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Modern Due Diligence: Manual vs AI-Powered Solutions

Dec 10, 2024

AI is changing how businesses handle due diligence by speeding up processes, reducing errors, and analyzing massive datasets. While manual methods rely heavily on human expertise, AI tools like TRACT, LexisNexis, and Diligent automate tasks like compliance checks, risk assessments, and document reviews. Here’s a quick summary:

Key Differences:

Time: Manual checks take days or weeks; AI processes data in minutes.
Accuracy: Human error rates are higher; AI achieves up to 95% accuracy.
Cost: Manual methods require ongoing labor; AI reduces costs over time.
Scalability: AI handles large volumes effortlessly; manual methods need more staff.

Quick Comparison Table:

| Aspect | Manual Due Diligence | <a href="https://www.usetract.com/blog/revolutionizing-due-diligence-how-ai-is-changing-the-game" data-framer-link="Link:{"url":"https://www.usetract.com/blog/revolutionizing-due-diligence-how-ai-is-changing-the-game","type":"url"}">AI-Powered Due Diligence</a> |
| --- | --- | --- |
| <strong>Processing Time</strong> | Days to weeks | Minutes to hours |
| <strong>Accuracy</strong> | 60-70% | Up to 95% |
| <strong>Cost</strong> | High labor costs | Lower over time |
| <strong>Scalability</strong> | Limited by staff | Unlimited

AI tools work best for repetitive tasks and large datasets, but human oversight is still essential for complex decisions and ethical considerations. Businesses should aim to balance both approaches for the best results.

How Manual and AI-Based Due Diligence Differ

Human-Led vs. Automated Processes

Manual due diligence depends on human expertise for tasks like reviewing documents and assessing risks. In contrast, AI-powered systems use algorithms to quickly analyze large volumes of data in a structured way.

For instance, Centerline Business Services reported a 35% boost in productivity after adopting AI-driven due diligence tools [*].

Time and Efficiency

The time savings between manual and AI-based methods are striking. Human analysts need to carefully review each document and data point, while AI can handle multiple sources simultaneously.

| Task Type | Manual Approach | AI-Powered Approach |
| --- | --- | --- |
| Data Analysis and Risk Assessment | Takes hours to days for thorough evaluation | Processes data in minutes to hours |
| Compliance Checks | Verifies each requirement individually | Screens multiple databases automatically |
| Report Generation | Requires manual assembly and formatting | Creates reports instantly

AI doesn’t just save time - it also delivers consistent results, reducing risks tied to human error.

Error Rates and Consistency

Human-led processes often struggle with consistency and accuracy due to factors like fatigue or varying skill levels. AI solutions, on the other hand, offer standardized assessments, automated pattern detection, and uniform reporting. By leveraging technologies such as text recognition and advanced language processing, AI improves document analysis accuracy [*][*].

Although AI minimizes errors and ensures consistent performance, combining it with human oversight achieves the best results. We'll delve deeper into this balance in the next section.

Understanding these differences helps businesses decide how to integrate manual expertise with AI-driven tools for their specific needs.

Harnessing AI to Detect Controversies and Streamline Due Diligence

Why Use AI for Due Diligence?

Traditional due diligence methods rely heavily on human expertise, but AI brings a whole new level of efficiency by processing and organizing vast amounts of data quickly. Here's how AI stands out:

Faster Data Analysis

AI tools can analyze thousands of sources in just minutes, delivering insights far quicker than manual efforts. For example, Diligent's AI-powered platform gathers risk data from global sanctions lists, PEPs databases, and adverse media sources. This allows chief compliance officers to make well-informed decisions much faster [*]. The platform works in real-time, giving instant access to key insights.

Spotting Patterns and Risks

AI excels at uncovering patterns and risks that might go unnoticed by human reviewers. It uses advanced algorithms to detect correlations and anomalies across large data sets, offering a deeper level of risk assessment.

Take TRACT, for example. It reviews billions of records from legal, social, and professional sources, providing actionable insights such as:

| Data Type | Analysis and Insights |
| --- | --- |
| Legal Records | Examines court filings and criminal histories for risk |
| Social Data | Analyzes reputation across 100+ social platforms |
| Professional Info | Verifies backgrounds through employment and education

Improved Reporting and Organization

AI tools not only improve the accuracy of reports but also keep data secure [*]. A great example is Tofler's Company360, which provides consolidated reports for tasks like competition benchmarking and vendor onboarding [*]. It organizes data efficiently, making it easier for decision-makers to:

Quickly find relevant information
Monitor updates in real-time
Keep detailed audit trails
Create standardized compliance reports

"Now with AI-powered due diligence reports, customers benefit from an even more efficient, scalable, and risk-based approach to managing third-party risk." - Amanda Carty, GM, Compliance at Diligent [*]

These features highlight why businesses are increasingly adopting AI-driven platforms like TRACT and Diligent for their due diligence needs. We'll dive deeper into these tools in the next section.

Examples of AI Tools and Their Uses

AI tools are reshaping how industries handle due diligence. Below are some standout platforms and their practical applications.

Introducing TRACT

TRACT processes over 100 billion records from 9,500 sources, making due diligence faster and more efficient. Its features highlight AI's role in simplifying compliance, evaluating risks, and verifying credentials:

| Feature | Business Impact |
| --- | --- |
| Legal & Risk Analysis | Flags compliance risks by reviewing legal and financial records in real-time |
| Social Intelligence | Monitors social media for potential reputation risks |
| Professional Verification | Confirms credential accuracy and conducts background checks

Common Business Scenarios

AI platforms are proving their value in industries like finance and compliance:

LexisNexis: Known for monitoring politically exposed persons (PEPs) and sanctions screening, it's a go-to for financial institutions conducting detailed background checks [*].
SignalX: Speeds up vendor due diligence with machine learning that processes millions of documents. This helps companies avoid compliance failures like those experienced by Uber and JP Morgan Chase [*].
Refinitiv: Offers in-depth risk analysis for mergers and acquisitions, enabling businesses to make smarter decisions before finalizing deals.
Signzy: Automates KYC processes in banking, identifying fraud patterns that manual methods often miss [*].

These tools showcase how AI is taking over traditional due diligence tasks. But how do they stack up against manual approaches? Let's dive into a comparison.

Manual vs. AI: A Side-by-Side Comparison

AI-driven due diligence is changing the game in risk assessment and compliance. It offers faster results, greater accuracy, and the ability to handle massive amounts of data - things traditional manual methods struggle to match. With businesses dealing with more complex data than ever, AI tools are reshaping how decisions are made, especially in high-stakes scenarios like mergers and acquisitions.

Comparison Table

| Aspect | Manual Due Diligence | AI-Powered Due Diligence | Real-World Impact |
| --- | --- | --- | --- |
| Processing Speed | 2-3 weeks for thorough checks | Minutes to hours for the same scope | Centerline Business Services cut processing times by 35% using V7 Go <a href="https://www.v7labs.com/blog/ai-due-diligence" target="_blank" rel="nofollow noopener noreferrer" data-framer-link="Link:{"url":"https://www.v7labs.com/blog/ai-due-diligence","type":"url"}" data-framer-open-in-new-tab="">[*]</a> |
| Accuracy Rate | 60-70% with human review | Up to 95% with AI algorithms <a href="https://signalx.ai/blog/10-tools-to-automate-your-due-diligence/" target="_blank" rel="nofollow noopener noreferrer" data-framer-link="Link:{"url":"https://signalx.ai/blog/10-tools-to-automate-your-due-diligence/","type":"url"}" data-framer-open-in-new-tab="">[*]</a> | Exposed fraudulent vendor activities, reducing financial and legal risks |
| Data Coverage | Limited by human capacity | Analyzes massive datasets from global sources | $TRACT supports real-time analysis across multiple areas |
| Cost Structure | High ongoing labor costs | Higher upfront cost, but lower over time | Diligent users report 30-40% lower operational costs <a href="https://www.diligent.com/company/newsroom/diligent-launches-ai-powered-due-diligence-reports" target="_blank" rel="nofollow noopener noreferrer" data-framer-link="Link:{"url":"https://www.diligent.com/company/newsroom/diligent-launches-ai-powered-due-diligence-reports","type":"url"}" data-framer-open-in-new-tab="">[*]</a> |
| Risk Detection | Relies on manual expertise | Flags fraud, compliance gaps, and reputational risks instantly | Enables continuous monitoring for proactive risk management |
| Scalability | Requires more staff for larger workloads | Easily scales to handle any data volume | Manages complex M&A projects without additional resources

Technologies like OCR and advanced language models allow for rapid data extraction and analysis - tasks that are nearly impossible to manage manually. These tools have become essential for tackling the complexities of M&A and compliance checks [*][*].

Knowing these distinctions helps businesses decide which approach fits their needs best. Whether relying on manual expertise or leveraging AI's efficiency, the decision often comes down to the specific requirements and complexity of the task.

Final Thoughts and Advice

AI tools are transforming due diligence by offering faster data processing combined with human expertise. If you're considering these tools, start by identifying bottlenecks in your current processes to see where automation could make the biggest difference.

Solutions like TRACT and Diligent show how AI can simplify workflows while still requiring human judgment for critical areas.

AI works best for tasks like:

Handling large datasets
Routine compliance reviews
Monitoring risks in real-time
Automating repetitive processes

Human oversight is essential for:

Ethical considerations
Complex business relationships
High-level strategic decisions
Interpreting AI-generated insights in context

Make sure your team is trained on these tools, regularly check the outputs, and keep algorithms updated to ensure accuracy. As businesses evolve, blending AI capabilities with human expertise will be key to managing risks and capturing new opportunities.