Laying the Foundation: Crafting the First Phase of an AI-Enhanced Legal Application

Now in this edition of the Legal Informatics Newsletter we will try to build a bridge from the theoretical aspects discussed so far towards the planning and development of a practical use case. Any of such possible Legal AI Tech Applications will have its specific technical and legal challenges. So, there is no obvious right use case to start with.

The use case we will start with is an Automated Legal Compliance Application. That for the simple reason, that we do have various planning and design but also legal ?data and workflow aspects in compliance which will help us to showcase the relevance of many of the theoretical aspects we have discussed already in the previous editions of the Legal Informatics Newsletter.

Introduction

Traditionally, ensuring compliance with a large pocket of internal policies and external regulations is a labour-intensive and time-consuming task. It requires meticulous attention to detail, a deep understanding of complex legal texts, and constant vigilance to keep up with the ever-changing legal landscape.

The compliance function is usually not an area with rich budgets and an oversupply of workforce. Clearly supporting that work force in routine tasks and automating various elements of the daily routines and workflows will enhance their ability to focus on more important quality work.

Here are some of the key aspects we need to consider:

1. Identifying the Scope: Along with defining the range of regulations, consider the different user groups that will interact with the application. These would include compliance officers, other staff members, and potentially even suppliers, clients or customers.
2. Gathering and Organizing Data: While organizing the data, consider how it can be presented in a way that is easily understandable and useful for the different user groups. This involves creating different levels of detail or using clear and simple language. When we go about collecting information and data, we also need to consider a data model for our compliance application
3. Defining the Compliance Rules: Along with translating the legal rules and regulations as well as internal provisions and other relevant texts into data and rules, we need to consider how this information can be used to provide guidance and training to the users.
4. Designing the User Interface: User Interaction is a key for any knowledge specific application to keep the interest and appreciation of the users up.
5. Selection of Technology: Once we have a scope, identified data sources and routines, as well as a basic design of our application we need to decide on the appropriate technologies
6. Building and Testing the Application: now start with building and then testing the application, gather feedback from users and other stakeholders in the project in order to refine and improve.
7. Implementing and Monitoring: After implementation, monitor not only the application's performance but also its usage by the different user groups in order to further improve but also make sure the application is secure.
8. Updating and Refining: Such an application is in an ongoing process of regularly update and refining to better meet the users' needs but also catch changes in laws and regulations and new challenges in the relevant area of compliance.

Scope and Gathering of Information and Data

Defining the scope of a compliance application is a critical first step in ensuring its effectiveness and alignment with a company's specific legal and regulatory requirements.

Some Key Steps for Defining the Scope of Your Compliance Application

1. Identify the Relevant Compliance Areas, Data Sources and Workflows

·??????? Assessment of Requirements: Begin by conducting a comprehensive assessment of the regulatory landscape that impacts your business. This includes understanding federal, regional, local, and international laws that are relevant for your business.

·??????? Data Sources: Define the relevant data sources and which of them can be imported automatically and which are depended on human in the loop interaction. This will include laws, regulations, precedent judgements but also industry standards, opinions and other relevant sources.

·??????? Workflows: Include descriptions of working routines and specific knowledge and know-how of domain experts (in the compliance department but also those departments that are affected by the compliance regulations and objectives).

·??????? Internal Policies: Don’t overlook internal policies and procedures that need enforcement. These may include everything from data protection practices to ethical guidelines

2. Engage with Stakeholders

·??????? Gather Input: Engage with key stakeholders such as compliance officers, legal teams, IT personnel, and business unit leaders to gather insights and expectations.

·??????? Identify undocumented information: Every business has lots of routines and rules that are not documented but constantly complied with. Such information needs to be documented in order to be able to catch it in our compliance applciation

·??????? Define Priorities: Use these discussions to identify which rules have priority over others

·??????? Define Gaps: find agreement what automation shall cover and which routines might be left out (at least for a start).

3. Determine Application Capabilities

·??????? Technology Mapping: Outline what technologies and tools will be needed to address the identified compliance areas effectively. Consider capabilities like real-time monitoring, data analysis, reporting, and user interaction.

·??????? Feasibility: Evaluate the technological and operational feasibility of integrating these tools into the existing systems environment of your business and how such systems might interact

·??????? Data Model: We need to consider a flexible data model that can represent in particular legal regulations and their interconnection and dependences.

·??????? Rule Application: In the development of an AI-driven legal compliance application, a critical step is the identification and extraction of rules from comprehensive legal documents. This process begins with the meticulous analysis of laws, regulations, industry standards and best practices, ?case law relevant to the business as well as internal compliance regulations and is performed with the support of ?legal experts who pinpoint precise rule-based directives within the texts. These directives specify required or prohibited actions under specified conditions and are essential for defining the operational boundaries of the compliance system.

Once these rules are clearly identified and validated, they need to be structured logically—using conditions, obligations, and exceptions—and then translated into a format that can be encoded into the application's rule-based engine.

The objective is to create an algorithm that uses the rules to e.g. represents and explains, monitors compliance regulations, detects violations, and provide guidance to the users. This process requires a combination of legal expertise and technical skills, as well as careful validation and testing to ensure the rules are accurate and reliable so we? can enable the application to understand and apply the compliance regulations effectively.

4. Set Goals

·??????? Specific Objectives: Establish clear, measurable goals for what the application should achieve. This might e.g. include reducing compliance-related errors, decreasing the time spent on compliance tasks, or improving audit readiness.

·??????? Performance Reviews: Define how performance will be measured and reviewed and how feedback can help to further improve.

·??????? Manage Expectations: Make sure form the outset that expectations in terms of short, mid and longterm objectives are kept realistic and are well communicated.

·??????? Cost: Manage cost well and size the project in line with a cost to value perspective.

5. Plan for Scalability and Flexibility

·??????? Future-Proofing: Consider future growth and changes in the regulatory environment. The application should be scalable to accommodate business expansion and flexible enough to update as laws and regulations change and/or evolve.

·??????? Integration Considerations: Ensure the application can integrate smoothly with existing systems and workflows without requiring extensive costly adaptations.

6. Define User Needs and Accessibility

·??????? User Profiles: Develop detailed profiles for different types of application users, such as compliance officers, managers, and frontline employees, understanding their unique needs and challenges.

·??????? Functionality: such an application can provide for a multitude of functions and serve on end the compliance officers in their daily routine but also on the other side be a training tool for everyone subject to such compliance regulation as well as a source for Q&A interaction saving time of the compliance team.

·??????? Accessibility Features: Plan for accessibility features that ensure all employees, regardless of their role or location, can use the application effectively.

·??????? Communicate: Availability and Accessibility need to be communicated in a clear and simple way, so plan for that as well

·??????? Support: plan for user support in using the application and catch feed back in that line at the same time for future improvement or enhancement.

7. Outline Legal and Data Requirements

·??????? Compliance with Compliance: Ensure that the application itself complies with relevant data protection regulations, such as GDPR, depending on your location and industry.

·??????? Data and Systems Security: Define the security measures needed to protect sensitive information processed by the application and avoid any misuse of the application.

·??????? Data Update: Legal Data and information, including laws, regulations, judgments but also relevant industry standards are constantly changing, the application needs therefore be flexible and have routines to deal with these changes

·??????? Time Stamp: Legal regulations apply differently over time – it is very important to foresee a time stamp function that allows to differentiate e.g. when a particular regulation has been applicable, how and when it has been amended and come out of force. The same applies for routines and processes subject to the compliance exercise.

·??????? Log Files: Log Files are a key data source. They keep track of the interaction between user and system. Even if such data is recorded on an anonymous basis such data is extremely helpful in spotting relevant topics, potential misunderstandings or even gaps in in data and/or regulations and support the future development and improvement of the application.

8. Prepare for Implementation and Review

·??????? Communication: Consider Communicating the project broadly and extensively to (i) achieve buy-in and collaboration and (ii) to avoid any speculation and opposition because of a “secretive” approach

·??????? Pilot Programs: Consider setting up pilot programs or phased rollouts to test the application with a smaller user group before full-scale implementation.

·??????? Quick Wins: Quite often pilots allow to showcase some quick wins that take off a particular burden for users or allow for better accessibility of data or other relevant information

·??????? Continuous Feedback: Establish mechanisms for ongoing feedback from users and stakeholders to continually refine the application during development as well as post-launch.

Clearly the above is just a overview list of relevant topics and not a complete checklist, which needs to be developed individually for such a project taking onto account the industry as well as the company specific environment. By carefully defining the scope of your compliance application, you ensure that the development process is guided by a clear understanding of what needs to be achieved and how it aligns with your business objectives. This preparation not only enhances the application's relevance and effectiveness but also supports a smoother implementation and adoption process.

Technology:

Now we need to turn to think about which technology we want to use. Clearly in compliance we should aim for applications that provide correct, reliable and explainable answers, the system application as such should be (very) transparent. The choice of technology plays a crucial role in the success of an automated AI compliance application. It determines the application's capabilities, efficiency, and scalability.

It is also important to stress that there is no one AI system that really does it all, it is therefore important to find the right components and to fit them together and make them working.

For our compliance application, the proposal is a combination of three core technologies: a knowledge graph for legal data, a rule-based engine for compliance regulations, and a (large) language model (LLM) for chatbots.

• Knowledge Graph for Legal Data

A knowledge graph is a powerful tool for organizing and analysing complex data. For our compliance application, we can use a legal knowledge graph to represent the vast array of legal data, including laws, regulations, and internal policies. The knowledge graph will structure this data in a way that reflects its relationships and dependencies, making it easier to understand and use. This will enable the application to handle complex compliance scenarios and provide accurate and relevant guidance.

• Rule-Based Engine for Compliance Regulations

A rule-based engine is a software system that executes one or more rules to infer new information or direct a course of action. For our compliance application, we can use a rule-based engine to implement the compliance regulations. The engine will translate the regulations into a set of rules, which it will then use to monitor compliance, detect violations, and provide guidance. This will ensure that the application applies the regulations correctly and consistently, enhancing its accuracy and reliability.

• Language Model (LLM) for Chatbots

A language model is a machine learning model that understands and generates human language. For our compliance application, we can use a language model to power a chatbot that interacts with the users. The chatbot will answer queries, provide guidance, and offer training and support in a conversational manner. This will make the application more user-friendly and effective, enabling users to easily access and understand the compliance information they need.

By combining these technologies, we can create an automated AI compliance application that is not only functionally effective but also technically robust and scalable. The knowledge graph will provide a solid foundation for handling legal data, the rule-based engine will ensure accurate application of compliance regulations, and the language model will facilitate user interaction and learning. This will result in a comprehensive and user-friendly solution for automated compliance.

There will be areas for use of other and additional technology for support. In order to read and import legal or other information into our knowledge environment we will use OCR and NLP technology. In order to learn rules and regulations or extract other relevant data we might use ML and other technology.

Conclusions (so far)

In this edition, we have laid the foundational understanding of the scope and technological backbone necessary for developing an AI-driven legal compliance application. We have explored how integrating a legal knowledge graph, a rule-based engine, and an LLM-powered chatbot can significantly enhance the efficacy and efficiency of compliance processes. We have discussed how careful planning and preparation can lay the foundation for a comprehensive and user-friendly solution for automated compliance. This is just the beginning.

As we continue this series, future editions of our newsletter will delve deeper into other critical aspects of the compliance application. We will discuss the implementation challenges, the ethical considerations, data security measures, and the impact of emerging technologies that could further revolutionize the compliance landscape.