Where most financial marketing leans on features, rates or seasonal spikes, Monzo chose a bigger ambition – make money knowledge accessible to everyone. Published with Penguin, The Book of Money is a real personal finance handbook designed for people who would never normally pick one up. It is warm, practical and jargon free, shaped by insights from millions of Monzo customers.

The work started with a bold insight. Monzo’s research found that 51 percent of Brits feel they aren’t reaching their financial potential due to lack of money knowledge, and 72 percent of under 34s feel financially held back. That problem became the backbone of the creative idea.

To launch the book, Monzo opened The Book Nook, a hot coral pop up bookstore in Soho. Visitors completed a money goals quiz and walked out with a personalised book cover, one of more than 800 titles generated from 8,000 ideas. It was a simple but powerful way of making money feel human, relatable and personal.

The campaign then scaled nationally through retailers, social content, OOH and a five part video series, “Lessons from the Book of Money”, fronted by creator Shu Lin. The series has already generated over seven million views, turning book chapters into everyday money lessons delivered in under 60 seconds.

Most importantly, Monzo is donating its share of book royalties to Money Ready, a financial education charity supporting around 50,000 people a year.

AJ Coyne, VP Marketing & Growth at Monzo, described the intent clearly:

Congrats Maja Bayyoud Writing Lead, Monzo and your brilliant all-female team and Coral Garvey Creative Director, Monzo, on bringing to life such a wonderful, personal finance guide for people who’d never normally read one!!

Why we love it…

Monzo’s campaign is everything modern financial marketing should be:
• research led
• culturally relevant
• values driven
• creative at scale
• anchored in real human need

Tristan Fawley Executive Creative Director, The Dubs Agency said

It’s a campaign that educates, inspires and elevates the category and a deserving winner of Financial Marketer’s Campaign of the Year 2025.

Congratulations Monzo on a great campaign!

The post ‘Monzo’ wins Financial Marketer 2025 Campaign of the Year appeared first on Financial Marketer.

As we approach 2026, the financial marketing landscape is poised for dramatic transformation. The Dubs Agency reveals six key trends that will reshape how financial brands connect with professional audiences, from the rise of Meta as a B2B powerhouse to the ethical deployment of AI-generated content.

Meta emerges as a serious B2B player

For years, LinkedIn has dominated the conversation around professional audience targeting. But 2026 will mark a turning point as Meta platforms establish themselves as credible alternatives for reaching institutional investors and financial decision-makers.

The data tells a compelling story. According to Brunswick Group’s Digital Investor Survey, 75% of professionals now use secondary social media platforms alongside LinkedIn. These sophisticated investors aren’t limiting themselves to a single channel, they’re consuming content across multiple touch points throughout their research and evaluation process.

Meta’s targeting capabilities have evolved to match this opportunity. Financial marketers can now reach users by job title, target competitors’ audiences, upload matched audience lists, and track conversions with precision that rivals LinkedIn’s offering. Early adopters are already seeing the results, with The Dubs Agency reporting highly cost-effective on-site conversions from professional audiences reached through Meta platforms.

The implication for 2026 is clear: successful financial marketers will need to develop sophisticated multi-platform strategies rather than putting all their eggs in the LinkedIn basket.

Video dominates the content mix

If 2025 was the year video became important, 2026 will be the year it becomes indispensable. Video uploads on LinkedIn have surged 45% year-on-year, and the platform projects an additional 65% growth by 2025, setting the stage for video-first strategies in the year ahead.

This shift reflects changing consumption patterns among financial professionals who increasingly prefer dynamic, visual content over static text. Financial marketers who have been slow to embrace video production will find themselves at a significant competitive disadvantage.

The key will be developing scalable video content strategies that balance production quality with volume. Financial brands should expect to produce regular video content across educational pieces, thought leadership interviews, product explainers, and market commentary to maintain visibility in increasingly video-saturated feeds.

Connected TV reaches critical mass

Connected TV advertising has crossed the threshold from experimental channel to mainstream media buy. CTV refers to television content streamed over the internet through smart TVs, devices like Roku and Apple TV, or streaming services like Hulu and YouTube, rather than traditional cable or broadcast signals.

The contrast with traditional linear TV buying is stark. Legacy television means purchasing dayparts and hoping your target audience is watching, with minimal targeting precision and limited measurement. You’re paying for broad reach during commercial breaks that viewers routinely ignore or skip.

CTV transforms this equation entirely. Financial marketers can now target households based on demographics, job titles, and viewing behaviour – reaching CFOs, wealth advisors, or institutional investors with precision impossible in traditional TV. Ads appear within streaming content in non-skippable formats, and detailed attribution shows which households viewed and what actions they took afterward.

The numbers reflect this shift, eMarketer reports in 2025, CTV ad spend in the United States is projected to reach US$33.3 billion, representing nearly 10% of total digital advertising expenditure. Statistic data shows these ads deliver a 95% completion rate, dramatically outperforming traditional video advertising. Most tellingly, 98% of LinkedIn users now watch connected TV, substantially higher than the 83% who watch linear television.

Professional audiences have migrated to streaming platforms, yet many financial brands continue allocating significant budgets to traditional TV based on legacy buying patterns. The question for 2026 is no longer whether to invest in CTV, but how quickly you can shift budget from outdated linear approaches that are delivering diminishing returns.

Immersive storytelling transforms long-form content

The traditional PDF report is facing extinction. In its place, financial marketers are embracing immersive, interactive digital experiences that drive dramatically higher engagement.

Nuveen’s Equilibrium Institutional Investor report exemplifies this evolution. Built using no-code responsive page development tools, the report features interactive infographics, dynamic charting, and multi-chapter navigation that guides readers through complex investment themes. The content is available in multiple languages including English, German, and Japanese, extending its reach across global markets. And won a Gramercy Financial Content Award, Gramercy Asset Management Content Marketing Award and was shortlisted for the 
Financial Services Forum Marketing Effectiveness Awards.

As Flourish reports, the results speak for themselves interactive reports generate 73% more read time compared to traditional PDFs. For financial marketers struggling to capture attention for lengthy thought leadership pieces, this format provides a path to making substantial content feel approachable and engaging.

In 2026, expect to see interactive annual reports, market outlook pieces, investment strategy guides, and ESG reports that leverage these tools to transform static content into immersive experiences.

AI-Powered podcasts scale audio content

Audio content has long promised efficiency for time-pressed financial professionals, but production barriers have limited its adoption. AI-powered podcast creation tools are removing these obstacles, enabling financial marketers to atomise written editorial content into conversational audio formats at scale.

These platforms can transform blog posts, research reports, and articles into natural-sounding podcast conversations. They offer the ability to incorporate recorded stakeholder voices, adjust scripts for compliance approval, and publish directly to platforms like Spotify.

The Financial Marketer podcast demonstrates this capability in practice, showing how AI can elevate editorial content without requiring extensive audio production resources. For financial brands with substantial written content libraries, this technology offers an efficient path to reaching audiences who prefer audio consumption.

Multilingual video becomes accessible

Global financial brands have long struggled with the cost and complexity of producing video content for multiple regional markets. AI avatar technology is dramatically reducing these barriers, making multilingual video strategies accessible to organisations of all sizes.

These tools can take existing video content and rapidly generate versions with AI avatars speaking in different languages while maintaining consistent messaging and visual quality. The technology has matured to the point where the output appears natural and professional, suitable for external communications rather than just internal use.

For financial marketers operating across multiple geographies, this capability enables truly localised video strategies without multiplying production budgets. Expect to see increased use of this technology for everything from CEO communications to product explainers to educational content throughout 2026.

Josh Frith, Founder The Dubs Agency – AI Avatar speaking in Spanish and Mandarin.

Preparing for 2026

These six trends collectively point toward a financial marketing landscape that is more visual, more automated, and more distributed across channels than ever before. Success in 2026 will require financial marketers to embrace new platforms, invest in video capabilities, experiment with AI tools, and develop truly multi-channel strategies that meet professional audiences wherever they consume content.

The organisations that thrive will be those that view these changes not as threats to traditional approaches but as opportunities to achieve greater reach, engagement, and impact with the audiences that matter most to their business.

If you enjoyed this article and would like to know more contact The Dubs Agency we’d love to help.

[For full disclosure: The author used Claude to research this article while the podcast was created using ElevenLabs]

The post 2026 financial marketing predictions that will transform the industry appeared first on Financial Marketer.

In this article, we’ll explore:

• The promise and current adoption of AI in finance

• What parts of storytelling AI already handles well

• What it struggles with (and often fails)

• Strategic guidelines and guardrails

AI in finance

Before diving into storytelling, it helps to understand where AI has already taken root in finance, because storytelling builds on those foundations.

• According to NVIDIA’s State of AI in Financial Services survey, 43% of respondents already use generative AI in their organisations.

• A KPMG global study of ~2,900 finance executives found many are rolling out AI across accounting, planning, treasury, risk and tax operations.

• All About AI reports the global AI in finance market is estimated at USD 38.36 billion, with forecasts suggesting it could reach USD 190 billion by 2030.

These numbers show that AI is no longer hypothetical in finance, it’s increasingly operational. But most adoption to date is in back-office, pattern recognition, anomaly detection, forecasting, and document processing rather than full narrative creation.

What AI can do for financial storytelling

Here are areas in the storytelling pipeline where AI is already quite capable and where it adds genuine value:

1. Data ingestion, structuring & anomaly detection

One of the unglamorous but crucial steps in storytelling is preparing the raw financial data: cleaning, aggregating, ensuring consistency, flagging anomalies or outliers. A.I. (especially machine learning models) excel at pattern detection, outlier identification, consolidation across data sources, and detecting correlations that might be non-obvious.

2. Draft narrative / first pass commentary

Generative AI can transform processed financial data (e.g. revenue by segment, margins over time, variance from budget) into narrative text. For example, it can write a first-draft “management commentary” or “insight summary” that says: “Segment A’s margin contraction in Q2 was largely driven by input cost inflation, partially offset by higher volume in Region X …”

KPMG notes that generative AI, combined with finance, “can create better speed and efficiency by eliminating redundant or manual activities, allowing finance professionals to focus on higher-value tasks”, though “it is only as good as the underlying data and well-engineered prompts.”

3. Visualisation & adaptive charts

AI tools can suggest optimal chart types, build dynamic visuals, or even animate transitions. Some platforms can auto-select chart frames, colour schemes, or overlays (e.g. revenue trend + benchmark). These visuals support the narrative by making data more digestible and engaging.

4. Text-to-video & multimodal storytelling

The newer frontier: converting narrative and visuals into short videos or animated summaries. Platforms like Mootion the “AI financial explainer video maker” help turn complex financial concepts, investment strategies, wealth-management advice and personal-finance topics into video stories, combining chart animation, voiceover, scene transitions and narrative text. As video becomes more consumed in finance communications, social media, or internal updates, this capability is significant.

In fact, as Finextra reports UBS has begun deploying AI-generated avatars of its analysts to deliver video research content to clients,  scaling video production while freeing analysts to focus on deeper insights.

5. Personalisation & scenario variants

Because AI is programmable, it can generate variant narratives tailored to different audiences (e.g. investors vs operations) or scenarios (optimistic, base, downside). It can also more easily produce “what-if” or scenario-driven storylines by combining data inputs with narrative templates.

What AI Can’t (or doesn’t reliably) do yet

While expectations are high, there remain several limitations, risks, and failures that financial storytellers should be wary of:

1. Deep domain insight, judgment & nuance

Financial storytelling often hinges on domain understanding, intuition, subtlety, and judgment calls (e.g. regulatory implications, market sentiment, qualitative drivers). AI can suggest patterns, but cannot reliably substitute for an expert’s interpretive reasoning. It may miss counterintuitive insights or over-emphasise correlations that lack causal basis.

2. Contextual consistency over long narratives

AI may produce internally inconsistent narratives, especially over longer explanations (e.g. repeating contradictory statements, drifting focus). Ensuring logical narrative flow, contextual coherence, or a crisp “through-line” in longer documents remains challenging for many generative models.

3. Handling ambiguous, conflicting or missing data

When data is incomplete, contradictory, or ambiguous, A.I. struggles. It may attempt to hallucinate or smooth over gaps, potentially generating misleading statements. Human oversight is required to vet and correct.

4. Creativity, metaphor, tone & audience empathy

Storytelling is also about voice, emotion, resonance. AI generally lacks true creativity, empathy or deep sense of audience feedback. It may write pedestrian statements or fail to tailor tone dynamically. The “human edge” intuition, rhetorical framing, emotional resonance remains a competitive differentiator.

As Scott Winters, puts it in this Financial Gravity article

5. Bias, error, hallucinations & overconfidence

Generative models can hallucinate facts, misstate numbers, invent references, or misinterpret prompt context. Unless constrained carefully, these outputs risk inaccuracy or misleading claims. Rigorous validation, guardrails, and fact-checking remain essential.

6. Governance, auditability & compliance

In regulated financial environments, story content (especially forward-looking statements or risk disclosures) must be auditable and defendable. A.I. models often operate as “black boxes.” Ensuring traceability (which data used, which prompt, who edited) is a complex but necessary requirement for responsible use.

7. Visual / video limits

Although AI video generation is advancing, there are limits: high resolution, long-form coherence, facial realism, lip-sync accuracy, audio synchronisation and contextual transitions remain challenging. Text-to-video models are computationally intensive, limited in output length, and prone to artifacts.

Strategic guidance & best practices

Here are the principles and guardrails for integrating A.I. into your financial storytelling workflow:

KPMG emphasises that generative AI’s effectiveness depends heavily on “well-engineered prompts” and robust embedding into finance workflows.

What the future looks like

• Multimodal models are advancing: systems like MAViS or MM-StoryAgent research projects attempt to coordinate script writing, visuals, character modelling and audio in unified storytelling pipelines.

• Text-to-video models like Veo (from DeepMind Google) are evolving to support longer content with improved audio/video sync.

• More financial institutions will adopt hybrid avatars (as with UBS), enabling scalable video research and narration.

• The frontier will shift from “drafting commentary” to “interactive, live narrative agents” (e.g. investor dashboard that tells evolving stories in real time).

• Regulation, explainability, bias controls, and domain certification will become prerequisites for adoption in regulated settings.

AI is a powerful enabler in the financial storytelling toolkit, accelerating data work, drafting commentary, generating visuals, and even producing short video stories. But it is not a substitute for the human judgment, domain nuance, narrative sense, and accountability that financial storytelling demands.

The ideal path is augmentation, not replacement: let AI handle repetitive or structured tasks, while human experts refine, validate, add insight, tone and integrity. With disciplined guardrails, iterative adoption, and transparency, AI can amplify storytelling reach without compromising trust.

If you enjoyed this article and would like to know more contact The Dubs Agency we’d love to help.

[For full disclosure: The author used Perplexity to research this article while the podcast was created using ElevenLabs]

The post What AI Can and Can’t do for financial storytelling appeared first on Financial Marketer.

Neuro branding uses neuroscience and behavioural science to shape how customers feel about financial brands, not just what they think. For financial marketers in banking, fintech, insurance or wealth management, this means using insights from how brains process trust, risk, reward, visual cues and storytelling, so that marketing works not only on logic but on emotion.

Tools may include eye tracking, EEG, user-interface testing, biometric feedback, and behavioural experiments. The goal is to reduce friction (especially around complex financial decisions), enhance trust, increase retention, and improve lifetime value.

Why neuro branding matters for financial marketers

Numbers & evidence

• A Katalysts.net study showed that message retention in financial content can improve by up to 40% when neuromarketing or psychology-informed tactics are used.

• In a MDPI research project with banking websites, eye-tracking and heat maps revealed that users’ immediate focus (first 20 seconds) on key trust signals (e.g. security badges, clear pricing, simple layout) correlated strongly with lower bounce rates.

• Finextra research in content marketing for financial services, shows emotional storytelling (as opposed to fact-only content) has been shown to drive higher engagement, improve brand trust, and shorten sales cycles.

As Lisa Joyce from the The Financial Brand says, Neuroscientists have an expression:

That means even as financial products become more digital, consumers are still driven by basic emotional and neurological drivers: fear, reward, loss aversion, trust. Neuro branding helps financial marketers speak to those drivers, not just features, terms or numbers.

How financial brands can apply neuro branding in practice

• Design interfaces for trust: Simple, clean UI; clear labels; calming colour palettes; minimal jargon; early display of credibility symbols. UXDA has documented how emotional motivations and simplification reduce anxiety in digital banking.

• Storytelling and framing: Use investor/customer narratives, real-life goals, aspirational frames (saving for education, retirement, happiness) rather than technical specs. Finextra reports these approaches trigger emotional engagement and memory.

• Micro-nudges and small wins: For fintechs or savings apps, UXDA reveals celebrating increments (goals reached, progress bars, reminders) produces dopamine feedback, improving retention and habit formation.

Research in consumer neuroscience by Kenning and Hubert (2008) indicates that subconscious, emotional factors strongly influence our decisions. In finance, these factors are magnified by everyone’s subconscious fears about money, risk and loss. Leveraging neuromarketing principles allows brands to tap into users’ natural motivations, creating engaging, trust-building experiences that build meaningful financial well-being.

Considerations and challenges

• Cost vs ROI: Some neuroscience tools are expensive. Financial firms need to pilot small and measure carefully (A/B tests, control groups) to ensure the investment pays off.

• Compliance & transparency: Regulatory constraints in finance require that emotional claims don’t mislead, that risk is clearly disclosed, and that message framing is ethical.

• Trust is fragile: If consumers feel manipulated, that can harm reputation. Neuro branding must aim for emotional resonance, not manipulation.

For financial marketers, neuro branding is more than a “nice to have.” It’s fast becoming a competitive advantage in markets where trust, emotion, and clarity matter as much as product features. Embed science-backed methods; measure results; act on findings. Use emotional cues, stories, interface clarity. Do it well, and you’ll see better retention, lower churn, higher lifetime value and stronger brand equity.

[For full disclosure: The author used Perplexity to research this article and the podcast was created using ElevenLabs]

The post What is Neuro branding in finance? appeared first on Financial Marketer.

Search engine marketing (SEM) has been a cornerstone of digital media strategies for financial brands for more than a decade. But the landscape is shifting. Rising costs, shrinking organic reach, and the dominance of AI-generated answers are reshaping how consumers find and engage with financial services online.

Forward-looking marketers are asking: if SEM is no longer enough, what comes next?

The SEM squeeze

The cost of search ads continues to climb. Wordstream reports that the average cost-per-click for financial services is $3.44, one of the highest of any sector. Competition for key terms like “home loan” or “financial adviser” is intense, but even the top paid placements no longer guarantee meaningful traffic.

AI-powered search experiences are accelerating the shift. A Semrush study predicts that 75% of search traffic will be powered by generative AI by 2028. Zero-click results and summaries mean fewer people are clicking through to brand websites.

Smarter paid media: what’s working now

Financial marketers are diversifying budgets into channels that deliver stronger visibility, better targeting, and more measurable outcomes:

• Contextual advertising: Instead of relying on third-party cookies, brands are aligning with trusted financial content where audiences are already engaged. ReportLinker notes contextual targeting is expected to grow 13.3% from 2020- 2027.

• Native and sponsored content: Dianomi and other finance-specific networks report click-through rates up to 5x higher than display because ads blend with premium publisher environments.

• Paid social with creator partnerships: Fidelity research shows nearly 50% of UK investors now look to social media for financial insights. Paid amplification of influencer content can extend reach beyond organic followings.

• Programmatic guaranteed buys: For financial brands concerned about compliance, programmatic direct deals on premium inventory provide brand safety while still leveraging automation.

Lily Ray, Senior Director of SEO and Head of Organic Research at Amsive Digital says

Trends to watch

• AI-driven media optimisation: Platforms are increasingly automating bidding and placement, but financial brands need to balance efficiency with governance and compliance.

• Retail media networks: Banks and fintechs with owned ecosystems are beginning to explore retail media, offering advertisers access to highly segmented financial audiences.

• Video-first campaigns: Paid video, especially short-form on LinkedIn, YouTube and TikTok, is outperforming static display in engagement for financial education and brand storytelling.

The bottom line

SEM is still part of the mix, but it can no longer carry the weight of a financial brand’s paid media strategy. Success now requires a broader, smarter approach that blends context, credibility, and creativity across channels.

For financial marketers, the next chapter in paid media isn’t about chasing clicks. It’s about being discoverable in the right places, with the right message, at the right moment.

If you liked this article and want to know more contact The Dubs Agency we’d love to help.

[For full disclosure: The author used Perplexity to research this article and the podcast was created using ElevenLabs] 

The post Beyond SEM: smarter paid media for financial brands appeared first on Financial Marketer.

‘Don’t’ – keep pouring budget into SEM as your primary tactic

If “coming top of the Google search rankings” is still your number one goal, it’s time to rethink. AI-powered summaries, knowledge panels, and zero-click answers are reducing organic and paid click-throughs. In many cases, even the top ad placement no longer guarantees meaningful engagement.

In 2025, the real battle is for visibility inside AI-generated responses, and that means your digital strategy has to evolve beyond search listings.

‘Don’t’ – target as narrowly as possible using third-party cookie

Relying on cookies from multiple sources to micro-target might look clever on paper, but in practice it’s increasingly risky and less effective. Between privacy regulations, browser restrictions, and consumer pushback, the cookie’s lifespan is nearly over.
Getting “more granular” doesn’t automatically deliver better results. What’s working now is contextual targeting – aligning your brand with relevant, trusted content where your audience is already engaged. It’s privacy-safe, brand-safe, and performs better for financial services in particular.

‘Don’t’ – chase scale at all costs, and measure success in impressions

A scattergun approach to “owning the open web” might deliver big impression numbers – but impressions alone don’t translate into new clients or assets under management.
Much of the open web is plagued by MFAs (Made-for-Advertising sites) that inflate reach without delivering quality engagement. Financial brands should focus on premium publisher environments where context, audience quality, and brand safety are built in.

‘Don’t’- gate all your content behind a PDF download

Yes, content is critical. But hiding it all behind a registration wall or offering only static PDFs is a fast track to user drop-off. Audiences in 2025 expect multi-format content, articles, videos and infographics, delivered through frictionless, intelligent user journeys.
The most effective approach? Surface key insights within the environment where your audience is already consuming media, for example, embedding core messages directly into a relevant article page on a trusted publisher site. This boosts visibility, improves time-on-content, and encourages deeper engagement.

The takeaway

The digital landscape for financial services has shifted. AI is reshaping search behaviour, cookies are disappearing, and audiences demand value upfront. Winning brands in 2025 will:

• Focus on AI-era discoverability over search rank obsession.
• Replace cookie-driven micro-targeting with smart contextual placement.
• Prioritise quality environments over sheer scale.
• Deliver engaging, multi-format content where the audience already is.

In short: stop chasing outdated metrics, and start building strategies that work in the world as it is, not as it was.

If you liked this article and want to know more contact The Dubs Agency we’d love to help.

[**Full disclosure: The views and opinions expressed in this publication are those of the author. They do not reflect the views or opinions of any organisation or entity.]

The post How ‘NOT’ to do financial services digital marketing in 2025 appeared first on Financial Marketer.

In today’s fast‑moving financial marketing world, AI tools are making powerful capabilities accessible to all: content generation, data analysis, localisation at scale, automation. With widespread adoption, Gartner explored how AI has democratised access to productivity and insight across firms, countries, and roles. But that’s precisely why human creativity now matters more than ever.

AI boosts human creativity, but doesn’t replace it

A new arXiv meta‑analysis of 28 studies and over 8,000 participants found:

• GenAI alone performs about the same as humans on creative tasks (g = −0.05).
• Humans using GenAI significantly outperform individuals working solo (g = +0.27).
• However, idea diversity falls when relying on AI alone (g = −0.86).

In plain terms: AI acts like a creativity amplifier but diversity, nuance and originality still come from humans.

Industry leaders say: AI empowers, doesn’t replace

Stephan Pretorius (WPP CTO), in the The Australian advocates for democratised AI access, saying

How this plays out in finance marketing

DO: Use AI to handle scale, speed, and structure

• Batch‑generate multilingual summaries, content variations, compliance safe drafts.
• Automate data pulls, campaign segmentation, A/B tests, and optimisation.

DO: Lean into human strengths

• Focus on deep insights, storytelling, brand tone, ethics, and creative concepting.
• Use AI‑powered ideation but retain human judgment for final messaging and strategy.

DON’T: Assume tools equal creativity

• Don’t let AI default to lazy repetition or template driven thinking. Diverse, bold ideas still require human curiosity.
• Avoid substituting human review with unchecked AI output, especially in regulated finance contexts.

AI & creative agency brainstorming

WPP explains in The Times, half of the agency’s 96,000 employees now use its internal AI platform (“WPP Open”) generating campaign slogans, video concepts, “shower‑thought” prompts, and synthetic focus‑group testing. But WPP’s CTO emphasises that

Tools equalise, creativity differentiates

AI tools have made capabilities once reserved for large budgets available to many. That means the next frontier for differentiation is not speed or volume—but the quality, originality, and authenticity of human-generated ideas.

Final thoughts & best practices

1. Build a solid foundation first: strategy, brand values, audience insight, AI amplifies what already exists, it can’t invent it.
2. Apply guardrails and review: ensure compliance, ethical standards, and tone consistency across AI‑generated content TechRadar.
3. Use AI for ideation not final drafts: let humans curate, remix, elevate raw AI output into stories with meaning.
4. Measure beyond quantity: track creative impact, engagement lift, share of voice, brand sentiment, not just output volume.

AI makes capabilities accessible but human creativity remains the ultimate competitive edge in financial marketing.

If you liked this article and want to know more contact The Dubs Agency we’d love to help.

The post Why AI levels the playing field, but creativity still wins the day appeared first on Financial Marketer.

Familiar with the message “Lots of people are creating images right now…” while this is  frustrating there’s no doubt that artificial intelligence is revolutionising visual storytelling and nowhere is this more evident than in the explosive growth of AI image generation tools. In 2025, this technology has shifted from novelty to necessity, empowering marketers, designers, and content teams to produce stunning, on-brand visuals in seconds.

The growth of AI image creation

Adoption rates are soaring. According to Salesforce, 62% of marketers are now using generative AI to create new image assets, and 76% use it for general content creation. The AI image generation market itself was valued at $336.3 million in 2023 and is expected to grow 17.5% from 2024 to 2032 (Global Market Insights).

Even more telling: a staggering 71% of images shared on social media in 2024 were AI-generated, highlighting how widespread and accessible this technology has become (ArtSmart).

Jessica Apotheker, CMO of BCG, shared insights from a recent BCG survey of more than 200 CMOs, the data shows

And while speaking at Cannes Lions 2025 she emphasised a critical need to balance creativity and analytical rigor to preserve authenticity and emotional resonance in marketing.

Why marketers are embracing AI-Generated images

AI image generators deliver a unique combination of speed, cost-efficiency, and control. Instead of relying on costly photo shoots or generic stock images, marketers can now create bespoke visuals tailored to campaigns, audiences, and brand aesthetics, with minimal resources.

This shift allows for greater experimentation, rapid A/B testing, and more consistent brand visuals across channels. It’s not just about convenience; it’s about elevating creative capacity.

The challenges: Ethics, quality and ownership

Despite the benefits, challenges remain. While the quality of AI-generated images continues to improve, it’s still not foolproof. Inconsistent outputs and visual errors are common when user prompts are vague or too complex.

There are also growing concerns around misinformation and ethical misuse, particularly in the realm of deepfakes and identity rights. Legal questions persist around copyright and image ownership. Until clear frameworks emerge, marketers must proceed with caution and ensure they’re using images responsibly and transparently.

Best AI image tools to use in 2025

Here are some of the top-performing tools currently being used by professionals:

• DALL·E 3 by OpenAI: Seamlessly integrated with ChatGPT, it enables conversational image creation with impressive coherence and creativity.
• Midjourney: A favourite among digital artists and designers for its stylistic control and consistently high-quality outputs.
• Adobe Firefly: Ideal for those already using Adobe tools, offering AI-powered image generation within Photoshop and Illustrator, plus multilingual support.
• PicWish: Focused on eCommerce and social content, this platform excels at background removal and AI art creation.
• DeepSeek Janus Pro: A powerful emerging model reportedly outperforming some established tools in image quality and prompt fidelity.

What the future holds

The next frontier for AI-generated visuals will focus on improved realism, accessibility, and integration. Expect to see:

• Seamless cross-channel content creation (image, video, 3D)
• Greater personalisation through better prompt handling
• Ethical standards and content authentication built into tools

For marketers in financial services and beyond, the message is clear:

If you’d like to know more contact The Dubs Agency we’d love to help.

The post AI image generation is reshaping visual content marketing appeared first on Financial Marketer.

For marketers and communication teams in finance, speed and clarity are everything. But when it comes to understanding financial reports—especially across borders—clarity is often hard to come by.

These documents are long, dense, and often riddled with industry-specific jargon and local regulatory nuances. Now add a second layer: language. If your team is reviewing a 40-page quarterly filing written in another language during a national holiday, good luck getting timely input. Your workflow stalls. Decisions are delayed. Opportunities slip.

It’s a familiar challenge—and not a small one.

Why this friction still exists

Despite years of digital transformation, many financial teams still struggle to quickly digest reports across geographies. The issue isn’t just language. It’s the sheer volume of data, the format of information, and the time it takes to translate, interpret, and extract key insights.

Some context:

• A Harvard Business Review study found that non-native English speakers in multinationals spend twice as long processing English-language reports as native speakers.
• McKinsey estimates that executives lose 20% of their time searching for internal information. Add a language gap, and that figure climbs.

This isn’t just a pain point. It’s a productivity drain.

Where AI tools come in

Artificial intelligence is beginning to turn this challenge on its head—transforming financial data into something far more accessible, in real-time.

1. From documents to decisions

Platforms like AiSK empower teams to transform unstructured content into structured knowledge bases and actionable insights. 

AiSK tackles this head-on. It automatically ingests lengthy, multilingual documents—think earnings reports, board minutes, regulatory filings—and transforms them into a searchable knowledge base. 

• Translates and summarizes dense materials in your team’s preferred language
• Tags and categorizes content for easy search and retrieval
• Highlights actionable insights, deadlines, and risks
• Syncs updates across teams so no one’s left behind

No more waiting for manual summaries or delayed input from regional teams. With AiSK, insights are instant—and decisions move at the speed of your ambition.

2. AI-Powered translation & dubbing

All of your financial reports in document or video formats in foreign languages can now be automatically translated and dubbed, bringing real-time understanding to global stakeholders without the need for human translators.

3. Smarter knowledge management

Unlike traditional knowledge management (KM) or learning management systems (LMS), tools like AiM leverage semantic search and summarization across various content formats. Instead of relying on simple keyword matching, they pinpoint the exact paragraph, timestamp, or phrase you’re searching for—even across different languages and media types, including documents and videos. Companies use these tools to enhance internal training and knowledge sharing, ultimately driving greater productivity.

From information to insight – faster

What sets AI-powered tools apart is not just automation—it’s contextual understanding.

With AI, these platforms do more than summarise. They interpret. They connect dots. They allow global teams to ask questions, receive relevant answers, and make data-informed decisions—without waiting on emails, translations, or workday overlaps.

What this means for financial marketers

For those leading content, communications, and martech in financial services, AI video and language tools aren’t just efficiency plays. They’re about speed-to-insight, localization at scale, and greater independence from siloed workflows.

No more waiting for post-holiday translations or deciphering complex documents on your own. With AI, you don’t just access information—you understand it instantly.

If you enjoyed this article and would like to know more contact The Dubs Agency we’d love to help.

[**Full disclosure: The views and opinion expressed in this publication are those of the author. They do not reflect the views or opinions of any organisation or entity.]

The post Why translating and understanding financial reports is still a pain—and how AI can help appeared first on Financial Marketer.

Financial marketers at global banks and asset managers face a daunting challenge: delivering high-quality content in each region’s language without ballooning costs or timelines. Audiences across Europe expect market outlooks, fund updates, and regulatory notices in their native tongue, delivered promptly. Traditionally, meeting this demand meant lengthy workflows and expensive translation budgets. Now, artificial intelligence (AI) is emerging as a game-changer. One major asset manager, for example, cut translation times by 80% using AI-driven localisation. This article explores how AI enables scalable, cost-effective regional content delivery in financial services, with examples from Schroders and Allianz Global Investors.

The need for localised content in finance marketing

In finance, content only resonates if the audience understands it – meaning firms must present everything from quarterly outlooks to fund fact sheets in the client’s own language. For UK and European marketers, that often entails producing materials in multiple languages simultaneously. Historically, doing this for every update was slow and costly, leading to inconsistencies and delays across regions. With pressure to achieve more with less, many teams now ask: Can AI speed up multilingual content delivery without sacrificing quality?

How AI is enabling scalable localisation

Neural machine translation engines (from providers like DeepL or Google) can convert text into dozens of languages with impressive accuracy. This makes it possible to take a single English market commentary and generate French, German or Italian versions in minutes instead of weeks. AI-driven translation has become a “powerful accelerator” for global campaigns, handling volumes that would overwhelm human teams.

Importantly, AI augments rather than replaces human expertise. Many organisations use a “machine-translate then human-edit” workflow: the AI produces a draft, and local experts quickly refine it. This yields fast turnarounds without losing nuance or compliance oversight. Schroders exemplifies this – its team automates initial translations and then reviews for accuracy. As one marketing lead put it, translations were an obvious target since

“ we spend so much money with translation agencies who in turn use AI tools as well – so why not bring the AI in-house?”

Real-world examples of AI localisation

Schroders stands out as an early adopter. The UK asset manager built an internal AI assistant called “Genie” to help employees with content tasks, including translation. By keeping the tool internal, Schroders overcame compliance concerns. The result: Schroders can now localise materials for its dozens of regional websites much faster than before. Its in-house system handles up to 28 languages and has slashed turnaround times – achieving around an 80% time reduction on some projects.

Allianz Global Investors likewise turned to AI to streamline content production. Allianz’s marketing team used an AI-driven captioning platform to generate multilingual subtitles for videos, making global webinars and interviews accessible in local languages eight times faster than manual processes.

Other players like BNP Paribas are reportedly exploring similar AI localisation strategies, integrating machine translation into their workflows – although specifics remain mostly internal.

Overcoming challenges in cost, speed and compliance

AI’s appeal lies in how it tackles the classic pain points of localisation:

• Cost efficiency: Automating translations with AI cuts down on pricey outsourcing. Once an AI system is in place, the cost to translate each additional document is far lower than using human-only resources.
• Scalability: A lean team can manage dozens of languages with AI doing the heavy lifting. Even a small staff can launch content in all markets at once, so no region waits for updates.
• Speed to market: What once took weeks can now take hours. Faster translation means faster publication – critical for time-sensitive market insights. For example, Allianz saw an 8× faster turnaround on video subtitles with AI.
• Compliance & consistency: AI can be trained on approved terminology and disclosure language to maintain accuracy across locales. Secure, on-premise solutions also keep sensitive data in-house.

“ The major gain to date is to have secured the translation process globally and significantly reduced the risk of confidential data leaks”

notes Laurent Rochat of private bank Lombard Odier. Human reviewers still check cultural and legal nuances that AI might miss.

Conclusion: A new era of efficient localisation

AI is ushering in a new era of efficiency for financial marketing localisation. Instead of choosing between scale and quality, teams can now achieve both – delivering multi-language content faster and at lower cost. Early adopters like Schroders show that, with the right safeguards, AI can expedite multilingual content production without compromising compliance or brand integrity. As these tools become standard, firms that embrace AI-driven localisation will gain an edge in engaging clients in every region in their own language.

If you’d like to know more contact The Dubs Agency we’d love to help.

The post AI-powered localisation: Scaling regional content for financial marketers appeared first on Financial Marketer.