The Generative AI-nxiety for Regulatory Change Management

2023 is shaping up to be the year of generative AI technology. Both tech and non-tech circles are abuzz about how generative AI can improve human productivity and even replace people.

A recent BCG survey found that workers are both curious and optimistic about the emergence of generative AI. 26% of workers now use ChatGPT, regarded as the face of generative AI, multiple times every week, and 46% have experimented with ChatGPT at least once.

In this context, it's crucial to delve into the disruptions and possible opportunities that generative AI is creating in the change management space.

In recent years, change management has been among the toughest challenges for companies in areas like governance, risk management, and regulatory compliance. So, how can generative AI bring ease to regulatory change management across industries?

Getting it Right: What is Regulatory Change Management?

Regulatory change management is, by definition, the process by which organizations can adapt to changing regulations in their sector. The problem is that most organizations find it challenging to keep pace with changing industry regulations. Regulatory change management makes it easier for them to implement new regulatory policies and controls in line with the evolving requirements.

The Role of Generative AI in Regulatory Change Management

Organizations spend plenty of time and effort aligning their operations with industry regulations. Here are some of the key aspects of regulatory change management:

• Defining which regulations apply to the organization
• Monitoring changes in regulatory legislation and activities
• Understanding the impact of any regulatory change on the organization's existing policies
• Identifying the business processes and procedures likely to be impacted by regulatory changes
• Recognizing how regulatory changes can impact customers

Can generative AI address these challenges?

Applications of Generative AI in Regulatory Change Management

Regulatory change management is a lot more than simply meeting compliance requirements. A significant way in which generative AI can simplify regulatory change management is in the implementation process. Here are four applications of generative AI technology in this domain:

Mastering Regulatory Transformation: Navigating Change with Precision

In the realm of industry regulations and ever-evolving changes, organizations are often bound by strict timelines for implementing and conforming to these transformations. This process can be both exhaustive and time-consuming. In this scenario, traditional manual monitoring processes no longer cut it when it comes to handling the influx of regulatory changes.

Enter generative AI tools, equipped to anticipate, capture, and meticulously track regulatory shifts through automated workflows. For instance, compliance teams can deploy AI tools to vigilantly monitor real-time updates on the websites of regulatory bodies governing their specific industries.

Leveraging their natural language processing (NLP) capabilities, these generative AI tools go beyond data collection; they possess the ability to analyze and understand complex regulatory requirements. What's more, they deftly sift through vast troves of regulatory data, interpreting nuances and extracting precise meanings with precision and efficiency.

This also makes generative AI a potent tool for not just identifying shifts in regulations but also changes across different versions of the same compliance policies. It enables businesses to discover and compare missing compliance policies and gaps in compliance initiatives that need to be addressed.

Revolutionizing Regulatory Change Management in Other Aspects

In addition to facilitating comprehensive implementation of regulatory changes, generative AI plays a significant role in other areas of change management that can lead to richer processes, reduced risks, and greater security and prevention measures.

1. Risk Management
Organizations must integrate regulatory compliance with their operational risk strategies for the assessment of compliance-related risks.

Favorably, generative AI can help assess and analyze risks through data patterns and trends that indicate non-compliance. For example, it can identify data anomalies in business transactions, which could indicate regulatory violations.

Using generative AI models, compliance professionals can simulate worst-case scenarios, thus allowing them to evaluate potential risks and impacts. They can also test and modify their risk management strategies to address various business scenarios.

The applications associated with this are manifold. For instance, U.S.-based compliance officers can perform compliance risk assessments in law enforcement agencies like the U.S. Department of Justice.

2. Fraud Detection
Compliance teams spend a lot of time and effort identifying fraudulent activities. Generative AI tools can save time and money spent on manual fraud detection.

Using synthetic data, organizations can train machine learning models to detect data anomalies and deviations that indicate fraudulent practices. With this application, companies can reduce the risk of financial losses and damage to their market reputation.

3. Data Governance and Compliance
Among other applications, generative AI can transform data governance and compliance. High-quality data is the cornerstone of effective data governance.

Generative AI can identify and fix data-related problems like inconsistent, incomplete, or missing data. It can synthesize new data for missing values.

For regulatory change management, generative AI tools can come in handy to evaluate risks and the impact of compliance-related changes on the business. They can automate the tedious manual monitoring of real-time transactions and compliance-related processes.

The Way Forward: How to Embrace Generative AI for Compliance

Recent research from McKinsey outlines how generative AI's influence on productivity could add around $2.6 trillion to $4.4 trillion across different use cases.

It could prove to be a game-changer, especially across highly regulated industries like the banking and financial sector, where compliance and legal needs are frequent and profound.

As an AI specialist, Xoriant enables organizations to embrace generative AI for a host of use cases and applications. We have enabled enterprises across diverse industries, including manufacturing, financial services, and healthcare, to leverage AI capabilities for their business growth.

Catalyzing Compliance Excellence with ORIAN for RCM

Introducing the ORIAN generative AI Platform for Regulatory Change Management, a pioneering solution designed to empower your organization in navigating the complex landscape of evolving regulations with confidence and efficiency. Our platform is engineered to excel in three key areas:

• Comparison and differential analysis: Uncovering regulatory evolution with precision
• Comprehensive compliance assessment: Evaluating compliance levels and pinpointing regulatory gaps with ease
• Proactive mitigations: Providing intelligent recommendations based on document insights and knowledge management

Get in touch with us to learn more about how you can adopt generative AI technologies to accommodate seamless regulatory change management.