Data Analytics: Efficient risk management

Category: Cyber Security, Data Management, Machine Learning, Management

“The risk management needs to lift up from risk control to risk intelligence which can identify the potential business growth opportunities.”― Pearl Zhu

Businesses need to constantly upgrade themselves to handle the risks emerging from a dynamic environment that is fraught with risk globally. They need to do a deep dive into their risk management strategies and look at fostering a culture of change for unlocking their business potential and achieving better business outcomes. Organizations need to think beyond traditional risk management methods through organisational transformation by adopting advancement technologies like advanced analytics. Let’s look at some of the ways by which it can be achieved. 

As a first step employees from the different levels of the organization need to actively participate in this journey for building their core competency and redefining the business processes. This would help in breaking the functional silos and unearth the value of data for building effective data models for forecasting future trends through collaboration and knowledge sharing. Customer is king and leveraging on new age analytics would help understanding the changing customer behavior by establishing customer models and identifying underlying patterns. By leveraging on data mining techniques large quantities of data can be analysed for better client engagement, revenue growth and cost optimisation. Using big data and analytics would also help businesses rethink their marketing campaigns by understanding customer behavior. 

Analytics help in assessing the exposure of the organization’s risk and its ability to measure and predict likely scenarios through forecasting techniques. In this process the analysts would come across huge volumes of data which could be structured or unstructured. Structured data are more qualitative in nature that would include numbers and values sourced form online forms network and server logs etc with limited usage and storage options. These can be used with the help of Machine Learning algorithms by business users. Unstructured data include posts in social media, website, internet of things which is gaining widespread importance due to its native format and scalable storage options. The availability of data can be both internal and external to the organization. Risk analytics helps in integrating them for deriving valuable business insights vand effective decision making. 

By analysing myriads of data sets and repetitive trend risk analytics helps In identifying and detecting any threats in their businesses, example frauds. Leadership can track the changes that resulted in transformations to the industry and take appreciated actions in the midst of crisis. It would help in preventing any damage done to the corporate identity and protect the brand image of the company. Organisations need to learn from the mistakes of their past and ensure that they are not repeated. Analytics help in understanding the reasons behind such mistakes and preventing them from happening again by applying preventive measures. All companies irrespective of their vintage or size need to have a dedicated team of risk managers who can use big data and analytics to evaluate risks in real time and quickly what gears and take appreciated actions during uncertainty. Creation of alerts for monitoring deviations in real time would help in identifying any outliers for problem solving and evaluating performance. 


We at Newlineinfo Corp make use of latest technologies like Artificial Intelligence, Machine Learning and Internet of things for evaluation risks and manage them proactively with the help of risk analytics tools for achieving business growth and resilience.