GRBusiness
In Fraud and Corruption investigations, Artificial intelligence and data analytics save time, says IT expert
When a legal team needs to find the facts behind fraud and corruption allegations in a government investigation, technology can drive substantial new efficiencies.
By filtering and evaluating vast amounts of information, artificial intelligence (AI) can effectively sort text messages, audio files, e-mail, and other unstructured data into manageable groups; identify potential relationships between parties accused of fraud or corruption; and recognize patterns of frequency or timing, which may support a client’s defense.
Technology-assisted data analysis can provide the diligence and reliable quality control needed to provide the government with conclusions they can trust.
In this interview, a Partner at Hogan Lovells in Washington, D.C., Peter Spivack, explains how the process of gathering, sorting, and evaluating enormous volumes of data has changed, and why skilled human intelligence is likely to remain a required component of an accurate analysis. Excerpt
Where does the data come from in a government investigation, what are you looking for in that data, and how do you use it in your case?
When we do investigations for a client, we’re trying to determine the facts. There’s usually a very vague allegation that comes in, maybe through an internal whistleblower hotline or a subpoena from the government. We have a list of documents that a government entity is requesting, a complaint that somebody called in to a hotline, an anonymous e-mail that reports some allegation, or a news article.
So there’s a certain amount of information that may show us the ballpark, for example, but we don’t know what row and what seat we’re sitting in. We’re trying to determine if there is an issue, and whether it’s the same issue that’s been identified. If it’s a government investigation, what’s the government looking at? What’s the strength of the evidence? What are the legal or regulatory defenses that we can use to advocate? What’s the client’s exposure? And how do we explain this to the in-house general counsel, chief compliance officer, board, audit committee of the board, and outside auditors, to give them an assessment of what the risk is?
And if we’re going in to see the government, how do we explain that we’ve done an investigation that they can rely on and found the relevant facts, or have taken sufficient steps that, based on the sources of information available to us, we can rule things out? Because they’re not going to simply say, we trust you and if you tell us you’ve looked at five e-mails, that’s all you needed to do. We need to be able to tell them that we’ve looked at the whole picture.
Then there are other constituencies that drive investigations, especially for big public companies. Are they trying to get a line of credit? Are they looking at a possible merger where someone may ask them, as part of due diligence, do you have any issues? If you do, what have you done to look at the issues, what steps have you taken to resolve them, and what confidence do we have in the result?
There’s a variety of things that drive us to try to determine what the facts are, depending on the situation, and sometimes they are present all at once.
After determining the approach to the investigation and the data you need, you then have to review the data sources. Where is that data stored?
The way companies keep data is basically structured and unstructured. Structured data is essentially kept in an accounting or enterprise resource planning (ERP) system, such as SAP or Oracle. The data housed there is a record of all the transactions they’ve undertaken, and we’ll work with a forensic accounting firm to define a set of data analytic tests that we can run.
Those tests can be a variety of different parameters we can flag that can be used to show basic fraud or corruption criteria. For example, are there round-number transactions? Are there sequential invoices to the same vendor? It may seem strange that the vendor is getting Invoices 1, 2, and 3, when it’s a vendor that ostensibly would have many other customers. Is there a mismatch in the location of the work and the actual route of payment? Maybe the work is being done in Colombia, but the payment is going to France. We may need to ask for an explanation.
You run those parameters across structured data and come up with transactions that can be tested by taking what’s been journaled in the accounting system and looking at the underlying documents. If you have a contract, does the contract description match the payment description in the system? If there are deliverables under the contract, are they general and vague, or measurable and specific? Can we determine that the transaction has actually taken place?
You can narrow the scope of those data analytics if you’ve got a specific question. For example, we think that this consultant is allegedly paying bribes to government people, so we’re going to look at that consultant, the contract, the signatories on the contract, and the description of work under the contract. We’re going to see what evidence there is of the work. We’re going to look at the payment terms and say, does this seem like something that is commensurate with the value being delivered? Is it a fair market value? We’re trying to hone in and test the bona fides, so to speak, of that contractor business arrangement.
Take an example: one of our clients paid a lot of money to hire a well-known lawyer from another firm. But if you looked at that lawyer, you’d say, he doesn’t really seem to have expertise in that area. So how do you explain that? Maybe there’s a legitimate explanation. But it’s something that comes up and so we say, we want to look at that further. It doesn’t necessarily give you the answer, but it focuses things for you to look at.
What is unstructured data, and how do you use them?
That’s basically the way that people use communications systems. It’s text messages, e-mails, messaging apps like Viber and WhatsApp, and other types of point-to-point encrypted communications. There’s been an explosion of unstructured data — so much more than there used to be.
My first investigation at Hogan Lovells was for a company that was under investigation for promoting its product off label. They had human growth hormone that had a very specific use, and the government was concerned that they were promoting it widely for other unapproved uses. I was literally looking at hard-copy documents and putting them in Redwelds, depending on which paragraph they were responsive to. That was in 1998. Twenty years later, we’d never do something like that, because we’ve gone from 100 boxes of documents to 200 terabytes of data, and one terabyte is enough to fill the U.S. Library of Congress. So there’s got to be some way to manage all that data and filter it.
How do you start narrowing down data?
The first step is collection: you’ve got to go out and actually get it. That means, looking at the e-mail system. If we think of unstructured data as a series of concentric circles, it also means going out one ring and getting devices that people use, like laptops, and imaging their hard drives. And going out another ring if you can, depending on data rules, and collecting peripheral devices — smart phones, external drives, USB sticks — that store data.
So now you have this immense amount of data, more than any team of lawyers could review if they reviewed every single document for the rest of their lives, their children’s lives, and their children’s children’s lives. It’s clearly an unmanageable amount. The only way to address that is to try to process it and get it all in a form that can be managed and filtered. You try to exclude things that may be very data heavy but are of little value: program files, photographs, things that are really large that suck up data storage space. Then you have a set of data that you try to filter.
What techniques do you use in filtering?
The most basic technique is search terms. You come up with a list of words related to the investigation and apply them across the data to see if there are hits for documents that contain those words. Then you’re reviewing them at first and second levels to see if they’re relevant to the investigation. That sounds good, except you may only have narrowed your ballpark to the club-level seats; you’re getting a tighter ring, but it’s still an enormous amount of data.
There are other techniques that can be used as well, such as an algorithm. It’s called technology-assisted review. You’re taking a set of documents and reviewing that set with a subject matter expert on the investigation. They’re going through a thousand documents and saying, this one is relevant, this one is not. You’re essentially training an algorithm and honing it on the computer so that it can then give you a probability-based set of outcomes for the potential relevance of documents. The probability stratifications can be in 10 percent levels, so you have buckets, from a very unlikely probability bucket to a highly likely probability. You might be able to review the first two buckets, so you screen out a portion of your documents that way.
There is nothing available yet that is really AI, but there are ways of doing concept searching with certain applications. One that we use is called Brainspace, and it’s basically a sophisticated form of the algorithm that groups concepts. You can run a set of documents through Brainspace and decide what concepts to look for. If you want to look for “office leases,” it will group documents around that. You get a set of documents that you can then review for the concept of “office leases,” whereas if it’s payments to a particular third party, you can group them around that concept as well. That gives you more ability to target and focus.
A lot of times we’ll run different techniques as a way to cross reference. That helps get through larger amounts of data at a higher and more efficient rate. But at the end of the day, it still depends on human evaluation and intelligence to look at a document and say, this is important, as it’s related to things that we’re talking about, or there’s a particular issue here.
While we’re doing that, you have to remember it’s a dynamic situation, so there may be something that comes out of the transaction and data analytics that then says, wait a minute, we really want to look at this company, so let’s run that as a new term through whichever technique we’re using. Or we may put these documents together for interviews. We have a set of documents, we go to talk to a witness and say, what happened? And they tell us but then they raise another issue. That gets fed back into the review of documents and transactions to see if there is anything here that we have to be concerned about or if a new issue has come up.
Or there might be another whistleblower e-mail that comes in, competitor complaint, or newspaper article. So a lot of times, it’s a dynamic process. You don’t have just a static set of issues that you’re looking at. One of the fun things about it is that there’s this constant evolution.
Who is a typical client in this scenario, and what’s the primary benefit of this approach?
This is a way of making investigations more efficient, and efficiency means cost effectiveness. Clients are getting more and more comfortable with data and techniques of analyzing data, to the point where some clients in their compliance programs not only have lawyers and accountants, but also data scientists. A big multinational client, with tens or hundreds of thousands of employees, has people on staff who can design the most current state-of-the-art search engines, train algorithms, and use them as a way to leverage resources.
It’s the outer edge of clients who have that capability, and they have to be big enough and operate in enough countries that they’ll use it. If they’re not, then we work with forensic technologists, both in-house and at forensic consulting companies. They’re very familiar with different search techniques and technologies and the way to leverage them to process and filter larger and larger amounts of data.
There have been significant advances in technology in the last few years, and more and more interest in it. A lot of it is because of the ever-increasing amounts of data, and as a result, ever-increasing cost. There have to be ways to get costs to a controllable, reasonable level. So we have to know how to do that and work with people who understand and are comfortable with the concepts. We have to be able to articulate both to the client — if they’re unfamiliar with it — and to the government — to defend it — what we’re doing, how we’re doing it, and why it’s reliable. The government uses these techniques as well, so most of them are very familiar with it. They just want to make sure there’s a sufficient level for liability.
About Peter S. Spivack
Peter Spivack is one of the most experienced members of the Investigations, White Collar, and Fraud practice area, and served as a global co-leader of the practice for six years. His experience in the criminal arena includes antitrust, environmental, Foreign Corrupt Practices Act (FCPA), government contract, and healthcare matters. Peter has three decades of experience working with multijurisdictional investigations, including matters involving allegations of bribery and corruption under the FCPA, the UK Bribery Act, and other anti-bribery laws.
Energy
Boost for Nigeria’s Oil Production, As NNPC’s Utapate Crude Grade Hits Global Oil Market
…OML 13 Asset Eyes 80,000 bpd by End of 2025
In a major boost for Nigeria’s crude oil production, revenue generation and economic growth efforts, the NNPC Ltd has officially unveiled its latest crude oil grade, the Utapate crude oil blend, before the international crude oil market.
It would be recalled that in July, 2024, NNPC Ltd and its partner, the Sterling Oil Exploration & Energy Production Company (SEEPCO) Ltd introduced the Utapate crude oil blend, following the lifting of first cargo of 950,000 barrels which headed for Spain.
During a ceremony held at the Argus European Crude Conference taking place in London, United Kingdom, on Wednesday, the Managing Director, NNPC E & P Limited (NEPL), Mr. Nicholas Foucart described the introduction of the Utapate crude oil blend into the market as a significant milestone for Nigeria’s crude oil export to the global energy market.
“Since we started producing the Utapate Field in May 2024, we have rapidly ramped up production to 40,000 barrels per day (bpd) with minimum downtime. So far, we have exported five cargoes, largely to Spain and the East Coast of the United States; while two more additional cargoes have been secured for November and December 2024, representing a significant boost to Nigeria’s crude oil export to the global market,” Foucart told a packed audience of European crude oil marketers.
He added that since its introduction into the global market, the Utapate crude oil blend has enjoyed a positive response from the international crude oil market, due to its highly attractive qualities.
Foucart said the Oil Mining Lease (OML) 13, fully operated by NEPL and Natural Oilfield Services Ltd (NOSL), a subsidiary of SEEPCO Ltd, boasts a huge reserves of 330million barrels of crude oil reserves, 45 million barrels of condensate and 3.5 tcf of gas.
“We have a number of ongoing projects to increase our production from the current 40,000bopd to 50,000bopd by January 2025 and 60,000bopd to 65,000bopd by June 2025. Essentially, we are targeting opportunities to increase production to 80,000bopd by the end of 2025,” Foucart added.
He said the Utapate crude oil terminal is sustainable, affordable and fully compliant with the rigorous environmental regulations and sustainability principles especially those aimed at reducing carbon emissions and other ecological effects.
Also speaking, the Managing Director of NNPC Trading Ltd (NTL), Mr. Lawal Sade said the pricing structure of the Utapate crude oil blend is similar to that of Amenam crude as it is a light sweet crude which is highly sought after by refiners across the world due to its low sulphur content, efficient yield of high-value products, API gravity and other similarities.
He said in bringing the new crude oil blend to the global market, NNPC Ltd wanted to optimise value for both its producers and counterparties across the globe.
He added to ensure predictability and sustainability of supply, the NNPC Trading intends to run a term contract on the Utapate crude oil blend cargoes, principally targeting off-takers from the European and the US East Coast refineries.
Produced from the Utapate field in OML 13 in Akwa Ibom State in Nigeria, the Utapate crude oil blend is similar to the Nembe crude oil grade. It has a low sulphur content of 0.0655% and low carbon footprint due to flare gas elimination, fitting perfectly into the required specification of major buyers in Europe.
The NNPC E&P Ltd and NOSL partnership is also committed to operating in a manner that is safe, environmentally responsible, and beneficial to the local communities.
The Utapate field development plan, executed between 2013-2019 and approved in October, included converting wells and facilities from swamp/marine to land-based operations.
The plan involved a multi-rig drilling campaign for 40 wells and the development of significant infrastructure such as production facilities, storage tank, a subsea pipeline and an offshore loading platform to facilitate crude oil evacuation and loading.
The entry of the Utapate crude oil blend into the market is coming barely a year after the NNPC Ltd announced the launch of Nembe crude oil, produced by the NNPC/Aiteo operated Oil Mining Lease (OML) 29 Joint Venture (JV).
This remarkable achievement signals the commitment of the NNPC Ltd to increasing Nigeria’s crude oil production and growing its reserves through the development of new assets.
Energy
NNPC Ltd Set to Supply 100mmscf/d Gas to Dangote Refinery
…10-year Deal to Boost Local Production, Revamp Industrial Growth, reports Ikenna Oluka
The NNPC Gas Marketing Limited (NGML), a subsidiary of the Nigerian National Petroleum Company (NNPC) Limited, has successfully executed a Gas Sale and Purchase Agreement (GSPA) with Dangote Petroleum Refinery and Petrochemicals FZE.
The agreement, signed by the Managing Director, NGML, Barr. Justin Ezeala and the President/CEO of the Dangote Group, Aliko Dangote on Tuesday at the Corporate Head Office of Dangote in Falomo, Lagos State, outlines the supply of natural gas for power generation and feedstock at the Dangote Refinery, in Ibeju-Lekki, Lagos State.
This major milestone is in line with President Bola Ahmed Tinubu’s policy of utilizing Nigeria’s abundant gas resources towards revamping the nation’s industrial growth and kickstarting its economic prosperity.
This development, which sees a huge investment of this nature penned with zero capital expenditure (CAPEX) outlay, has been described by many as unprecedented in the history of NGML or any gas Local Distribution Company (LDC) in the country.
Under the terms of the agreement, NGML will supply 100 million standard cubic feet per day (MMSCF/D), 50MMSCF/D being firm supply and the rest 50MMSCF/D interruptible natural gas supply to the refinery for an initial period of 10 years, with options for renewal and growth.
This collaboration is a significant step toward ensuring the operational success of the Dangote Refinery and enhancing Nigeria’s domestic gas utilization.
NNPC Ltd, through NGML, its gas marketing subsidiary, continues to lead efforts in promoting the use of domestic gas to support industries and businesses nationwide.
The agreement represents a milestone for both NNPC Ltd and Dangote Refinery, aligning with their shared commitment to boosting local production and providing vital products for the benefit of all Nigerians.
It is also a further proof of NGML’s unwavering commitment to business excellence and fulfilling NNPC Ltd’s core mandate of ensuring Nigeria’s energy security through the execution of strategic gas projects across the country.
Transport
WIMAfrica and SIFAX Group Partner to Champion Gender Equality in Maritime Industry
Women in Maritime Africa (WIMAfrica), in a significant step forward for female representation in the Maritime field, held a strategic meeting with SIFAX Group at the SIFAX headquarters on November 12th, 2023.
The two organizations aim to foster mentorship, sponsorship, and skills development programs that will empower women to pursue and excel in maritime careers, where female representation remains below 1%. Key figures from WIMAfrica, including Continental Vice President Mrs. Carolyn Ufere and Nigeria’s President Mrs. Rollens Macfoy, emphasized the need for corporate partnerships to expand access to training and professional networks for women. SIFAX’s Coordinating Director, Mrs. Wunmi Eniola-Jegede, expressed the Group’s commitment to gender inclusivity and highlighted the presence of women in leadership roles across its various sectors.
In closing, WIMAfrica extended an invitation for SIFAX Group to support its upcoming conference in Lagos, themed “New Economy and Moving Forward for the Next Generation,” which seeks to inspire young women to explore maritime career paths like engineering and marine security. The collaboration between WIMAfrica and SIFAX Group marks a crucial move toward an inclusive future in Africa’s maritime industry.
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