Garbage In, Garbage Out

Best practices for managing your data and five practical ways to improve its quality

Garbage in, garbage out, goes the old expression. That is, the quality of what you put into something relates directly to the quality of what you get out of it. It’s used as a metaphor for many aspects of life: from diet and health, to education, to even the finer points of formal rhetoric. The concept holds for any system that accepts inputs and creates outputs.

It’s traditional home, however, is the field of computing. And in the age of Big Data, with so much riding on the output of the applications and algorithms that make up the background hum of our daily lives, the concept of garbage in, garbage out has never been more relevant. Business, of course, is more data-driven than ever before. And aside from actual rocket science, modern finance may rely on data more than any other profession. High-frequency trading. Algorithmic trading engines. Cryptocurrencies. Derivatives so fiendishly complex they literally take an MIT grad to understand. 

For any enterprise financial institution, ensuring data quality is crucial, and something which too often falls by the wayside. Following are data-management best practices that apply specifically to the financial industry and five practical ways to improve data quality, which will help turn that volume of inbound data into insightful information and better decision making.

Best Practice Makes Perfect
Your firm is an information hub. Depending on its particular financial industry raison d’être, there’s a wide variety of data coming at it from a range of sources and systems.

From the larger financial world comes trading data, securities and pricing data, broker feeds, and news. From the smaller, but no less critical, world of your own company comes expense records, CRM data, contacts, expense records, and user and HR data. Critical data can also come in from outside partners, like those that perform data entry and provide record keeping.

Whatever compliance platform you’re using, there are universal best practices to manage this data better:

• With each new platform release comes new features and functionality. Install it, train on it, and use it. With upgrades come a learning curve, but the end result will always be worth the effort.
• Remove the human element. Whenever possible get data into your system via a feed. Data systems are designed to exchange information in the fastest and most efficient way possible. Try your hardest to get every internal and external partner to provide data feeds.
• On a related note, eliminate or lessen as much as possible how much data you get from manual input, whether it’s from internal or external sources. Not only is it slow, it’s prone to human error.

Remember that not all feeds are created equal. Some are more important than others. It’s important for you to know what data is the most important, and what will happen if that data takes a day off. A best practice is to establish a protocol if data is unavailable from a primary source. And do it sooner rather than later. A backup plan is best thought about well before you need it.

Finally, consider if you’re being properly kept in the know when it comes to the data your company depends on:

• Do you get file-not-received alerts? If you don’t, start. They can be lifesavers.
• Do you know who’s responsible for doing what in your firm or in any partner organization if there’s an issue?
• Do you know who’s responsible for monitoring and correcting issues, internally and externally?
• Have you considered the impact of file-import errors? Are they tolerable? If so, which kinds are tolerable and which are mission critical?
• What happens if an expected file is missing? What’s the downstream impact? Who does it impact?

Five Practical Ways To Improve Data Quality
It’s not just the thought of missing feeds and import hiccups that keeps people up at night. The feed may be fine, the files may be there, but the data inside might be bad. Back to garbage in, garbage out. Without quality data any application, like a compliance platform, is worse than useless, because it might produce false signals that lead you to believe all is well when it’s not. Here are five ways to help ensure the quality of your data.

1. Leverage The Broker Feeds
You may need to occasionally turn the heat up on a broker you work with to supply a data feed. Feeds are expensive, and it can be difficult to convince a broker to make the investment. But a smart enterprise financial institution will do all it can to convince a broker to supply a feed, including using employee convenience as leverage. 

Most firms think of an approved broker list as a last resort. Asking employees to transfer holdings to a different broker is a conversation to be avoided. But remember there’s strength in numbers. By joining forces with other firms you’ll be better able to persuade brokers to be more compliance friendly and supply the data feeds you need.

2. Implement A Routine
Once the pipes are connected and data is flowing, it must be checked. It’s important to implement a routine to keep pace with the daily volume. If you have a team at your disposal, a rotating shared-review process works well to stay on top of any unknown accounts and securities.

But beware a common industry pitfall. Once a conflict-of-interest system is up and running, the state of the data feeds can fall off the radar. So long as the feeds are there, normally vigilant professionals may take their eyes off the data-quality ball as more seemingly pressing matters demand attention. Stubbornly stick to the routine.

3. Utilize Reports For Data Checks
It’s important to not just keep an eye on the data, but to keep an eye on how well you’re keeping an eye on the data. To track how well you’re tracking, in other words.

A well-built compliance platform will give you the ability to create reports, including graphical reports, which will reveal trends and tell you if your data is getting better or not. It will also give you the ability to not just pull the kinds of reports that keep you and your colleagues in the know, but to schedule and auto-update them.

4. Leverage Extended Properties
Every compliance team has a unique set of data points they want to attach to each employee’s profile. A good compliance platform allows for sourcing of data points outside of a base configuration. This added flexibility in the system, known as extended properties, can be leveraged across the system and typically includes the ability to:

• Automate the assignment of users to groups.
• Bring new fields into your reports.
• Link the platform’s rules engine to make better automated decisions. 

5. Guide The User
Do all you can to make the system you have in place easy to use. The more intuitive a system is, the more likely people will actually use it and the less of an inconvenience following the rules becomes. Theoretically, this should mean more data is captured and that the data captured is more accurate, which reduces risk. Provide guidance at every possible point in the user process: 

• Add help and info banners at every user-interface level.
• Create quick-reference materials and one-page guides.
• Prevent bad data being entered by automatically running duplicate checks on contacts.

The human element
Garbage in, gospel out has become a sarcastic catchphrase for those who see the data-obsessed as misguided, willing to accept anything that comes out of the input/output system as unquestionable truth. But data must be dealt with. It certainly isn’t going anywhere. Nor are regulations that require the increased capturing and storing of it, like Europe’s new MiFID 2. 

The best tool you have to properly manage and improve your data is you. Ask your internal and external partners lots of questions. Learn your systems inside and out. Know your clients. Don’t rely on assumptions. The better relationship you have with your data the better relationship you’ll have with clients and regulators, and the better chance your enterprise financial institution will have of staying in business for the long haul.