Today’s data-rich environment is a double-edged sword for compliance professionals, with regulatory change or KYC adding to the risk of information overload. How can machine learning and intelligent tagging help?
- Machine learning has significant benefits for over-burdened compliance staff, freeing them to concentrate on higher value areas of responsibility.
- Thomson Reuters Intelligent Tagging uses natural language processing, text analytics, and data-mining technologies to filter and classify volumes of data.
- Intelligent tagging enables teams to more accurately understand and manage risk, helping them to #FightFinancialCrime.
Compliance professionals in this age of big data are faced with a dilemma: they must analyze and make sense of vast volumes of available data, pinpointing the information relevant to their changing needs at any given point.
Moreover, they must achieve this against a stringent regulatory backdrop, where the penalties for non-compliance can be severe.
The sheer volume of information available can be overwhelming, and compliance professionals therefore need the right tools to help them cut though the noise.
Machine learning in the age of big data
Machine learning refers to the process of computers analyzing volumes of data and producing recommendations. It is somewhat different to artificial intelligence, which implies a degree of ‘reasoning’ on the part of the machine.
Machine learning enables ‘augmented intelligence’ by taking unstructured data and filtering it to empower end-users to pinpoint the information most relevant to their needs.
Watch: As artificial intelligence transforms industries, is data becoming the new gold?
This has significant benefits for often over-burdened compliance staff, as it can free them to concentrate on higher value areas of responsibility by automating repetitive, time-consuming tasks. It also removes the human error factor.
Machine learning has many applications, one of which is intelligent tagging.
Thomson Reuters Intelligent Tagging (TRIT) uses natural language processing, text analytics, and data-mining technologies to filter and classify volumes of data.
TRIT tags people, places, facts and events across millions of documents at a far greater speed than humans could ever hope to achieve.
But more than this, intelligent tagging enriches content by attaching ‘relevance scores’ to data so that it becomes readily searchable, meaning that the most relevant information can be found with ease.
Intelligent tagging empowers compliance professionals to find the information they need.
It also helps them to spot trends and quickly understand if there are gaps in the information required to form a holistic picture of any entity or individual.
Watch: Thomson Reuters Intelligent Tagging
Intelligent tagging helps compliance professionals to:
- Pinpoint relevant information. Intelligent tagging highlights the information most relevant to any particular search across individuals, companies and industries of interest.
- Save time. Text can be processed and tagged in a matter of seconds.
- Gain deeper intelligence. Automatically generated rich meta-data filters out the noise and reveals insights hidden within volumes of text.
- Manage risk. Intelligent tagging helps teams to analyze volumes of data at speed; identify gaps in information; and quickly gain insight into global events to help them more accurately understand and manage risk.
Machine learning in the form of intelligent tagging helps compliance professionals to make sense of big data, and harness the power of an information-rich environment that could otherwise be overwhelming.
By automating the time-intensive aspects of the compliance remit, staff are empowered to build a more holistic picture upon which to base their most critical decisions.