A Strategic Approach to Risk Analytics: Essential Insights for Executives

More and more companies nowadays are applying big data, intelligent tools, and advanced analytics to enhance their decision-making processes, especially when handling factors that may negatively affect a company’s stability.

From artificial intelligence to machine learning to the Internet of Things, companies are leveraging various instruments to improve service delivery. It’s no wonder that the global risk analytics market size is projected to reach $54.95 billion by 2027, with a CAGR of 12.2% during the forecast period.

Risk factors should be analyzed before any emerging issues become too serious, and in turn, the adoption of these robust risk analysis techniques can become transformative for the company.

In this article, we’ll explore what risk analytics is and the steps it comprises, an overview of its benefits in various industries, and key components to be considered by executives to mitigate risks for their companies.

What is risk analytics? 

Risk analytics is a set of methods developed to assess, describe, and foresee risks. 

With everyday reports about leaks, malicious activities, and data theft, the business environment is becoming increasingly vulnerable to threats. 

Primarily, banking and financial institutions remain the most susceptible to risks. Financial risk analytics helps identify, measure, and manage the risks that have the potential to disintegrate the financial stability of an organization. 

Risk analytics creates a responsive and adaptable analytical framework to track and monitor data by providing a 360-degree view of the business’ state, enhancing transparency, and prompting self-service reporting and analysis. In the financial sector, for example, it helps perform analyses within asset classes such as equity, debt, and other investments, in order to mitigate any risks associated with intended harmful acts.

Most common industries that use risk analytics

Let’s take a closer look at some key industries where risk analytics is particularly useful:

• Banking, Financial Services, and Insurance (BFSI)

With strict regulations and compliance requirements, banking and finance rely heavily on risk analysis to navigate challenges of the industry and potential threats.

• Government

From weather forecasting to border security management, risk analytics is the backbone of government operations. With cyber attacks on the rise, governments are doubling down on predictive analytics to strengthen their threat prevention measures and make informed decisions that shape our world.

• Telecommunications

Given the level of competition in telecommunications, the companies in this industry are facing reduced revenues. Hence more and more telecom operators are turning to risk analytics solutions to be secured from revenue leakage, therefore increasing their revenue.

• Healthcare

In the realm of healthcare, risk analytics isn’t just about numbers—it’s about saving lives. From ensuring patient safety to controlling drug contamination, analytics-driven insights are revolutionizing the way healthcare organizations operate.

From consumer goods, manufacturing, transportation, and beyond, risk analytics is the secret sauce that fuels success in today’s unpredictable world. The demand for risk analytics will only continue to grow, driving innovation and resilience across industries.

Key benefits of risk analytics

There are several key benefits of risk analytics for companies:

• Reduced costs

By using risk analytics tools, businesses can significantly cut expenses. Business intelligence tools allow companies to convert raw data into insights that help make well-informed decisions to mitigate potential economic losses.

• Combating frauds

Artificial intelligence and machine learning tools help companies analyze massive amounts of data and eliminate suspicious activities. By identifying errors and wrongful activities, they enhance security measures and prevent frauds.

• Long-term planning

By gaining insights into potential threats and vulnerabilities, companies may implement a set of actions to prepare for various negative events. This helps build a holistic planning framework where a business is not overly dependent on external factors and can operate under any circumstances, even if something unexpected occurs.

7 steps in setting up a risk analytics system

When managing medium to large size businesses, risk analysis becomes complex since each department has its own viewpoint and perspective of business operations. As a result, the only solution is for organizations to streamline their risk management and have a single source of truth for risk-related data. The following are the seven steps to follow in implementing risk analytics in an organization with multiple departments and siloed data:

• Step 1: Build a comprehensive risk library

By building an extensive library of potential threats accessible to all departments, it will be easier to have a common vision of potential issues. The library should include a wide range of scenarios, such as factors that could cause a risk event. The company departments can then develop scorecards and heat maps to highlight potential risks that could arise.

• Step 2: Review and validate data sources

Define crucial risk indicators and assess their usefulness by validating them through spot-testing data sources. Managers should assess risks, estimate potential negative effects, and identify possible decisions to control risk. The number of risk factors should be refined at different levels, ranging from very small unit-based issue assessments to corporate priorities.

• Step 3: Consolidate data sources

Centralize all data onto a single platform and implement a monitoring system to monitor and report risk continuously.

• Step 4: Automate testing

Implement automation to validate controls and set up trigger alerts for immediate action.

• Step 5: Visualize

Implement risk monitoring dashboards to identify patterns and assess risks.

• Step 6: Report

Regular insights encourage agility and help quickly identify and assess changing risk conditions learned from both success and error. Communicate insights regularly and effectively by using visualization tools.

• Step 7: Scale

When departments are more knowledgeable about risk analysis, apply them to a broader range of situations and consolidate them on a single platform. 

Share knowledge and processes to constantly upgrade teams’ risk management capabilities. With access to more data, organizations can conduct comprehensive testing and refine their risk management strategies continually.

To sum it up

As businesses continue to strive for the right balance between innovation and growth, the need for advanced analytics tools will only increase. From banking and financial services to government sectors, telecommunications, and healthcare, the applications of risk analytics are vast and far-reaching. By leveraging risk analytics, organizations can identify and minimize risks, securing their financial and operational integrity.

Kanda helps companies build complex risk analytics systems based on the unique requirements of organizations from various domains and sizes. 

With over 20 years of experience in data analysis and software development, we are able to provide top-notch, highly sensitive solutions through the use of innovative technologies. 

Talk to our experts and start your journey to a more secure future with us.