Officials from the Federal Trade Commission (FTC) said that 7-Eleven’s parent company moved ahead in its merger arrangement with Marathon Petroleum Corporation even as the commission continues to probe the deal, according to a Friday (May 14) press release.
Federal Trade Commission Acting Chair Rebecca Kelly Slaughter and Commissioner Rohit Chopra said that Seven & i Holdings announced that it had wrapped up a $21 billion deal with Marathon Petroleum Corporation, buying approximately 3,900 Speedway retail fuel and convenience store businesses from Marathon.
“We have reason to believe that this transaction is illegal under Section 7 of the Clayton Act and Section 5 of the Federal Trade Commission Act, raising significant competitive concerns in hundreds of local retail gasoline and diesel fuel markets across the country. In many local markets, the transaction is either a merger-to-monopoly or reduces the number of competitors from three to two,” Slaughter and Chopra said in the press release.
The officials noted that the commission has the ability to “challenge these harmful mergers” and does so with regularity with the support of a majority of commissioners.
Slaughter and Chopra said in the press release that “the parties have closed their transaction at their own risk.”
The officials noted in the press release that the FTC had expended sizable resources looking into the deal but “has not yet come to an agreement with the parties and a majority of the Commission that would fully resolve the competitive concerns.”
“Seven and Marathon’s decision to close under these circumstances is highly unusual, and we are extremely troubled by it,” Slaughter and Chopra said in the press release.
In the Seven & i Holdings Co., Ltd. press release, Seven said that it “announces that the acquisition of the shares and other interests of the companies operating the convenience store and fuel retail businesses of U.S. Company Marathon Petroleum Corporation (‘MPC’) mainly under the Speedway brand (excluding certain fuel retail operations with direct dealers and certain other businesses) by the Company’s consolidated subsidiary 7-Eleven, Inc.”
Agentic artificial intelligence (AI) promises to improve operational efficiencies and the customer experience offered by enterprises.
The advanced technology is finding applications in loan underwriting and fraud detection, and now it’s moving across borders.
TerraPay Co-Founder and Chief Operating Officer Ram Sundaram told PYMNTS as part of the “What’s Next in Payments” series focused on exploring AI’s use in banking and by FinTechs that automated decision making and streamlined processes will continue to transform global money movement, especially as faster payments gain ground in cross-border transactions. That’s the inexorable trend, but as Sundaram put it, there’s still room, and a necessity, to have some human interaction in the mix.
In terms of global fund flows, TerraPay’s single connection ties more than 3.7 billion mobile wallets together across 200 sending and 144 receiving countries, touching 7.5 billion bank accounts. As one might imagine, coordinating and enabling the transactions is complex.
“Obviously, in the best-case scenario, everything goes smoothly, but when things are not going smoothly, that’s when the customer queries come in,” Sundaram said.
It’s no easy task to find out straight away where a transaction is, as analysts and representatives at the company have to look at logs and query partner systems.
“A lot of that work is done manually,” said Sundaram, who added that the agents “know the corridors and the markets that they are working in, but it still takes some time.”
TerraPay is using AI models with machine learning to bolster customer support and automate tasks as financial institutions (TerraPay’s client base) send payments in real time, and those payments are processed into local markets’ beneficiary banks.
“We still don’t trust [AI models] to let them respond to the customer straight away, but we can do the analysis, and then that gets reviewed by an agent who decides if [information] is accurate or not and then sends it off,” Sundaram said.
The same principles are guiding AI models and company practices to improve technical and security operations, analyzing and categorizing anomalous transactions and automating integrations with partner firms.
“Compliance is an issue where there is a lot of review needed of the alerts, and we are using [AI models] to speed up those processes,” Sundaram said.
Asked by PYMNTS about how agentic AI can be harnessed, he said: “In financial services, you can’t take chances on technology like this, which has the freedom to go wrong. You have to be careful about making sure that it’s 100% reliable before we can let things run entirely by automation.”
Agentic AI also remains pricey. For example, OpenAI is charging $20,000 a month for its specialized agents. However, Sundaram said the industry will become commoditized quickly, which will lower prices, and some open-source offerings are capable.
“There’s a fire hose of news about breakthroughs and new ideas and new ways of doing things that are coming out on a daily basis,” he said.
Data underpins it all, and Sundaram told PYMNTS that no matter what the application, the information fed into the models must be clean. Most organizations have a range of data sitting in different intra-company silos, and those silos need to come down.
In addition, the data must be structured so that it is accessible and can be synthesized by the models. Many firms may have more than 1,000 software-as-a-service (SaaS) resources to which they are subscribed but are not accurately tracked or monitored.
“Every database is separated, each one sitting somewhere else,” he said.
The days of stitching together those separate SaaS offerings to run an enterprise are ending, he said, and we’re headed to a future when data is collected in one place.
AI models and agentic AI “are extensions of what we’ve always valued at TerraPay, which means building the most efficient infrastructure possible in order to make sure that transactions are processed safely, quickly and affordably,” Sundaram told PYMNTS. “We see AI and [AI models] as powerful tools that help us scale all this very quickly while making sure we build more and more efficiency into the system.”
