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Governance, Risk and Compliance Transformation with Smart Technologies
Today, organizations operate in an increasingly complex regulatory environment that demands greater transparency and focus on minimizing and managing risk to stay compliant with rules and regulations. Data privacy has become a significant challenge and adds another layer of complexity as not all data may be collected, archived or used for multiple purposes.
Compliance teams are starting to develop a more thoughtful approach to regulatory compliance by defining comprehensive risk taxonomies used for compliance operating models. Emerging technology can play a big role in improving performance, especially in the ability to mimic human behavior and handle relatively routine tasks, such as client onboarding, money laundering and fraud detection. Using smart technologies can greatly improve efficiency and help employees work more effectively by providing data-driven insights.
Smart Technologies in Compliance Risk Management
Businesses using data collection can gather and convert both digital and analog data into a harmonized digital format for analysis and processing. For example, Optical Character Recognition (OCR) converts text from scanned documents and images, including handwriting and forms, into editable and searchable information. Analyzing speech using voice recognition technologies can identify and translate spoken language into digital text, such as trade surveillance or subject matter expert commentary and opinions in audio and video format. Image recognition and digital matching techniques can be leveraged to identify and classify information. These technologies could be used when opening a bank account or reconstructing facts and evidence at an incident scene when dealing with environment and healthcare compliance.
Organizations leverage advanced data analytics practices to detect behavioral patterns, such as fraud detection, or to separate the signal from the noise. Data mining techniques and statistical methods can help identify patterns in large data sets for transaction monitoring. Case-based reasoning helps in decision-making by analyzing a database of existing cases using a similarity metric, such as previous occurrences of money laundering. Rule-based expert systems can mimic the knowledge and reasoning of a human expert like know-your-customer risk ratings.
Machine learning has become a fundamental practice in compliance and risk. Supervised learning uses a dataset of problem instances with known answers to train a machine with constant performance improvement, such as detecting data linkages across policies and documents and constructing citations and semantic linkages. On the other hand, unsupervised learning techniques, including clustering, dimensionality reduction and anomaly detection, find structures in data. An example of unsupervised learning would be to improve detection models related to money laundering.
Often, businesses apply more than one technology to act on findings and leverage the insights from data collection, analysis and learning. Sentiment analysis provides the ability to extract information, such as the author’s attitude, evaluation, emotional state and personality, from various media and attribute it to a brand, concept or point of view. Robotic process automation (RPA) automates previously manual tasks using static rules to make decisions, such as screening negative reports during customer onboarding or processing print forms like loan applications and policy documents.
Natural language understanding translates natural language into machine-readable models through the use of syntactic and semantic analysis, while natural language generation assists in translating machine language to natural language. These technologies, various conversational agents and interfaces (also known as chatbots) enable the automation of advisory services, such as self-service functions and service desks.
Before implementing any technology to address compliance and risk, it’s important to keep your business goals in mind to reap the benefits and set yourself up for success. Ultimately, choosing the smart solution that’s right for your organization can increase efficiency and streamline processes so your teams can focus on higher value tasks.