Risk Management Solutions from Teradata
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What is Risk Management?
Risk management, sometimes referred to as risk mitigation, is the process of calculating the maximum acceptable level of overall risk to and from an activity, then using risk assessment techniques to pinpoint the initial level of risk and, if found to be excessive, developing a strategy to mitigate specific individual risks until the collective risk level is pared down to an acceptable level.
In the past, risk management required having humans painstakingly go through an overwhelming amount of data to find suspicious activity. The massive data produced by the Internet of Things makes that impossible. As the pace of business and technology increases, companies are more vulnerable to risk than ever before. The rate of threat is also increasing due to certain factors: Companies are removing the human element within processes and service; and criminals are becoming smarter in how they identify, share and exploit organizational weaknesses. Information management is critical to the new realities of increased crime, staff and client fraud, data security, process failure and compliance to local, national, and global laws.
Analytics-based risk management solutions address the unique risks in different industries by allowing customization of threat intelligence tools that neutralize risks—operational, supply chain, fraud, credit, data/cyber security and regulatory compliance, sales of regulated products—with the potential to do permanent corporate damage. Machine learning and advanced analytical techniques make it possible to illuminate patterns, signals, and trends. Risk and threat profiles can be quantified and prioritized, giving risk management pros clearer focus and streamlining risk reporting processes. Scenarios can be modeled and tested more accurately, thanks to better data and stronger response plans.
Identifying and Avoiding Risks
Institutions that are the most innovative and effective in their response to regulatory mandates will tend to drive future standards and practices. Perhaps more importantly, effective internal performance analysis and measurement mandates this seamless linkage and transparency.
They will develop new analytic capabilities that provide companies with an integrated risk view to identify potential risks quicker and quantify exposure across the enterprise, including operational, reputational, technological, product, security/cyber, and fraud. They will possess the increased ability to detect fraud—especially fraud conducted by insiders, such as employees, contractors and partners, which is the most common type of fraud and typically very difficult to detect. They will take new information sources to spot risk issues never previously possible at scale (e.g. voice recordings, claims submissions/staff email records and patterns of behavior across multiple channels). They will automate risk monitoring rules across multiple disciplines (e.g. credit, fraud, internal compliance to processes, information access). Finally, they will avoid future costs/exposure by getting onto the 'front foot' and investing in being future-ready.
The most effective risk mitigation strategies identify and address patterns, trends, and signals that are otherwise invisible.
In the past, risk management required having humans painstakingly go through an overwhelming amount of data to find suspicious activity. The massive data produced by the Internet of Things makes that impossible. As the pace of business and technology increases, companies are more vulnerable to risk than ever before. The rate of threat is also increasing due to certain factors: Companies are removing the human element within processes and service; and criminals are becoming smarter in how they identify, share and exploit organizational weaknesses. Information management is critical to the new realities of increased crime, staff and client fraud, data security, process failure and compliance to local, national, and global laws.
Analytics-based risk management solutions address the unique risks in different industries by allowing customization of threat intelligence tools that neutralize risks—operational, supply chain, fraud, credit, data/cyber security and regulatory compliance, sales of regulated products—with the potential to do permanent corporate damage. Machine learning and advanced analytical techniques make it possible to illuminate patterns, signals, and trends. Risk and threat profiles can be quantified and prioritized, giving risk management pros clearer focus and streamlining risk reporting processes. Scenarios can be modeled and tested more accurately, thanks to better data and stronger response plans.
Identifying and Avoiding Risks
Institutions that are the most innovative and effective in their response to regulatory mandates will tend to drive future standards and practices. Perhaps more importantly, effective internal performance analysis and measurement mandates this seamless linkage and transparency.
They will develop new analytic capabilities that provide companies with an integrated risk view to identify potential risks quicker and quantify exposure across the enterprise, including operational, reputational, technological, product, security/cyber, and fraud. They will possess the increased ability to detect fraud—especially fraud conducted by insiders, such as employees, contractors and partners, which is the most common type of fraud and typically very difficult to detect. They will take new information sources to spot risk issues never previously possible at scale (e.g. voice recordings, claims submissions/staff email records and patterns of behavior across multiple channels). They will automate risk monitoring rules across multiple disciplines (e.g. credit, fraud, internal compliance to processes, information access). Finally, they will avoid future costs/exposure by getting onto the 'front foot' and investing in being future-ready.
The most effective risk mitigation strategies identify and address patterns, trends, and signals that are otherwise invisible.
- Identify Vulnerabilities: find and quantify areas of potential weakness.
- Proactive Defense: establish monitoring and advanced threat intelligence.
- Risk Management Models: account for all risk categories—IT, brand, operational.
- Fraud and security risk varies by industry, but all businesses require the ability to improve their capability to identify potentially fraudulent situations and mitigate them quickly.
- Businesses face the potential for a huge increase in online and claims fraud, and identity theft.
- Operational risk is increasing and can materially affect a company’s reputation with their investors and clients. The result could be huge fines and mitigations.
- Regulatory compliance across industries is demanding more complex analytic and reporting linkage, involving expensive and time-consuming projects.
- Cyber breaches are increasing in sophistication and impact, leading to higher security risk in all areas of the business, including operations, finance, and global perception of the brand.