We are coping with the disruption of life in modern times. Amid challenges like medical innovation, the management of healthcare professionals, and ensuring the right information reaches citizens, we are also trying to keep the global economy afloat. Luckily, we live in a time where technology enables us to maintain a connection, even in a time of physical disconnection.
There is no time to slow down during a global pandemic; we have to remember that commerce still makes the world go ‘round. This is why leveraging machine learning models and becoming a data-driven enterprise enables you to navigate in a highly risk-averse ecosystem. Safeguarding with machine learning algorithms and using them to assess risk has become the cornerstone for accelerating performance during a time of great social and financial distress.
Cultivating the Right Mindset
The rules of the game have changed with COVID-19. We are suddenly faced with a broken supply chain and operations, limited resources, and unknowns about next week, next month, next quarter, and year.
Having good information and good data, together with the capacity to make good decisions using data analysis, assists in the cultivation of the right mindset. Algorithms help adopt a risk-aware mentality to lead in the marketplace, equip enterprises to navigate the regulatory environment, and disrupt the industry through innovation. Take GM & Toyota, who are now delivering personalized shop-at-home initiatives to digitize buying a car.
To thrive in uncertain times, data-driven decisions and accurate risk assessment using nimble technologies, help us respond rapidly to unknowns and to mitigate potential risks. By pushing back on the urge to submerge in this highly risk-averse ecosystem, and instead becoming risk-aware, it becomes possible to navigate during a difficult time.
Safeguarding using Algorithms
Business spending on cognitive technologies is rapidly growing and is still expected to continue at a five-year compound annual growth rate of 55 percent to nearly $47 billion this year. Going forward, algorithms will be used to power many of the IoT-based smart applications across a myriad of industries seeing a broader use of machine learning-based algorithms.
Decision making will have a profound impact on customers who will be influenced by these algorithms—including what information they will be exposed to, whether or not they will want to engage, and also when and where to invest time and resources.
Algorithms are the arcane ‘black boxes’ of decision making, making it critical to put mechanisms in place to deeply analyze data and manage associated risks.
Machine Learning for Risk Assessment
To thrive in uncertain times, data-driven decisions and accurate risk assessment are more critical than ever. Navigating with accuracy into the future ecosystem using machine learning algorithms helps us move forward and become risk-aware.
Risk-informed decisions are used in circumstances where something of value is at stake. That’s why the machine learning approach allows for the prediction of possible future risk scenarios. Understanding whether the system is, or may be improving or worsening in terms of risk, is a fundamental component of making smarter decisions.
When data is processed, risk modeling helps to appropriately manipulate large datasets that have been collected, describing the state of the data to produce meaningful information.
We have to extract and assess the right data to move forward, and using risk analysis by harnessing machine learning, coupled with new digital tools, will lead to new techniques, insights, and opportunities for becoming less risk-averse.
Liquid Analytics Vantage Point
Liquid Analytics’ Confidence AI solution allows enterprises to thrive during times like these by enabling them to make data-driven decisions and accurate risk assessments. Confidence AI produces consistent systemized multi-factor models that eliminate the noise and reduce statistical error to deliver the most valuable insights to drive results-based action for your organization.
It provides users with complete data across segments, eliminating the risk of making decisions based on information captured by manual methods and biased by subjective human analysis.
Confidence AI allows you to process information over time. Organizations can use Confidence AI as it learns from new data with usage by specific segment experts in real-time, and continuously building on this data.
Your team no longer has to manually gather and analyze individual pieces of data, which saves time and increases confidence and accuracy of decision-making, while assessing cash flow risk and opportunity.
Analyst Bottom Line
Embracing the complexity of managing risks during COVID-19 can go a long way when the power of algorithms is harnessed. Organizations that adopt a risk-aware mindset will do so with machine learning to create a risk assessment approach that relies on the reliability of algorithms.
Predicting risk needs to be carried out using appropriate data analysis. If precautions are measured, making the right decisions will become a smoother process and accelerate long-term performance.
How prepared are you to manage risk during unprecedented times? Reach out to us for a deeper conversation.