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Retailers Rely on Modern POS to Beat Uncertainty | PYMNTS.com

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The traditional brick-and-mortar retail store is undergoing a transformation, evolving from a transaction point into a sophisticated command center designed to enhance visibility, deepen engagement and improve operational efficiency.

At the forefront of this shift is the concept of unified commerce.

Nikki Baird, vice president of Strategy and Product at Aptos, an enterprise solution provider exclusively focused on the retail industry, told PYMNTS as part of the “Summer School” series that macro-level pressure is spurring retailers to re-examine the pain points of their operations.

“Tariffs are top of mind,” she told PYMNTS, because retailers “can’t operate with such a level of uncertainty — and they’re doing everything they can to really establish certainty around cost.”

Merchants have found themselves scrambling to pull in product ahead of potential new tariffs. Consumers have already pulled forward spending in prior months. There’s a mismatch in terms of supply and demand.

Commerce transcends the mere act of selling to consumers; it is fundamentally about “connecting customers to products,” she said.

Baird emphasized the critical duality of this connection: “A lot of companies that talk about unified commerce are really only talking about the commerce piece of it, like selling to consumers. And you can be the greatest company in the world with the most rabid fans, but if you can’t get product to them, you are not going to be successful.”

True unified commerce necessitates bringing together all the disparate operational pieces required to facilitate this connection, extending beyond the isolated silos of eCommerce, order management or traditional point of sale.

The absence of connectivity across channels often results in significant friction points within the physical store, directly impacting the customer experience and transaction integrity, Baird said.

She highlighted a common scenario prevalent in many retail environments: “Some retailers today are still using an iPad to look up a customer … They go to a completely different iPad to place an order for inventory that’s not in the store that they want secured for that customer.”

This cumbersome, multi-device approach is then often followed by the need to ring up a separate cash-and-carry transaction that the consumer brought to the till initially.

Such disconnected processes are not merely inefficient; they jeopardize sales. As Baird told PYMNTS, “Anytime you leave the consumer with time to think about ‘Do I really want this purchase? Am I really willing to stand here and wait for this store associate to go through all of this stuff?’ You’re putting that transaction in jeopardy.”

A modern POS system can serve as the “operating system of the store,” she said, enabling associates to seamlessly facilitate connection, thereby safeguarding transactions.

Aptos One: A Unified Platform for Seamless Retail Operations

To address these prevalent pain points and enable genuine unified commerce, Aptos developed Aptos One.

“We designed Aptos One as a mobile-first, enterprise-grade POS application that is built on a cloud-native and microservices-based unified commerce platform. Our intent was really universal services,” she said. That means workflows and microservices used for in-store order placement for out-of-stock inventory are precisely the same ones utilized by a customer service representative placing an order from a call center through an order management system.

This approach directly tackles the inefficiencies tied to brick-and-mortar operations.

“A lot of the complexity that retailers face today is from that duplication of capabilities across different systems that were never designed to support unified commerce and pulling those into the platform so that they can be reused across touchpoints,” Baird said.

Despite prolonged discussions surrounding mobile strategies in retail, their successful deployment within stores remains a persistent challenge for many, Baird contended.

Beyond technical reliability, there is also cultural and operational resistance. Many retailers shy away from a “cash register-less” model, believing such an approach is exclusive to tech giants like Apple. But as consumers become increasingly mobile in their daily lives, their expectations for in-store interactions have evolved. “The consumer expects their store associates to be mobile just as much as they are themselves,” Baird said, reinforcing the notion that a mobile-first strategy is no longer optional but a fundamental expectation.

Future Trajectories: AI Integration and Enhanced in-Store Service

Noting the pervasive impact of artificial intelligence (AI) on retail, Baird said that a substantial portion of Aptos’ innovation efforts is dedicated to embedding data and sales chatbots directly into its solutions, providing query capabilities and feedback to store associates, managers and higher organizational levels. This immediate, data-driven feedback, facilitated by AI, has the potential to dramatically impact business performance. Beyond performance metrics, Aptos is also enhancing the in-store experience by creating an eCommerce-like feel for sales associates when assisting customers. This includes making inventory searching, product lookups and customer history retrieval more intuitive and seamless.

“If you have brick-and-mortar, you have to get that right. That’s what the modern point of sale helps you do,” Baird told PYMNTS.

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Experian Unveils New AI Tool for Managing Credit and Risk Models | PYMNTS.com

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Experian Assistant for Model Risk Management is designed to help financial institutions better manage the complex credit and risk models they use to decide who gets a loan or how much credit someone should receive. The tool validates models faster and improves their auditability and transparency, according to a Thursday (July 31) press release.

The tool helps speed up the review process by using automation to create documents, check for errors and monitor model performance, helping organizations reduce mistakes and avoid regulatory fines. It can cut internal approval times by up to 70% by streamlining model documentation, the release said.

It is the latest tool to be integrated into Experian’s Ascend platform, which unifies data, analytics and decision tools in one place. Ascend combines Experian’s data with clients’ data to deliver AI-powered insights across the credit lifecycle to do things like fraud detection.

Last month, Experian added Mastercard’s identity verification and fraud prevention technology to the Ascend platform to bolster identity verification services for more than 1,800 Experian customers using Ascend to help them prevent fraud and cybercrime.

The tool is also Experian’s latest AI initiative after it launched its AI assistant in October. The assistant provides a deeper understanding of credit and fraud data at an accelerated pace while optimizing analytical models. It can reduce months of work into days, and in some cases, hours.

Experian said in the Thursday press release that the model risk management tool may help reduce regulatory risks since it will help companies comply with regulations in the United States and the United Kingdom, a process that normally requires a lot of internal paperwork, testing and reviews.

As financial institutions embrace generative AI, the risk management of their credit and risk models must meet regulatory guidelines such as SR 11-7 in the U.S. and SS1/23 in the U.K., the release said. Both aim to ensure models are accurate, well-documented and used responsibly.

SR 11-7 is guidance from the Federal Reserve that outlines expectations for how banks should manage the risks of using models in decision making, including model development, validation and oversight.

Similarly, SS1/23 is the U.K. Prudential Regulation Authority’s supervisory statement that sets out expectations for how U.K. banks and insurers should govern and manage model risk, especially in light of increasing use of AI and machine learning.

Experian’s model risk management tool offers customizable, pre-defined templates, centralized model repositories and transparent internal workflow approvals to help financial institutions meet regulatory requirements, per the release.

“Manual documentation, siloed validations and limited performance model monitoring can increase risk and slow down model deployment,” Vijay Mehta, executive vice president of global solutions and analytics at Experian, said in the release. With this new tool, companies can “create, review and validate documentation quickly and at scale,” giving them a strategic advantage.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

Read more:

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Experian Targets ‘Credit Invisible’ Borrowers With Cashflow Score

CFPB Sues Experian, Alleging Improper Investigations of Consumer Complaints

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Anthropologie Elevates Maeve in Rare Retail Brand Launch | PYMNTS.com

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Anthropologie is spinning off its Maeve product line as a standalone brand, a rare move in a retail sector where brand extensions have become less common.

The decision reflects shifting strategies among specialty retailers as they work to adapt to changes in women’s fast-fashion and evolving consumer behavior.

Maeve, known for its blend of classic silhouettes and modern flourishes, will now operate independently with dedicated storefronts and separate digital channels, including new social media accounts and editorial content platforms, according to a Monday (Aug. 4) press release. The brand is inclusive, spanning plus, petite, tall and adaptive options, which broaden its reach as the industry contends with demands for representation.

Maeve has nearly 2 million customers and was the most-searched brand on the Anthropologie website over the past year, the release said. It is also a driver of TikTok engagement. Several of the company’s most “hearted” items online are already from the Maeve label.

“Maeve has emerged as a true driver of growth within Anthropologie’s portfolio,” Anu Narayanan, president of women’s and home at Anthropologie Group, said in the release. “Its consistent performance, combined with our customers’ emotional connection to the brand, made this the right moment to evolve Maeve into a standalone identity.”

While many retailers have retreated from new brand creation, opting instead to consolidate or focus on core labels, Anthropologie’s move suggests confidence in cultivating sizable, engaged consumer communities around sub-brands.

Anthropologie is backing Maeve’s standalone debut with a comprehensive marketing campaign, including influencer-driven content, a new Substack, a launch event in New York, and a charitable partnership, per the release. The first Maeve brick-and-mortar store is set to open in Raleigh, North Carolina, in the fall.

The move comes as the apparel sector in the United States sees shoppers valuing not just price and selection, but brand story, inclusivity and digital experience. While the outcome remains to be seen, Anthropologie’s gamble on Maeve reflects a belief that consumers remain eager to embrace distinctive, thoughtfully curated fashion.

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Meta Faces Scrutiny Over AI Prompt Disclosure | PYMNTS.com

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Meta’s artificial intelligence assistant may publicly share user prompts, and its apps may have exploited a technical loophole to track Android users without their knowledge, CPO Magazine reported.

Meta’s AI app introduced a pop-up warning that content entered by users — including personal or sensitive information — may be publicly shared, per a June 20 report. It seems these prompts can be published in the “Discover” feed. The feature, which launched earlier this year, showcases AI-generated content and occasionally displays user-submitted prompts, some of which have included private data such as legal documents, personal identifiers and even apparently audio of minors.

Although users can opt out, the setting is enabled by default, and users must manually disable it, the report said. Privacy advocates argue that no other major chatbot service offers a comparable mechanism that proactively republishes private inputs.

Consumers already have privacy concerns around generative AI. The PYMNTS Intelligence report “Generation AI: Why Gen Z Bets Big and Boomers Hold Back” found that 36% of generative AI users are nervous about these platforms sharing or misusing their personal information, and 33% of non-users are kept from adopting the technology because of the same hesitations.

Separately, Meta may have taken advantage of an Android system vulnerability known as “Local Mess” to harvest web browsing data, per a June 17 CPO Magazine report. The loophole, involving the mobile operating system’s localhost address, potentially allowed Meta and Russian tech company Yandex to listen in on users and correlate their behavior across apps and websites. The tech giants may have been able to do this even when users were browsing in incognito mode or using other privacy protections. This data could be linked to a user’s Meta account or Android Advertising ID.

Meta has since halted sending data to localhost, characterizing the issue as a miscommunication with Google’s policy framework. Privacy watchdogs and experts say both cases could trigger regulatory action in the European Union and other jurisdictions.

Meta is already facing legal action over its privacy practices in an $8 billion lawsuit concerning alleged data misuse.

Google, for its part, is scheduled to appear in court later this month for allegedly violating the privacy of both Android and non-Android mobile phone service users.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

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