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Bolstering anti-money laundering (AML) compliance with AI

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Bolstering anti-money laundering (AML) compliance with AI

By Stuart Brock

Stuart Brock

Stuart Brock

International efforts regarding anti-money laundering (AML) and counter-terrorist financing have intensified in the last decade; as governments and the private sector work to staunch the cross-border flow of funds used by criminal and terrorist organizations. As a result, bad actors have become more sophisticated in their methods, moving their activities away from the global financial system and into the murky world of trade-based financing.

While other industries have adopted data-driven frameworks and technologies, which are well suited to monitoring and revealing wrongdoing, trade finance remains remarkably document-based. Paper contracts and agreements are generally reviewed manually to ensure compliance with regulators. In cases of concern, contracts are individually examined by specialists – who, like first-line reviewers, are prone to human inconsistency, error, and delay.

Banking and financial services firms are now deploying artificial intelligence (AI) to analyze contract data, as a means to identify cash smuggling and financial system misconduct under AML laws and regulations. These institutions are using this technology to determine if their supply- and sell-side contracts fully align with internal risk processes and regulatory obligations. While applying AI-based reviews for ongoing end-to-end assessment of third-party paper. This entails more than automating the examination of documents or data, but determining if these instruments define the systems, processes, relationships, and the controls necessary to maintain AML transparency.

Legacy processes undermine compliance

Criminals often employ invoicing tactics, such as over- and under-pricing trade goods, so that an importer can resell goods and recover the difference in fair market value on the open market;  issuing multiple invoices to achieve duplicate payments and misrepresenting goods in terms of value or quantity, so that importers can recover the difference in cost.

Criminal entities also conduct transactions across poorly regulated markets, particularly in developing countries, where infrastructure is weak or non-existent, or across free-trade jurisdictions, using shell companies and bank accounts that add legal complexity to trade finance.

In these institutions, the quality of the data represented by contracts erodes the ability to standardize manual document review, and fragmented data repositories inside and outside corporate boundaries make aggregation difficult to achieve. Examiners spend a disproportionate  amount of time and effort finding contracts and extracting the data and legal clauses they contain. This critical, but methodical task, greatly reduces the time available for their investigative efforts as they focus more on the process than the result itself.

Moreover, manual methods for determining contractual risk and scoring of that risk are notorious for producing false positives. Out of an abundance of caution, investigation of low-risk contractual documents is a drain on resources and diverts attention from the much more significant sources of money laundering and trade finance violations. As mandates become more complex and numerous, additional evaluation criteria and divergent thresholds only serve to compound this problem.Inconsistent standards for contract language require a great deal of human interpretation, with screeners often disagreeing on what constitutes risk and violation of AML compliance. Qualitative and quantitative metrics for assessing risk across jurisdictions and processes are often equally inconsistent.

Certainly, strides in operational efficiency and contract governance can improve trade-finance crime-prevention. Firms are making strategic investments into advanced AI-based contract analytics, including machine learning-based risk scoring and process automation. Rather than reacting to market and regulatory demands by invoking legacy approaches, they are using the new technologies to substantially reduce AML risk exposure and avoid hefty penalties related to non-compliance, not to mention to minimize the potential reputational blow of such events.

When deficiencies are found using contract analytics, they almost always result from a systematic effort at automated monitoring because the problems are rarely parcel to the due diligence process of setting up the contract or papering, in the first instance. Examiners invariably discover that the level of monitoring does not align to the risk or the type of relationship.

Automation of contract investigation
Companies too often fall into a false sense of complacency that says when due diligence is completed, the work of compliance is mostly done. Traditionally, wrongdoing is almost always identified only when something goes wrong or when a regulator steps in. Like most industries, banking and financial services firms are concerned with the bottom line and the impact of significant cost centers, such as compliance and risk functions.

In an environment of growing regulations, lean staff, and even leaner budgets, there is no way for banks and financial institutions to achieve, let alone sustain, AML compliance without automation. It is simply not possible to extract contract intelligence amid the byzantine world of trade finance with spreadsheets and manual data entry. Management of incumbent contractual details across often hundreds of operational centers and analysis of the massive number of data points needed to satisfy regulatory requirements is tremendously challenging without some form of technological intervention.

Especially amid the rising costs of non-compliance, as fines are levied by regulators with greater frequency and intensity, AI contract analytics has emerged as a gateway for understanding risk and non compliance. As a matter of contract governance and strategy, banks and financial institutions are applying data analytics to their legal agreements for robust oversight of finance, shipping and insurance interests, cross-jurisdictional legal systems and customs procedures, and even in cases where multiple languages govern a relationship.

Automation of contract investigation for AML adherence can also significantly reduce the caseload assigned to manual reviewers. By escalating fewer contracts for investigation by examiners, contract AI is being employed to reduce level-one alerts, populate forms and databases for reporting, and allow for overall labor optimization so that humans can focus on higher-level review requirements. Artificial intelligence also enhances the prioritization of contracts for upstream resolution with rules-driven document management and escalation.

By embedding contract discovery, extraction, and analysis technologies into organic processes for AML compliance, banks and financial services providers can fundamentally reshape their defenses. Keeping pace with threats from organized crime, terrorist elements, and other corrupt cartels and individuals, who often cloak their malicious activities by flying under the contractual radar, requires dynamic approaches that scale to a clear view of risk across an entire organization. With the right application of AI-derived analysis to data contained in contracts and legal paper, these institutions can confidently address the AML challenge.

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Stuart Brock is a director at Seal Software where he helps lead Seal’s financial services programs. He is a licensed attorney who practiced law at a top national firm for some 10 years before moving in-house at Bank of America. Stuart’s roles at BofA included oversight for governance and management of third-party contracts including maintenance and technology to support BofA’s arsenal of contract templates across more than 60 countries.

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Oil extends losses as Texas prepares to ramp up output

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Oil extends losses as Texas prepares to ramp up output 1

By Ahmad Ghaddar

LONDON (Reuters) – Oil prices fell from recent highs for a second day on Friday as Texas energy firms began to prepare for restarting oil and gas fields shuttered by freezing weather.

Brent crude futures were down $1.16, or 1.8%, to $62.77 per barrel, by 1150 GMT, while U.S. West Texas Intermediate (WTI) crude futures fell $1.42, or 2.4%, to $59.10 a barrel.

Unusually cold weather in Texas and the Plains states curtailed up to 4 million barrels per day (bpd) of crude oil production and 21 billion cubic feet of natural gas, according to analysts.

Texas refiners halted about a fifth of the nation’s oil processing amid power outages and severe cold.

However, firms in the region on Friday were expected to prepare for production restarts as electric power and water services slowly resume, sources said.

“The market was ripe for a correction and signs of the power and overall energy situation starting to normalise in Texas provided the necessary trigger,” said Vandana Hari, energy analyst at Vanda Insights.

Oil fell despite a surprise fall in U.S. crude stockpiles in the week to Feb. 12, before the freeze. Inventories fell by 7.3 million barrels to 461.8 million barrels, their lowest since March, the Energy Information Administration reported on Thursday. [EIA/S]

The United States on Thursday said it was ready to talk to Iran about both nations returning to a 2015 agreement that aimed to prevent Tehran from acquiring nuclear weapons.

While the thawing relations could raise the prospect of reversing sanctions imposed by the previous U.S. administration, analysts did not expect Iranian oil sanctions to be lifted anytime soon.

“This breakthrough increases the probability that we may see Iran returning to the oil market soon, although there is much to be discussed and a new deal will not be a carbon-copy of the 2015 nuclear deal,” StoneX analyst Kevin Solomon said.

(Additional reporting by Roslan Khasawneh in Singapore and Sonali Paul in Melbourne; editing by Jason Neely)

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Analysis: Carmakers wake up to new pecking order as chip crunch intensifies

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Analysis: Carmakers wake up to new pecking order as chip crunch intensifies 2

By Douglas Busvine and Christoph Steitz

BERLIN (Reuters) – The semiconductor crunch that has battered the auto sector leaves carmakers with a stark choice: pay up, stock up or risk getting stuck on the sidelines as chipmakers focus on more lucrative business elsewhere.

Car manufacturers including Volkswagen, Ford and General Motors have cut output as the chip market was swept clean by makers of consumer electronics such as smartphones – the chip industry’s preferred customers because they buy more advanced, higher-margin chips.

The semiconductor shortage – over $800 worth of silicon is packed into a modern electric vehicle – has exposed the disconnect between an auto industry spoilt by decades of just-in-time deliveries and an electronics industry supply chain it can no longer bend to its will.

“The car sector has been used to the fact that the whole supply chain is centred around cars,” said McKinsey partner Ondrej Burkacky. “What has been overlooked is that semiconductor makers actually do have an alternative.”

Automakers are responding to the shortage by lobbying governments to subsidize the construction of more chip-making capacity.

In Germany, Volkswagen has pointed the finger at suppliers, saying it gave them timely warning last April – when much global car production was idled due to the coronavirus pandemic – that it expected demand to recover strongly in the second half of the year.

That complaint by the world’s No.2 volume carmaker cuts little ice with chipmakers, who say the auto industry is both quick to cancel orders in a slump and to demand investment in new production in a recovery.

“Last year we had to furlough staff and bear the cost of carrying idle capacity,” said a source at one European semiconductor maker, who spoke on condition of anonymity.

“If the carmakers are asking us to invest in new capacity, can they please tell us who will pay for that idle capacity in the next downturn?”

LOW-TECH CUSTOMER

The auto industry spends around $40 billion a year on chips – about a tenth of the global market. By comparison, Apple spends more on chips just to make its iPhones, Mirabaud tech analyst Neil Campling reckons.

Moreover, the chips used in cars tend to be basic products such as micro controllers made under contract at older foundries – hardly the leading-edge production technology in which chipmakers would be willing to invest.

“The suppliers are saying: ‘If we continue to produce this stuff there is nowhere else for it to go. Sony isn’t going to use it for a Playstation 5 or Apple for its next iPhone’,” said Asif Anwar at Strategy Analytics.

Chipmakers were surprised by the panicked reaction of the German car industry, which persuaded Economy Minister Peter Altmaier to write a letter in January to his counterpart in Taiwan to ask its semiconductor makers to supply more chips.

No extra supplies were forthcoming, with one German industry source joking that the Americans stood a better chance of getting more chips from Taiwan because they could at least park an aircraft carrier off the coast – referring to the ability of the United States to project power in Asia.

Closer to home, a source at another European chipmaker expressed disbelief at the poor understanding at one carmaker of how it operates.

“We got a call from one auto maker that was desperate for supply. They said: Why don’t you run a night shift to increase production?” this person said.

“What they didn’t understand is that we have been running a night shift since the beginning.”

NO QUICK FIX

While Infineon, the leading supplier of chips to the global auto industry, and Robert Bosch, the top ‘Tier 1’ parts supplier, both plan to commission new chip plants this year, there is little chance of supply shortages easing soon.

Specialist chipmakers like Infineon outsource some production of automotive chips to contract manufacturers led by Taiwan Semiconductor Manufacturing Co Ltd (TSMC), but the Asian foundries are currently prioritising high-end electronics makers as they come up against capacity constraints.

Over the longer term, the relationship between chip makers and the car industry will become closer as electric vehicles are more widely adopted and features such as assisted and autonomous driving develop, requiring more advanced chips.

But, in the short term, there is no quick fix for the lack of chip supply: IHS Markit estimates that the time it takes to deliver a microcontroller has doubled to 26 weeks and shortages will only bottom out in March.

That puts the production of 1 million light vehicles at risk in the first quarter, says IHS Markit. European chip industry executives and analysts agree that supply will not catch up with demand until later in the year.

Chip shortages are having a “snowball effect” as auto makers idle some capacity to prioritize building profitable models, said Anwar at Strategy Analytics, who forecasts a drop in car production in Europe and North America of 5%-10% in 2021.

The head of Franco-Italian chipmaker STMicroelectronics, Jean-Marc Chery, forecasts capacity constraints will affect carmakers until mid-year.

“Up to the end of the second quarter, the industry will have to manage at the lean inventory level,” Chery told a recent Goldman Sachs conference.

(Douglas Busvine from Berlin and Christoph Steitz from Frankfurt; Additional reporting by Mathieu Rosemain and Gilles Gillaume in Paris; Editing by Susan Fenton)

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Aussie and sterling hit multi-year highs on recovery bets

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Aussie and sterling hit multi-year highs on recovery bets 3

By Tommy Wilkes

LONDON (Reuters) – The Australian dollar rose to near a three-year high and the British pound scaled $1.40 for the first time since 2018 on optimism about economic rebounds in the two countries and after the U.S. dollar was knocked by disappointing jobs data.

The U.S. currency had been rising in recent days as a jump in Treasury yields on the back of the so-called reflation trade drew investors. But an unexpected increase in U.S. weekly jobless claims soured the economic outlook and sent the dollar lower overnight.

On Friday it traded down 0.3% against a basket of currencies, with the dollar index at 90.309.

The Aussie rose 0.8% to $0.784, its highest since March 2018. The currency, which is closely linked to commodity prices and the outlook for global growth, has been helped by a recent rally in commodity prices.

The New Zealand dollar also gained, and was not far off a more than two-year high, while the Canadian dollar rose too.

Sterling rose to $1.4009 on Friday, an almost three-year high amid Britain’s aggressive vaccination programme.

Given the size of Britain’s vital services sector, analysts say the faster it can reopen the economy, the better for the currency. Sterling was also helped by better-than-expected purchasing managers index flash survey data for February.

The U.S. dollar has been weighed down by a string of soft labour data, even as other indicators have shown resilience, and as President Joe Biden’s pandemic relief efforts take shape, including a proposed $1.9 trillion spending package.

Despite the recent rise in U.S. yields, many analysts think they won’t climb too much higher, limiting the benefit for the dollar.

“Our view remains that the Fed will hold the line and remain very cautious about tapering asset purchases. We think it will keep communicating that tightening is very far off, which should dampen pro-dollar sentiment,” said UBS Global Wealth Management strategist Gaétan Peroux and analyst Tilmann Kolb.

ING analysts said “the rise in rates will be self-regulating, meaning the dollar need not correct too much higher”.

They see the greenback index trading down to the 90.10 to 91.05 range.

U.S. dollar

Aussie and sterling hit multi-year highs on recovery bets 4

The euro rose 0.4% to $1.2134. The single currency showed little reaction to purchasing manager index data, which showed a slowdown in business activity in February. However, factories had their busiest month in three years, buoying sentiment.

The dollar bought 105.39 yen, down 0.3% and a continued retreat from the five-month high of 106.225 reached Wednesday.

(Editing by Hugh Lawson and Pravin Char)

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