it into more structured and usable forms.
Better to do this than to search for data once it has been sitting somewhere within your network for a spell. Different departments may label it differently or put it in different forms. If it is not properly labeled and you don’t know where it is, how can you properly protect it in an era stressing the importance of privacy?
“Those are still very manual processes that organizations have to do today,” Ms. Tsai said.
BigID helps their customers build a single new inventory and then decide what to do with, Ms. Tsai said.
“There’s a multitude of use cases we’ve been able to help our customers with, especially with our foundation of data discovery that is really unique in the marketplace,” she said.
BigID also helps customers navigate the challenges arising from suddenly remote workplaces, where proper access levels still need to be maintained. Employees are creating and storing more information on their personal computers. BigID’s technology can help customers place that data in structured groups.
“That produces a risk from an enterprise perspective,” Ms. Tsai said. “What are the independent files employees are creating that contain personal or risky or sensitive data, anything they may not want to be leaked out?”