How GenAI transforms workflows, due diligence, and investigations

In professional circles, the idea that generative artificial intelligence (GenAI) will ultimately revolutionize the way human beings work is pretty much an accepted fact. Given the inevitability of GenAI’s impact on the working world, the questions all sorts of corporate leaders and professionals are now asking are:

• How can GenAI help our business or profession?
• What will GenAI allow us to do that we couldn’t before?
• What will work look like if we incorporate GenAI capabilities into our workflows and processes?
• Should we invest in GenAI-powered tools now or wait until the technology matures?
• If we do invest in GenAI-powered tools, will the payoff be worth it?

Why GenAI?

Until now, most professional applications of AI have been based on machine-learning models trained on a specific dataset that can identify patterns within that dataset. Once this form of AI recognizes a pattern, it can “learn” how to categorize the data, interpret it, and execute certain commands or functions based on algorithms defined by the user. In the corporate sphere, professionals typically use such algorithms to automate specific repetitive, data-heavy tasks to save time, reduce errors, and lower costs.

So, for example, accountants use machine-learning-based AI to automate such repetitive tasks as data validation and reconciliation for audits. Lawyers use this AI to draft standard contracts and speed up the data-intensive discovery process. Manufacturers use it to automate repetitive supply-chain processes and monitor warehouse inventory levels, among other things.

The GenAI difference

Generative AI differs from machine-learning versions of AI. It is capable of mining much larger universes of data and extracting pattern-based information that might otherwise get overlooked. It then uses that information to extrapolate or generate new ideas and insights — or images and video — that didn’t exist before. Generative AI can also teach itself to diagnose problems, correct errors, and refine its output for greater accuracy.

ChatGPT’s extraordinary ability to answer questions, engage in dialogue with people, and generate original content based on a few basic prompts are the most well-known applications of GenAI. But that’s not why business leaders and professionals are excited about this technology. The primary interest of corporate leaders and professionals — doctors, lawyers, engineers, scientists, bankers, software developers, etc. — lies in the application of generative AI technology. They see opportunities for improved job performance, better outcomes for customers and clients, and sustained competitiveness in a fast-evolving market.

For example:

• GenAI’s ability to synthesize and summarize information from huge datasets is a time-saving godsend for professionals who must digest material buried in long research reports or complex user manuals.
• GenAI’s ability to produce original ideas and concepts is spurring innovation by helping engineers design new products.
• Scientists are using GenAI to help develop new drugs and medical procedures.
• Healthcare companies are using GenAI to create chatbots that can handle routine medical inquiries and schedule appointments.
• Software engineers are using GenAI to automate basic coding functions.
• Companies everywhere are using GenAI for everything from human-resource onboarding and training to advanced business intelligence.

Indeed, professionals in a wide variety of fields are finding increasingly innovative ways to apply generative AI technology, often through industry-specific tools developed by third-party providers that understand how to maximize generative AI’s usefulness in a particular field.

Streamlined workflows and processes

Thomson Reuters has been at the forefront of professional AI development for decades and is now incorporating GenAI into many of our software products. Customers don’t always know it, but many of the new functions and capabilities available to users of our products are enabled by various forms of AI, which operate in the background, out of sight, by design.

However, generative AI represents a qualitative leap in AI’s capabilities and is expected to radically expand and improve upon previous software iterations. This difference is so profound that GenAI has the potential not only to transform how people do their jobs but also how enterprises organize their workflows and processes, if not their entire culture. 

Strategic deployment of this technology can streamline business functions, leading to greater efficiency, time savings, and lowered costs. It also boosts productivity through faster innovation and smarter resource allocation. Ultimately, it helps companies stay competitive by creating a more responsive and agile organization.

Forward-looking management possibilities

For example, manufacturers who utilize free trade zones (FTZs) must track and process an enormous amount of data on inventory levels, shipping schedules, transportation logistics, customs declarations and fees, etc. — all with the goal of optimizing the profit potential of operating within an FTZ. Software is available for such tasks as shipment tracking and inventory management, of course, but these systems are typically limited to their specific functions. Cloud-based tools powered by generative AI offer the possibility of pulling data from the entirety of a manufacturer’s business systems and analyzing it to give FTZ managers a much more forward-looking and holistic view of their operations.

Using GenAI, FTZ managers can:

• Forecast future product demand based on historical data
• Use trade data to identify future supply-chain risks
• Identify and mitigate potentially costly customs errors
• Optimize inventory storage and holding costs
• Create more efficient shipping and delivery schedules
• Anticipate responses to changing regulatory and compliance issues
• Ensure consistently accurate sourcing documentation
• Identify more efficient import/export processes and schedules

In truth, much more can be accomplished using GenAI, but the point here is that it gives organizations a heretofore unavailable tool to help them develop targeted, data-backed strategies for more efficient management. These strategies minimize risk factors, save money, spur innovation, and maintain competitiveness.

Improved operations and efficiency

Financial institutions also use GenAI capabilities to improve their operations and overall efficiency.

For example, when assessing credit risks, financial institutions can use GenAI to set up scoring models and algorithms that draw from larger datasets and provide more accurate, efficient credit evaluations. It can also analyze financial data and market trends to optimize asset allocations and provide customers with investment strategies based on their personal risk profile.

Fraud detection is another area ripe for GenAI, given the technology’s superior ability to identify suspicious financial activity and recognize anomalous transaction patterns. As many bank customers are already learning, generative AI is powering a veritable army of customer-service chatbots ready 24/7 to answer questions and handle routine customer interactions.

The cumulative impact of these advancements has allowed financial institutions using GenAI to streamline their know-your-customer (KYC) processes and improve compliance with anti-money laundering (AML) regulations, all while providing more responsive customer service and minimizing the risk of fraud.

Applying GenAI at Thomson Reuters with CLEAR

Thomson Reuters customers already enjoy some of these capabilities because AI in various forms has been powering our products for many years. Indeed, we have been a pioneering leader in the AI field and are committed to remaining at the forefront of GenAI technological research and development. As we continue to invest in our products and develop our own proprietary applications, customers can expect continued innovation, improvement, and expansion of our solutions for government and business far into the future.

One product currently introducing new GenAI capabilities is CLEAR, our industry-leading investigative software.

Corporations, financial institutions, law enforcement, retailers, manufacturers, and government service providers use CLEAR to conduct customer and vendor due diligence, prevent fraud, and uphold the law. It is an effective investigative tool because it penetrates much deeper into public data sources — like court records, business filings, DMV records, sanctions lists, and social media — than any Google search can. Plus, it’s supported by proprietary databases that strengthen and extend the software’s reach.

CLEAR is a powerful tool that generates an enormous amount of data. Its investigative reports are extensive, so customers don’t always know where to find specific pieces of information or how to interpret all the data the system uncovers. The software’s dashboard, search tools, and alert systems provide a great deal of insight. However, potentially vital information can sometimes be overlooked, not because the software doesn’t detect it but because the user doesn’t always know how or where to find it.

A new GenAI-powered tool for CLEAR

To help customers get the most out of their investigations, CLEAR now includes a GenAI-powered tool called the “Risk Analysis Summary for Business Reports.”

We’ve designed the Risk Analysis Summary (RAS) to reduce the time it takes CLEAR users to investigate and conduct due diligence on businesses, corporations, and potential vendors and suppliers. Presented at the top of the Business Reports section, the RAS provides a concise overview of the critical information obtained during a search, including key business details, social media links, and other relevant information. In addition, the RAS employs generative AI to generate a company profile and risk overview of the business in question.

At the top of every RAS report is a GenAI risk overview — a concise, AI-generated summary outlining the general findings for the report subject. The summary draws on both open-source data and proprietary data to highlight, in plain language, the report subject’s overall potential risks.

For example, the summary might read: “Company X, a manufacturing company specializing in plastics products, has faced significant legal and regulatory challenges. The company pleaded guilty to making false statements in a procurement fraud case, resulting in a ($X) fine in 2018. The company’s current operational status is concerning, as its primary corporate filing shows it was administratively dissolved in 2018. Additionally, the company appears on multiple sanctions lists, including the U.S. System for Award Management exclusions list, where they were deemed ineligible for federal contracts from (X date).”

In general, every RAS report can also contain:

• Company overview — a narrative description of the business’s operations
• Risk overview — a narrative description of potential risks identified in the company’s report and in open-source information
• Key business details — a list of legal names, addresses, business filings, ticker symbols, and information on essential personnel and beneficial owners
• Adverse records/media review — an expandable list of any adverse records, media events, or sanctions mentioning or involving the business in question
• Social media activity — links to assess a company’s social media presence

At a glance, the RAS provides users with a brief overview of all the crucial details about a company and alerts users to any risks or issues that might merit additional investigation. It also provides links to relevant source documents, allowing users to quickly verify information that has been flagged or needs to be double-checked. Furthermore, users can customize RAS reports to focus only on information relevant to their specific industry or purpose.

AI transparency

Thomson Reuters is aware that AI tools are not infallible and that users may have legitimate concerns about the technology’s reliability and accuracy in these early days of the technology's development. 

That’s why every RAS report uses easy-to-identify color codes to highlight AI-generated portions of the report and to distinguish AI-driven content from manually parsed data. Additionally, every report provides source attribution for all summary details, including internal and external sources so that users can verify all statements made within the AI-driven content. Over time, users can come to their own conclusions about the veracity of the RAS’s AI-driven content as they interact with and test our source attribution. 

Saving time and money

The RAS’s main benefits are that it can save users a great deal of time and help them manage risk more precisely when investigating businesses and conducting due diligence. Not only can RAS users verify necessary information, but they also get a handy index for accessing any additional information that may be essential, as well as direct links to the documents or sources containing that information.

At a financial institution that conducts dozens or hundreds of know-your-customer (KYC) searches daily, for example, the cumulative time saved using the RAS tool will allow users to structure their investigative time more effectively and conduct deeper due diligence across more accounts. They can use the time saved to perform other important tasks, thereby increasing productivity, improving individual performance, and lowering overall costs.

New processes and work habits

The RAS-driven boost in search efficiency will likely change how users integrate CLEAR searches into their daily workflow. If users spend less time on repetitive investigations, they will likely discover ways to take advantage of these new efficiencies — and adapt their work habits accordingly.

GenAI: Delivering value

Thomson Reuters knows business leaders and professionals everywhere are eager to understand how generative AI might help them. In our Future of Professionals Report 2024, 77% of respondents said they believe AI will have a high or even transformational impact on their careers. Another 40% said the aspect of GenAI that excites them most is the additional value AI-powered technology might bring to their day-to-day lives.

Value comes in many forms, of course, but the primary value that professionals seem to understand intuitively about GenAI is that it promises to free up some of that most precious of resources — time. What people choose to do with that extra time is up to them, of course. There is at least some comfort in knowing that technologies powered by generative AI may help people exert an additional measure of control over their working lives — a sense of control that seems to be lacking in this age of overwhelming workloads and perpetual uncertainty.

Value can be monetary, too, naturally. Early use of GenAI in corporate settings suggests companies are enjoying many tangible benefits, including the possibility of new revenue streams. In general, this value stems from:

• Cost reductions and containment
• More efficient workflows
• Faster research and development and product-to-market
• New product and service ideas
• Alignment of GenAI with core business functions
• Improved customer service
• Data-backed business intelligence

The Thomson Reuters commitment to AI

In 2023, Thomson Reuters president and CEO Steve Hasker announced our multiyear global strategy for GenAI, including a promise to invest more than $100 million annually in AI research and development.

“AI will revolutionize and transform the future of work for professionals across the globe,” Hasker said at the time. “Professionals have our unwavering commitment and support as they safely navigate the opportunities and challenges provided by the evolving AI landscape.”

Following through on that promise, we have since released several GenAI tools and product enhancements and established strategic partnerships with other leading AI companies to accelerate the development of this ground-breaking technology.

Corporate leaders, too, understand the transformative potential of generative AI. Increased efficiency, improved accuracy, more strategic business insights, lower operational costs, optimized workflows, and less system maintenance — these are all benefits corporate leaders hope generative AI will continue to provide as the technology matures and evolves.

We intend to make sure GenAI delivers on this extraordinary potential and that our customers reap the rewards.