Risk analytics tools boost operational efficiency. But do you know what tools to implement to derive the best results?
With the burgeoning demand for big data all over the world, major corporate houses are taking risk analytics – the process of collecting, analyzing and measuring real-time data to forecast future risk for improved decision-making – to a new high.
Risk analytics is an umbrella term – there are a lot of things that pops up in mind when we utter the word Risk Analytics. A whole lot of specialized risk analytics products is now available for CFO’s to evaluate, what they need now is the right implementation, that’s it.
Today, there exist two main types of risks: Internal and External. External risks relate to those risks that take place outside the firm, and are dependent on government regulation, economic trends, and competitive markets and so on. It is this risk that relies heavily on data. As this particular type of risk is related to an entire economic system – hence, outside the jurisdiction of the company. However, companies can use quantitative techniques– benchmarking or probabilistic modeling software helps in adapting ourselves to the new data that arrives.
In contrary, internal risks are more on-the point and controllable in nature. Organizations look forward to operational risk assessment to improve the decision-making process. For that, Compliance Risk Assessment is to be considered, especially in the industries, like agriculture and banking.
Besides, a good number of veritable enterprise governance, risk and compliance products are up on offer – they provide organizations some ways to discern and analyze some kinds of identified risks occurring at diverse levels within the management. Also, there are a few highly advanced industry-specific risk analytic tools devised for the financial sector, which are also a real treat for the analytic professionals.
Now the times have changed, risk analytics software has evolved from being tactical solutions to useful solutions to optimize strategic future of the companies. “Especially for banks and credit unions, risk analytics tools are focused more on strategy and the need to integrate with other departments, like finance,” said Danny Baker, vice president of market strategy, financial and risk management solutions at Fiserv Inc., a financial technology firm based in Wisconsin. “The integration across departments is key.”
It’s true that Risk Analytics tools and packages can solve complex issues in a jiffy, but if adequate data is not available, even god can’t save them. Many times, major conglomerates face issues with the quality of data –you may face some challenges in the ETL processes, which require a comprehensive skill set and needs to be backed by a large, superior team of developers. In these times, an inherent risk of not having adequate transparency of data causes trouble in minimizing data quality risks.
Maintaining a proper database is crucial for fuller optimization of risk analytics tools. A database that minimizes ETL dependency, while offering an expansive view of all types of data makes risk analytics better, robust and inexpensive need to be considered. So, in a nutshell, it is to be concurred that by gathering all of company’s data in one place actually leads to better risk-based decisions, which is of course not wrong in any way.
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