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.

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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.

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.

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