Compliance units have the function of ensuring that all processes are in line with relevant laws and regulations. Non-compliance may generate unnecessary costs (e.g. administrative fines) and lead to reputational losses and customer exodus. In certain circumstances, it may also adversely affect the management board and its members, as a lack of compliance may result in personal liability.
It is vital to have effective and swift units that can react to any wrongdoing.
Control and supervision of business units and their activity are one of the main goals of compliance functions. In case of a potential threat, such teams should be able to act to eliminate risk.
How can a compliance function effectively oversee a whole business, especially if it is highly decentralized?
It seems it is almost impossible.
In a company with thousands of sellers or relationship managers solely responsible for selling products or providing services, all of them are expected to respect a set of specific rules and procedures. This set will cover customer service's do and don'ts, grand rules for communications and examples of use cases.
Compliance officers will often review the data from phone and mail communications in customer service, which are stored and archived for legal and regulatory purposes (e.g. support or deny potential claims).
These conversations with customer service employees represent hours of hardship to find possible gaps or inconsistencies with relevant policies or procedures.
It is a massive task prone to human errors.
But is there a way to automate this process?
With Docmatic's natural language processing techniques, compliance officers may be able to train models with a set of key phrases, words or whole sentences suggesting that specific undesirable behaviours took place.
Instead of going through the entire document,
the compliance officer will receive an alert every time the model encounter said phrase or keyword
and link this alert to a particular part of the text that requires attention.