Skip to content

Our Privacy Statement & Cookie Policy

All Thomson Reuters websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.

Financial institutions

Practical tips for vetting a data partner

Michael Purcell  Public Records Product Specialist

Michael Purcell  Public Records Product Specialist

Locating high-quality data can be a vital turning point in an investigation. It can even prevent criminal activity, terrorism, and fraud from happening in the first place. But how do you find that critical information? Many industries look to outside vendors to manage their data quality. With the global datasphere projected to hit 175 zettabytes by 2025, knowing how to assess your data partner is paramount to being able to evaluate risk within your organization.

What’s at stake

Financial intuitions are required by law to conduct thorough customer due diligence (CDD). This increased financial transparency is designed in part to preempt or catch terrorists and drug cartels. Thorough CDD is also meant to curb rising consumer fraud. According to the Federal Trade Commission, consumers reported losing more than $3.3 billion to fraud in 2020, up from $1.8 billion in 2019.

CDD investigations are comprehensive and rely heavily on finding quality data. Simply put, without high-quality and intelligent data aggregation tools, risk analysis and due diligence are simply not possible.

Assessing data partners

There is an incredible amount of data and investigative tools available to investigators today. These investigative tools can aggregate and analyze data at lightning speed. With so many options available, how does one evaluate a potential vendor to determine confidence in what they provide? How do you know if you’re missing anything? Is the data current? What about transcription errors?

To ease your mind, here are three practical tips that will help you determine if your data partner is providing you with quality information.

Currency, accuracy, and transparency (CAT)

Currency means having access to frequently updated, or even “live” data. Ensure that your data aggregator is lobbying to have their content updated as frequently as possible. A partner that cuts costs by delivering less frequent data updates is not going to serve you when time is of the essence. You need to understand the update frequency of each source. Also, be sure to ask how many “live gateways” there are. These are powerful live API data feeds that execute a “virtual handshake” with source data in real-time.

Accuracy means your data partner has strict controls in place for onboarding new data sets, sampling the records with a human testing process, and precision-recall testing. Solid QA processes are paramount in ensuring the most accurate data is being delivered. Public records are notorious for being “messy” and riddled with errors. A good vendor will use advanced entity resolution matching/pinning, artificial intelligence, human testing processes to deliver the best results. Keep in mind, if your vendor is providing access to a slew of data sources then you, as the end-user, can embrace the redundancy of data. You will feel more confident in knowing that certain data points are being reported by numerous sources. A strong vendor will help you get the data you need with limited false positives and redundant source detail. This translates into greater efficiency and quicker analysis.

Transparency means seeing where your data is coming from and when it was reported. If you can’t, that’s a problem. Believe it or not, most investigative data tools don’t list the name of the source or the date the source reported the information. So why do some vendors skimp out on providing this level of critical detail? It’s simple. It’s wildly expensive and exposes huge gaps not only in coverage but in the frequency of updates. If the data being reported is stale, then a vendor has the convenience of not being transparent to intentionally screen their shortcomings. It should be expected that the source details are provided along with specific dates reported by the source. The more sources reporting specific data points the stronger the data. Redundancy and transparency drive confidence.

You certainly should not cut corners when it comes to due diligence, risk analysis, and fraud prevention. With Thomson Reuters® CLEAR, the “CAT” principle is already baked in. There is a lot at stake for your organization. While it’s true there are many investigative systems available to financial institutions today, CLEAR sets the bar for access to credit header data, data source transparency, and entity resolution.

Get the vital information you need for your investigation with Thomson Reuters CLEAR.

Learn about creating a consistent and well-documented AML investigation with CLEAR and schedule a free demo today.

More answers