The trend had seemed to run out of steam lately, eclipsed in the media by the rise of artificial intelligence—which it has notably failed to incorporate. Yet CaixaBank’s push into extra-banking services is regaining momentum. Its latest move: Facilitea Casa, a dedicated real estate portal, joins a lineup of non-banking ventures from the Spanish bank and its Imagin brand.

While other similar initiatives rely on partnerships with property listing sites or equivalent players, CaixaBank built its own offering in-house. It allows real estate professionals—including its own subsidiary Building Center—to showcase their properties, for sale or for rent, on its platform, promising them potential visibility among its millions of retail customers. Over 1,000 professionals have reportedly signed up.

For people looking for a home, whether or not they have an account with CaixaBank, Facilitea Casa follows a traditional model. After choosing a location, various filters (price, size, number of rooms, amenities, etc.) let users refine results drawn from a database of 40,000 properties. And as on any real estate aggregation site, visitors are invited to contact the agency if they want more information or to schedule a visit.

Unsurprisingly, CaixaBank embeds its own services—financial and otherwise—into the experience. In addition to the mandatory mortgage simulator—which, notably, redirects to the bank’s website—there’s also a link to its online store (via another redirect), where those who have already found their dream home can buy the furniture and appliances they’ll need before moving in.

The idea of a bank taking over the real estate journey—aiming to capture future loan clients as early as possible—is hardly new. To name just two among many examples, CommBank was a pioneer on mobile back in 2010, while BBVA launched Valora View on the Spanish market in 2018. None, as far as I know, have demonstrated strong long-term results, with most eventually being abandoned—a failure that I suspect stems mainly from consumers’ resistance to changing deeply ingrained habits when searching for a home. Whether Facilitea Casa can buck the trend remains to be seen.  

I’ve been urging the financial industry for years to move beyond passive personal finance management tools and offer consumers a true coach that actively guides them toward better money practices. BBVA is finally leading the way. Could this be the start of a broader industry awakening?

The underlying needs are obvious, as countless studies show. In Spain, for example, 84% of women do not plan for retirement, 80% of savers set no goals, and 70% of people do not save enough to build an emergency cushion. While it seems natural for banks to address these issues, they often do so superficially, with generic recommendations that have limited impact.

With its new assistant, BBVA is tackling the problem head-on through a concrete and personalized approach supported by powerful data analysis models (and artificial intelligence, of course—it is 2025, after all). Users are invited to join the program as soon as they see their current financial status upon logging in. If they accept, the tool diagnoses their situation along three axes: saving capacity, availability of an emergency fund, and debt levels.

Based on this analysis and its results, the tool then suggests options for remediation or improvement: spend less, save to cover unexpected events, or prepare for a future project. Once the user makes a choice, a tailored action plan adapted to their habits is put in place to guide them step by step toward achieving their goals. 

The recommended actions remain fairly basic—avoiding “ghost purchases” (those unnecessary items that quietly drain your budget), setting up automatic transfers to a savings pot, and so on—but the real value lies in the contextual interactions. Additionally, a few gamification features are included to maintain engagement, although I remain skeptical of the elementary mechanisms implemented (mainly virtual badges awarded when progress is detected).

BBVA’s coach represents a meaningful advance compared to traditional PFM solutions or tools that focus exclusively on a single area (such as goal-based saving). Consumers need to be guided across the full spectrum of their personal finances, as the hardest part for the average person is often juggling all these demands simultaneously. Yet it still lacks some essential components to reach perfection.

First, the dimensions covered deserve expansion, separating lifelong dreams (such as retirement planning or buying a home) from short-term projects (organizing a trip, buying a new phone) and adding protection needs (including insurance). It’s also unclear whether the platform can handle multiple goals simultaneously, and whether external accounts can be integrated for multi-bank customers. 

Last but not least, an educational component alongside recommendations would be a worthy addition—and the ultimate level of guidance would incorporate psychological perspectives for deeper personalization and maximum effectiveness.

Klarna, the Swedish fintech that just weeks ago admitted it was reconsidering its decision to replace most of its call center agents with virtual ones, is now unveiling a direct line to the avatar of its CEO. But will it truly deliver on its promise to improve the collection and use of customer feedback?

The concept allows consumers to interact with an AI that takes on the appearance, voice, and (at least shareable) knowledge of Sebastian Siemiatkowski, enabling them to share comments, complaints, and suggestions about the company and its services—or ask about his vision. The goal of this alternative to traditional satisfaction surveys is to better leverage the insights gathered in this way.

To this end, the system is designed to hold real conversations—the quality and relevance of which remain to be seen—without predetermined direction (unlike standard questionnaires), which Klarna hopes will encourage engagement. Additionally, the collected results are analyzed by AI to populate an innovation dashboard, allowing teams to track requests in real time and prioritize related tasks.

As this description suggests, using a CEO avatar is purely a gimmick—one that could even backfire if pranksters decide to vent repeatedly at it. I’m also skeptical about the entirely “open” conversational approach, which, on one hand, will likely attract mainly dissatisfied customers (as with other methods, admittedly), and on the other hand, ignores the diverse communication preferences people have.

In reality, as Klarna itself acknowledges, the true value of this initiative lies downstream in how the collected data is used. Regardless of how feedback is captured, its potential is only realized if it helps uncover customer pain points. And there are countless opportunities to gather such insights, including through passive means (monitoring social media, analyzing platform usage patterns…) that are far less intrusive and more spontaneous.

In conclusion, I can’t help but compare Klarna’s initiative to an old idea once implemented by Umpqua Bank in the US: a red phone in every branch allowing customers to call the CEO directly, aiming to create a sense of closeness between the institution and its clients. In this dehumanized version, however, the concept loses its meaning and ends up feeling rather pointless.

Like so many banks around the world searching for growth opportunities beyond their core business, Chase is launching its own e-commerce store. However, it has chosen a very specific positioning that makes the initiative less risky than previous attempts—and perhaps gives it a chance at success.

In short, The Shops at Chase is exclusively available to holders of the US bank’s main payment cards, and its operation is closely tied to the rewards programs associated with those cards.

The shopping gallery, integrated within Chase’s web and mobile apps, features a curated selection of brands—generally premium or luxury names such as Baccarat, Bang & Olufsen, Breitling, Dyson, Ray-Ban, and others—across various categories. The lineup is expected to evolve over time. One notable feature is that visitors are regularly shown product recommendations based on their preferences, which are presumably identified through their transaction history.

As an incentive, shoppers will receive promotions on frequently updated products, in addition to the points they normally accumulate under their card agreements. Conversely, they can also use their available rewards to pay for purchases in full or in part. If they use their Chase card for any portion of the payment, the checkout process is simplified, with payment information transmitted automatically and shipping addresses pre-filled.

While the concept may resemble other bank-run retail platforms, linking this marketplace with Chase’s card business (and its broader retail payment capabilities) lends it added legitimacy. For instance, the ability to “spend” rewards directly without any conversion steps—across a wide range of products—is an attractive feature, at least enough to get customers to try it out.

From the bank’s perspective, the anticipated benefits are probably the usual ones. Simply acting as a distributor holds little economic value in itself. Rather, the main value lies in capturing customers within its ecosystem, encouraging greater use of its cards in particular.

There’s no guarantee this kind of move into consumer retail will fare better than similar past attempts by banks, which have struggled to gain traction. However, with its exclusive promotions, its coherent integration into the e-commerce context, and its behavior-based targeting approach—which is, as far as I know, unprecedented—Chase is taking care to ensure its initiative feels legitimate in the eyes of its customers… something many of its competitors have failed to achieve.

Just days after Griffin launched its “agentic bank” and at a time when the industry as a whole is still struggling to adapt to open finance requirements, the insurance sector now sees its first pioneer of ready-to-use services for AI applications, in the form of US-based Sure.

The approach, shared by both companies, is likely to quickly become a standard. It involves adapting existing APIs into a format compatible with the Model Context Protocol (MCP), originally developed and open-sourced by Anthropic. MCP ensures that exposed functions are compatible with an increasing number of platforms adopting it, thereby allowing their virtual agents to autonomously perform actions seamlessly.

Sure’s solution covers the entire insurance lifecycle, from instantly generating quotes based on customer requests to policy issuance, administration, claims management, and follow-up—all governed by pre-set parameters. Equipped with these capabilities, a bot can handle a customer’s insurance needs end-to-end without first requiring a separate orchestrating application to coordinate these tasks.

Naturally, the offering covers the full range of products (and insurers) available via Sure, with built-in regulatory compliance through defined guardrails. Combined with controls at the underwriting level, these mechanisms are designed to reassure the startup’s partners, who understandably fear AI “hallucinations” or errors that could damage their reputations or lead to legal liabilities.

The service is currently in beta testing and, as expected, initial feedback suggests excellent results. However, the reported time savings—95% for underwriting and 80% for support responses—lack a baseline reference point and could simply reflect a previously inefficient process. Furthermore, like the highlighted high satisfaction rates, these gains only apply to the onboarding stage.

Finally, as is always the case with automation, it’s possible that initial enthusiasm driven by novelty will fade over time, leading to declining perceptions. In conclusion, while it may be worthwhile to test the technology to understand its capabilities and limitations, it will be crucial to assess perceived quality over the long term to avoid eroding customer trust. Another persistent question remains: in an industry known for extreme caution, are insurers truly ready to entrust their customer relationships to artificial intelligence?

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