For Compliance, Prevention through AI is the Best Medicine
For companies nowadays, a culture of compliance isn’t something “nice to have.” It’s a requirement. Regulators are looking more closely at compliance programs, requiring executives and managers to create and maintain a culture that actively promotes compliance. Regulatory guidelines lay out the framework businesses must follow when they are designing their ≈, with the end goal of detecting and preventing criminal conduct.
Traditionally, companies have used approaches like developing strategy, communications, job descriptions and hotlines; hiring a compliance officer at headquarters; providing annual training and monitoring performance evaluations. These means have been helpful in demonstrating a commitment to compliance among employees. Yet often the programs and training came too late, finding that a breach had already occurred.
Managers need to understand the factors that influence employees to behave ethically or unethically to prevent unethical behaviors from endangering a company. Unethical behaviors are due to many different risk factors, such as perception of earned pay-grade, performance pressures, risk tolerance and lack of consequences or accountability. Unethical behavior is also associated with a culture that excuses ethical failures if corporate objectives are met. Stated otherwise: for many it’s okay if the end justifies the means.
Now, companies need to know how to measure and analyze compliance data before unethical or illegal behavior happens. They will need to evaluate high volumes of data to determine if action is needed to prevent breaches of compliance. High-quality data sources with predictive power will enable companies to assess their current culture of compliance and take prompt action when needed. Some new methods include external benchmarking, anonymous reporting, pulse surveys, reputation analyses, management communications, group discussions, exit interviews, and focus groups. Companies also use feedback from external stakeholders, such as contractors, suppliers and customers.
Yet to utilize high volumes of data, companies are relying on cognitive automation technology services for data extraction. Cognitive automation helps organizations intelligently analyze conflicting data sources, automatically identify and reconcile costly data anomalies, and maximize business performance. Policy-based solutions scale to automate extraction, verification and reconciliation rules to continuously audit and analyze diverse structured and unstructured sources regardless of type and volume. By discovering and alerting companies about their data patterns, deviations and inconsistencies in company information, cognitive automation extraction services can even deliver actionable insights needed to proactively seize business opportunities, protect businesses from fraud and abuse, all the while maintaining compliance with regulations and organizational governance.
For compliance, it is no longer enough to train and expect employees to act ethically. Data extraction services are a preventative step to ensuring that unethical patterns are promptly identified, addressed and unethical behavior is thwarted. AI will be a companies best medicine for compliance.