There has been several trends driving regulations in Vendor Risk Management space that has had organization take a deeper dive into supplier risk, some of these include:
1. Greater Overall Interest in Enterprise and Operational Risk:
Supplier risk is a type of operational risk, which is taking on more importance to regulators. In May 2012, Thomas Curry, head of the Comptroller of the Currency, said the operational risk is “currently at the top of the list of safety and soundness issues and might have eclipsed credit risk as a safety and soundness challenge.”
2. Changing Nature of Outsourcing:
Insurance companies are outsourcing an increasing number of sensitive functions (e.g., policy administration, customer support centers, claims processing) which materially increases the need for better vendor management. Additionally, the growth of cloud computing and other technologies presents new challenges as to where sensitive data is stored and what protections of this data exist. The regulators know that suppliers are the soft underbelly for cyber-security and privacy risks
3. Greater Interest in Compliance Risk:
The Dodd-Frank act requirements are leading to more supervisory focus on compliance risks, which mean greater regulatory scrutiny of suppliers, especially suppliers that interact directly with customers or have customer data
Our Vendor Risk Management Solution:
With increasing new regulatory mandates of DODD-FRANK, HIPAA HITECH and other government regulations, Aponia Data has created a predictive risk analytics solution to support the forecasting of risk events and the impact in vendor risk management. This will allow mid-markets to comply quickly, while reducing the overhead of high salaried employees.
Risk Management Features:
• Updated control polices: e.g. ISO 27001 v2013, COBIT, Basel IV
• Compliance with Dodd-Frank and HIPAA-HITECH Regs.
• Custom Client User Experience for Risk Dashboar
Predictive Analytics and BI Features:
• Predictive Risk Management Engine to help find risk, and improve vendor management with minimal human interaction.
• Provide the data clients need, leave out the noise
Big Data Features:
• Built for size, scalability, flexibility and performance
• Merge Structured and Unstructured sources.
• Funnel all components and data into one engine