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How Decision Management Systems Boost Data Analytics In Risk Management

During the pandemic, digital transformation in organizations jumped within 90 days, compared to a predicted ten years. McKinsey referred to this surge of digitization as “The Quickening.” Savvy risk managers recognized the trend, and improving data analytics in risk management became a hot topic. But if you want to navigate the ever-changing risk landscape, you must use the right tools.

Innovation is now vital for businesses in our new modern, digital world. The traditional Business Rules Management Systems (BRMS) have worked well. But there are now more advanced ways to analyze data. Decision Management Systems (DMS) is the new kid on the block. Find out how DMS can help you take your risk management analysis to the next level.

What is a Business Rules Management System (BRMS)? 

Before we get into the nitty-gritty and compare the two different systems, it’s best to overview BRMS briefly. Business Rules Management (BRM) is the practice and process of the following:

  • Formally defining your business rules
  • Implementing the defined rules
  • Managing the rules on a consistently
  • Automating the deployment of the rules

BRMS is the technological platform through which you can use BRM. The BRMS allows you to manage the entire business rules lifecycle. You can define and store rules as formal business logic. You can also audit the existing rules and manage the decision logic that guides the automation. It allows you to make smart decisions consistently and quickly with little human intervention. 

What is a Decision Management System (DMS)? 

The new kid on the block is even better. In a nutshell, a Decision Management System (DMS) is another layer placed on top of BRMS. The regulators love DMS as it provides another layer of transparency. Imagine as a risk manager having all the functionality of BRMS. But on top of this, being able to boost your data analytics in risk management even further. 

You need to have the equivalent technology in your organization to analyze new Big Data. Traditional operating systems, such as a BRMS are unable to handle this data. DMS is far more flexible. You can apply analytical techniques to DMS and gain the most value from your data. With DMS, you can seamlessly integrate the results of predictive analytics models and business rules into your operational systems. 

The Agility and ROI of DMS

DMS systems are adaptive, analytical, and agile. Their design means they can constantly adapt. The system automatically learns from successes and failures so it can improve decisions. DMS can also take all available data and analyze it to enhance decision-making quality. Additionally, they are also agile enough to handle rapid changes to regulations and update accordingly.

If you don’t harness this new technology, it will affect your profitability. Your organization will be too slow to respond to regulatory updates. Also, you could struggle to keep up with competitors who are using DMS. These systems can provide a high-level return on investment in several areas of your business:

  • Improving risk management 
  • Increased operational efficiency of the business
  • Boosting business performance across the board

The World Is Already Jumping On Board

A study found that the global decision management market value will grow to $11.4 million by 2028. If this hits the target as predicted, it will be a considerable jump from the global market value of $4 million in  2020. Already companies utilize these systems to reduce business risk and ensure they are compliant. No organization wants to face the scrutiny of regulators or face potentially hefty fines.

The Main Differences Between BRMS And DMS

As mentioned earlier, DMS adds a new level to BRMS. With BRMS, you can use the predefined business rules for regulatory requirements, risk models, internal policies, customer communication preferences, etc. With DMS, your decision-making is more finely tuned as you can use predictive technologies to help you. For example, artificial intelligence and machine learning can help you with fraud detection and the subsequent best actions for customers. In financial or insurance industries, holistic decision requirements are essential. It is crucial because there are always two dimensions - business and regulatory. The beauty of DMS is that it can combine business questions and regulatory compliance questions into one decision model. This capability makes your risk management more intelligent and more efficient.

How To Handle The Investment In Risk Technology

It can sometimes be challenging to secure investment into risk technology. At Ventiv, we understand that getting colleagues on board can be a balancing act. You can download Ventiv’s free guide to help you. The guide explains how to make a business case for investing in risk technology. This ebook has helped many organizations to improve their risk management.

DMS is a new frontier of risk management, and you can utilize your data like you never have before. DMS should be a key part of a risk manager’s tools to help you manage business risk. DMS makes you more agile and responsive as your business is more streamlined. A streamlined organization is essential for both insurance and risk management spheres. 

Level Up Your Data Analytics in Risk Management

If you want to level up your risk management processes, AI and data analytics can help you. Be bold and ramp up your risk management strategy by adopting new technology out there. BRMS serves its purpose, but the evolution to DMS is a game-changer. Chat with an expert to learn how data analytics in risk management can help your business.

 

 
 
 
 
 

Apr 27, 2022

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