Is Artificial Intelligence and machine learning the future of financial regulation?
Regulators and supervisors can rely on the power of artificial intelligence and machine learning for improved regulatory compliance and supervisory effectiveness.
Evolving regulatory analytics is becoming increasingly reliant on Artificial Intelligence (AI) to sort through massive amounts of data to improve the ability to find misconduct and identify at risk institutions. There has been an explosion of data so vast that without automated support to drive better, data driven decisions and leveraging automation it will be impossible to compete. That being said, development of AI does more than just challenge the supervisors to keep up with industry - it creates opportunities for supervisors to be more efficient and effective in deploying their resources to accomplish their missions, while maintaining appropriate prudential standards. AI will help Central Banks elaborate real-time predictions, using ‘big data’ technologies to define monetary policies.
The SQL Power Suite provides AI as a tool that can help improve financial institutions’ risk management, through more in-depth, comprehensive and informed risk assessment. In these applications, the solution offers an unprecedented depth and breadth of insight, and the ability to act on information and learn from its actions. With the SQL Power solution, dynamic machine learning capabilities are readily available for application in the financial regulation industry.
The SQL Power AI Solution comes bundled with integrated Analytics, and is able to perform in-line analytics enabling real-time decisions within operational systems. Analysts no longer have to remember to look-up acceptable key risk ratios or an organization’s reported metric in the last reporting period or its relative performance to its peer group.
The SQL Power Suite give the Regulator the ability to define their own Key Performance Indicators (KPIs) for a regulated entity, acceptable ranges for each KPI, or acceptable variance year over year. Machine learning algorithms can spot patterns so that examiners are pointed to the right direction when making decisions.
Upon submission, our application can make assessments based on these set parameters and immediately indicate outliers that require further human review with coloured flags (red, yellow or green), a colour-coded up or down arrow, while also allowing the analyst to hover over the submitted metric to view a pop up of the trending graph and a year-over-year performance comparison chart. With the input of data over time the platform provides the foundation for predictive analysis, significantly improving the efficiency and effectiveness of risk assessment programs and supervisory compliance.
The SQL Power Suite’s AI solution is designed to easily integrate with existing governance systems, leveraging existing data and technology investments for a seamless integration. Our platform can be configured to easily evolve with global financial regulation and compliance standards thus future-proofing your organization. Finally, our experienced team of engineers work within your business scale to ensure that our software implementation is smooth and functionally sound.
If your organization could benefit from SQL Power’s advanced AI solution, we’d love to hear from you!