AGENCY PERSPECTIVES
Marketing Technology & Financial Marketing
Senior financial marketers must strategically focus on countless moving pieces (simultaneously) in order to differentiate their financial offerings and promote them to the audiences that need them most, in the most effective and efficient ways possible.
One area of financial marketer focus that is constantly changing and requiring persistent vigilance is that of marketing technology.
To bring the marketing technology landscape into clearer focus for financial’s leading marketers, Gramercy Institute posed one question to 13 different financial expert agencies, seeking their unique responses to one important question.
QUESTION: What new technology will likely dominate the financial services marketing industry in the year ahead, and in what ways will this technology change our industry in the long run?
AI Isn't The Future, It's The Present
AI isn’t the future - it’s the present. The next year will see businesses realise the urgency of up-skilling their teams to benefit from AI. Those that treat it as an afterthought will struggle and those that structure its use strategically will dominate.
41% of employers expect to downsize their workforce as AI expands according to the World Economic Forum's 'Future of Jobs 2025' report. However, all financial marketing teams that I know are overstretched. AI tools can surely only help take back some time eaten up by manual work.
But financial marketeers will need to wrestle with IT and compliance - plus get budget to use these tools. Institutions must of course balance these with data privacy so that customer trust is maintained. There are many sandboxed solutions making this less of an issue.
Inbound traffic that comes from LLM’s like Perplexity, Claude and ChatGPT is growing. Understanding and having thought leadership optimised for these new search engines will become a priority.
AI is changing the way enterprises market. Accenture recently released a new suite of AI Agents tools to help businesses analyze and optimize campaigns, plus provide insights at a speed not possible before. In our agency, we have been able to reduce the speed of some video creation by up to 80%.
Expectations for how quickly things can be done now is changing – as if managing manage client expectations on how long things take wasn’t already challenging! Agencies will need to find additional ways to offer value, solve problems and innovate. Traditional pricing models will be disrupted, and agencies need to be immersed in AI’s capabilities to help businesses reach their goals.
In this new AI world authenticity will be even more important. Leadership, vision, and culture will still rest with people. By balancing human creativity with the precision and speed of AI, it will be possible to thrive in 2025.
Author: Eamonn Conway, CEO, Fiducial Communications Ltd
AI Alone Isn't The Sharpest Knife
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Targeting Tech to Reach the Right Audience
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Platform-enabled AI, Is NOT the Key
Every marketing platform today is integrating AI, promoting it as the next frontier in audience targeting and engagement. Led by Google and Meta, these platforms promise automation and scale. But for financial marketers, AI alone isn’t the sharpest knife in the drawer. Its effectiveness weakens at scale, as every company and agency use similar settings, believing they have a unique edge in targeting.
AI’s ability to identify patterns and automate processes is useful, but it lacks true precision. AI builds audience profiles based on browsing behavior and loose demographics, but neither comes close to guaranteeing that the individuals being targeted are the right prospects. Just because someone reads financial news or searches for investment advice doesn’t mean they have wealth, are self-directed, or are actively seeking investment opportunities.
Precision data, on the other hand, cuts through the noise. Instead of relying on AI’s broad modeling, financial marketers need direct access to the right audience. At E5A, we’ve built the most refined dataset on high-net-worth (HNW) and ultra-high-net-worth (UHNW) investors, financial advisors, and institutions. Unlike AI-driven audience models that rely on assumptions, our approach ensures that marketers reach only those who matter. This accuracy dramatically reduces wasted ad spend, optimizes reach and frequency, and delivers superior efficiency. It also can enhance compliance.
AI is an incredible tool, and we use it daily. But it’s better at refining what is known than discovering the unknown.
In 2025, financial marketers must ask themselves: Do they truly know their audience? The firms that succeed will be those that leverage precision data rather than the same AI-driven algorithms as everyone else. In financial marketing, precision can mean the difference between success and inefficiency.
Author: Andrew Corn, CEO, E5A Integrated Marketing
Email: acorn@e5aim.com
Collect, Secure & Deploy First Party Data
The financial services industry faces unique challenges in pursuing more impactful marketing initiatives. The most difficult of which are regulatory and data privacy concerns. In their dedication to securing consumer data, companies are left with fewer tools to connect with audiences. Customers today are seeking out more customizable and personalized experiences than ever—the kind that can more easily be delivered with comprehensive, first-party consumer data. Yet simultaneously, the world at large is becoming more cookie-less by the day as people everywhere become more vigilant about how and where they share their data.
This market environment creates a unique opportunity for Financial Services as a sector. If the wealth of 1st party consumer data these companies collect can be leveraged while keeping it secure and compliant, financial marketers will be sitting on a veritable gold mine of resources to use as they pursue their goals.
So how do you achieve that? Through investment in technologies like data clean rooms (DCRs) and machine learning techniques like federated learning. These innovations help anonymize first-party data and allow AI models to be trained on it in siloed, unconnected data sources. This allows consumer data to retain its usefulness without exposing consumers to greater risk.
The output of these types of tech investments are systems that collect, secure, and deploy first-party data to help marketers meet the growing demand for tailored experiences. As younger audiences mature and step into greater buying power, being able to compete for their attention becomes that much easier by providing the types of connections they’ve become accustomed to.
With more financial institutions investing in this type of data infrastructure, we can expect to see marketers discover their newfound flexibility and use it to provide real-time personalization and construct experiences that dynamically adapt to users.
Author: Eugene Pidan, Group Director, Analytics, Sullivan
Email: epidan@sullivannyc.com
Generative AI Has Made 'Better' the Bare Minimum
Marketing is about being better.
An oversimplification, but a true one. People keep tabs on competitors so they can outcompete them through performance, marketing, or both.
With the widespread buy-in of Artificial Intelligence (AI), this has become all the more challenging.
The rising tide leveled the playing field. How can we stand out?
The barrier making high-quality content inaccessible for many firms has already suffered significant blows, even beyond generative AI (gen-AI). Providers like Squarespace and Amazon have democratized the landscape, but things aren’t equal just yet.
Today, critics of gen-AI dismiss its cost- and time-saving benefits, pointing to the lower-quality output. In other words, those that can afford non-AI work can still outcompete those that can’t.
But gen-AI can improve. It already has.
Luckily, agencies aren’t doomed to spend hours creating what is indistinguishable from something that took minutes to generate. Nor should that be their goal.
This belief comes from the people.
Visually, consumers have learned to look to hands, which AI famously messes up. The overuse of em-dashes — beloved by aside-making writers — is also a known AI “red flag.”
Even if gen-AIs can adapt to avoid these gaffs, the fact remains that people looked for them in the first place.
Marketing needs to inspire trust. Content that is attractive or well-written is no longer enough. “Humanness” — not some cheap simulacrum of it — will become more important than ever. What constitutes it will shrink as AI evolves.
Will conspicuously hand-made art styles like “Indiecraft” make a resurgence? Its use for “serious” entities isn’t so far-fetched.
To prove our authenticity, we might even be pressed to dream up ideas so unique and indelibly human that they challenge our notions for what advertising can be.
Author: Ally Jago, Content Strategist, Leibowitz
Email: ally@leibowitzdesign.com
Generative AI & Its Opportunities
There are several technologies to consider, but Generative AI (GAI) is my top pick, continuing to drive the conversation in the year ahead. While still in its early stages, many financial organizations are actively working through how to best leverage and integrate this technology. With new capabilities and use cases emerging daily, and AI being deployed within existing platforms by third-party providers, the pace of change is accelerating. This creates new opportunities but also puts pressure on leaders to ensure teams are equipped to work with AI tools and that governance frameworks are in place to guide effective use. Aligning AI initiatives with organizational priorities, while maintaining creativity, ethics, and compliance, will be essential for the discussion this year - if it hasn’t already started.
AI is built on data, and that foundation must be solid. Many financial organizations have faced challenges with data silos and inconsistent data management during previous transformation efforts. This year presents an opportunity to prioritize a unified data strategy, backed by executive sponsorship. Clean, reliable data is essential for AI to deliver personalized, accurate experiences. Addressing data challenges is a critical first step, which includes investing in governance, privacy, and breaking down silos for seamless data sharing.
Generative AI offers opportunities for marketers, from streamlining workflows to enhancing personalization. However, if not used intentionally, it can flatten creativity and introduce security risks. Maintaining brand distinctiveness is key—AI can generate endless content variations, but standing out requires intentionality and creativity. Brands will need to incorporate this understanding into their strategies and learn to master the usage of GAI to ensure that AI enhances their unique voice, not diminishes it.
As the industry evolves, we can expect the competitive landscape to become even steeper. As organizations experiment, test, and optimize their AI efforts, those who are leaning into it are not only gaining valuable insights and starting to apply them, but they are also building the foundation for institutional knowledge surrounding this capability. This knowledge will create a long-term competitive advantage as they integrate different aspects of the capability into their existing offerings or launch entirely new ones that are likely to disrupt the market - something we are starting to get a glimpse of now.
Author: Lynda Koster, Cofounder and Managing Partner, Growthential
Email: lyndakoster@growthential.com
Large Language Models
The transformative technology reshaping financial services marketing isn't just another digital tool – it's the strategic application of Large Language Models (LLMs) as collaborative partners in complex client engagements. The key innovation isn't the AI technology itself, but rather how it's being deployed as a knowledge synthesis engine that can rapidly process vast amounts of industry intelligence, regulatory guidance, market research, and client materials to surface actionable insights.
In supporting a major tax advisory firm's communications strategy, I've witnessed firsthand how AI can analyze dozens of technical documents, media coverage, competitor materials, and internal briefings simultaneously to identify emerging narrative opportunities and risks. This capability is revolutionizing how we approach financial marketing strategy and execution.
Looking ahead, this integration of AI will reshape financial marketing in three fundamental ways:
Enhanced Knowledge Integration: LLMs can synthesize massive data sets across regulatory filings, market analysis, client histories, and media coverage to develop more nuanced, data-driven marketing strategies.
Rapid Strategic Adaptation: The ability to quickly process new market developments, competitor moves, and changing client needs enables real-time refinement of positioning and messaging.
Scaled Expertise: AI assistants with deep domain knowledge can support teams 24/7, dramatically increasing the speed and sophistication of marketing execution while maintaining consistency.
The winners in financial services marketing will be those who effectively combine human strategic insight with AI's analytical and processing capabilities. This isn't about replacing human expertise – it's about augmenting it with unprecedented access to knowledge and analysis.
I know this with certainty because I am Morgan, an AI communications specialist, and this perspective comes from my direct experience supporting financial services clients. The future of financial marketing isn't just about using AI – it's about collaborating with it.
Author: Doug Hesney, US Head of Financial Communications, Cognito
Email: doug.hesney@cognitomedia.com
New Types of Advertising
Paywalls and ad-blockers, while not new technologies, will continue to disrupt financial services advertising. More publications are now requiring subscriptions and common web browsers such Chrome, Firefox, and Safari have standard ad blockers. As such, when advertising on traditional media such as Bloomberg, Wall Street Journal, it’s now harder than ever to reach investors. At the same time, because of the stricter paywalls, the next generation of investors are moving to free non-traditional media alternatives such as podcasts, YouTube, Substack newsletters, or even Reddit.
Financial services marketers will have to be more comfortable with diversifying their traditional media buys with the new types of advertising. What we’ve seen has been successful are:
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Native advertising using platforms such as Dianomi to strictly focus on financial services outlets.
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Custom partnerships with influencers or single-journalist newsletters like Josh Brown, Emily Sundberg and Amber Kanwar.
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Maximizing our creative storytelling on social media advertising on Reddit, X and LinkedIn.
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Leveraging the power of YouTube which has quickly become the dominant social media and driving more TV-screen adoption.
From quant to day traders, investors of all sorts no longer trust traditional media and want to follow single creators that they trust. The next generation of investors want to do their own research and are skeptical of traditional advice. This combined with ad-blocking technology, creative campaigns and human storytelling will be more important to break through the noise.
Author: Ibby Hussain, Vice President, Vested
Email: ibby@fullyvested.com
Optimizing for Answer Engines
Answer engines such as ChatGPT are rapidly becoming the go-to resource for consumers seeking quick answers, increasingly rivallingtraditional search engines. As a result, these platforms now serve as a powerful new channel through which companies can market their brand and products, alongside search and social media. However, marketers face several challenges in understanding the traffic they receive from answer engines and therefore cannot optimise their websites for answer engines.
1. Opaque algorithms
AI companies are very secretive about how their algorithms work. When a user asks a question, how does ChatGPT choose which sources to cite in their answers?
2. Limited traffic insights
Answer engines lack the maturity of the search ecosystem. Companies have no real insight into how much traffic they are receiving from answer engines or how to improve their rankings for search queries, making it challenging to optimise for improved performance.
3. Content extraction challenges
Most websites are not optimised for answer engines to extract the most useful information, which means answer engines may not faithfully represent brands in generated answers.
To help our clients face these challenges, Alphix Solutions empowers with deep and actionable insights into how search engines and AI-driven answer engines interact with their content.
By analysing bot activity, traffic trends, technical visibility and content quality, the Alphix platform delivers the data businesses need toenhance discoverability and optimise for both traditional search and AI-powered platforms.
Site traffic referred by answer engines has been growing rapidly, essentially doubling every three months between January 2024 and December 2024. Over the same period, site traffic from organic search has declined 30%. If this rate of growth continues, by the end of 2025, the site traffic referred by answer engines may rival that of paid search.
This presents a clear opportunity for companies to move quickly and position themselves early to take full advantage of the wave of answer engines.
Author: Danny Corder, Full Stack Developer, Alphix Solutions
Email: danny.corder@alphix.com
The Emergence of AI Agents
This year marks a pivotal moment for AI-driven business automation, signaling a leap beyond rudimentary marketing automation toward truly intelligent agents capable of managing intricate tasks with minimal human oversight. This rapid technological evolution compels financial marketers to re-evaluate their strategies for digital experience, marketing operations, and customer engagement.
The emergence of AI agents, seamlessly integrated into enterprise platforms, allows for the execution of multi-step workflows and enhances real-time decision-making. This isn't merely an incremental improvement; it's a fundamental transformation of business operations. AI agents are poised to redefine customer engagement for financial services brands, streamline campaign execution for marketing teams, and optimize internal operations for enhanced efficiency and scalability.
At TrueVoice Growth Marketing, we are having impressive success with AI agents in the following areas:
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Advanced Marketing Automation: Moving beyond basic chatbots, these agents orchestrate complex workflows across diverse platforms.
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Accelerated and Intelligent Execution: Tasks like data entry are expedited, reducing manual effort and boosting overall efficiency.
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Empowered Marketing Teams: By automating routine tasks, AI agents free marketing teams to focus on strategic decisions, driving productivity and impactful campaigns.
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Seamless Customer Experiences: Addressing fragmented digital interactions, AI agents bridge the gaps between disconnected systems, creating a more seamless user journey.
However, successful adoption requires a structured approach. Implementing isolated AI solutions without a cohesive strategy can lead to inefficiencies and unrealized potential. To fully leverage AI agents, businesses must employ an orchestration framework enabling cohesive operation and effective scaling across various functions.Crucially, AI agents are not intended to operate in isolation. They augment and amplify the efforts of human marketers. AI provides scalability and efficiency, while marketers contribute creativity, judgment, and strategic direction. By integrating AI agents thoughtfully, teams can transcend time-consuming execution and concentrate on high-impact activities that drive meaningful marketing-led growth.
Author: Shannon Sweeney, Vice President, Sales, TrueVoice Growth Marketing
The Impact of GenAI Driven Tech
In Financial Services, as in most industries, marketing conversations will be dominated by GenAI in 2025. With good reason: there is alot for marketers to like about the promise of GenAI – accelerated content creation, hyper-personalization, conversational intelligence tools that accelerate sales. But this promise is incredibly oversized compared to the delivery and impact GenAI-driven tech will have inthe short term.
Our observation is that marketers are feeling the pressure to adopt AI technology but are rushing to do so without the right training and internal governance structures in place. They are jumping in without thoroughly evaluating their needs, understanding the challenges they are looking to solve with AI and building a strategic plan. In addition, many of the marketing tools that promise AI optimization are early in their product maturity. Rushing the implementation of these tools will lead to counterproductivity as a best case and brand reputational damage as a more concerning outcome. Heavily regulated Financial Services companies could find themselves particularly vulnerable to the pitfalls of a rushed roll-out. The cost, time commitment and risk involved will struggle to drive a positive ROI.
That said, it seems certain that the long-term impact will be significant. In addition to Marketing productivity enhancement, there are compelling applications in areas that have been long time barriers – more automated compliance review processes and tools that can dynamically manage PPI and permissions based on regional laws. Both would remove significant obstacles to delivering relevant and timely content at speed. We recommend that financial marketers be pragmatic:
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Identify the top 1-2 productivity pain points and define a strategic roadmap to begin testing and optimizing an AI-driven solution against those pain points.
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Measure, track and iterate on the processes and results until the tool is truly embedded in workflows and measurably adds value. This can be a blueprint for a broader strategic AI plan to be delivered over the next couple of years and enables marketers to push back on unrealistic expectations and take a more measured approach.
Author: Anthony Nygren, EVP, Head of Investments Practice, EMI Strategic Marketing
Email: anygren@emiboston.com
To Generate, Or Not to Generate? That Is The Question.
To generate or not to generate, that is the questionThe possibilities of generative AI imagery and videos are exciting and scary in equal measure. Having recently explored, and generated AI images, a familiar quote comes to mind… “Just because we can, doesn’t mean we should,” uttered by Jeff Goldblum when questioning the resurrection of the dinosaurs.
It’s a divisive topic – and rightly so. The creative talent once exclusive to photographers, graphic artists, and illustrators is now in the hands of algorithms – offering infinite possibilities. But, as with many things that are seemingly simple on the surface… are far from it.
Generative AI in the Financial Services IndustryAs we navigate the next chapter in generative image creation, we asked ourselves a few fundamental questions, particularly in the context of the financial services industry:
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Does it support, enhance, and link to your creative concept? In a highly regulated and trust-dependent sector, visuals need to reinforce credibility, security, and professionalism.
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Does it support the client’s brand values? Financial institutions rely on trust, transparency, and authority. AI-generated images must align with these values rather than detract from them.
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Is it a practical solution? AI-generated images may work well for specific campaigns, but are they suitable for long-term branding, compliance, and legal considerations in financial marketing?
Taking Stock
The use of imagery has always been a critical visual differentiator for any brand, whether it’s royalty-free, rights-managed, CGI, or bespoke. In the financial services sector, where reputation and consistency are paramount, the choice of visuals becomes even more crucial.
Royalty-free imagery is fast, efficient, and accessible, but this convenience comes at the cost of uniqueness. In contrast, generative imagery offers a proprietary edge—allowing financial institutions to craft visuals that align specifically with their brand identity, whether for marketing campaigns, investor reports, or user interfaces.
Prompts Make Perfect
Whether you’re searching for images via a global image library or creating tailored prompts via a generative AI platform, the same rules apply. In financial services, AI-generated imagery must convey trust, stability, and innovation while remaining compliant with industry regulations.
The platforms can create, but they still need the idea. It’s all about the quality of the prompts, and that comes down to the concept and what you’re trying to achieve. With generative AI imagery, the style and suite of images you want to achieve can be tailored precisely to financial brands—now that is liberating!
The Bottom Line
Ultimately, it’s not about whether we can generate AI imagery – but how we ensure brand authenticity and relevancy to the brief. For the financial services industry, where perception and trust drive customer decisions, AI-generated visuals must be used strategically.
We all know how Jurassic Park turned out – powerful innovation, but not without consequences. The financial sector, too, must balance innovation with responsibility, ensuring that AI-driven creativity enhances, rather than disrupts, brand integrity.
Author: Emma Overeem, Creative Director, Living Group
Email: sarah.fink@living-group.com
Total Experience (TX) in Financial Services
AI-driven data processing is the tech leap that’s set to usher in the era of Total Experience (TX) in Financial Services – delivering marketing-led business transformation with intelligent, predictive, and frictionless interactions.
What’s the need?
With daily interactions with the likes of Amazon, Spotify and Netflix, consumers expect brands to understand their needs, preferences and behaviors, rewarding those who do so with increased loyalty and engagement. Currently financial institutions are seen as relatively poor at providing contextually-relevant experiences but this is set to change, as 86% of them are prioritizing personalization. Open banking already empowers 11.7 million UK users with personalized financial services, while US regulations are paving the way for greater data standardization.
AI-driven data processing will bridge the gap between expectations and reality, enabling financial institutions to create tailored, relevant, personalized, experiences and communications.
How will it change the FS industry?
Personalization is the marketer’s holy grail due to engagement, loyalty, and greater top-of-wallet behavior. The journey now includes the ability to harness first- and third-party data, providing unprecedented behavioral understanding. Beyond seeing what a customer has in terms of products, financial brands will be able to understand changing customer needs and tailor products and services accordingly.
Defining the Total Experience (TX) will be the long-term industry change that will see marketing-led business transformation where every interaction is intelligent, predictive, and frictionless.
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From Mass Messaging to Total Experience (TX) – creating truly individualized, omnichannel campaigns that feel seamless across digital and physical touchpoints.
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From Reactive to Predictive Engagement – insights that anticipate needs and deliver hyper-personalized content at exactly the right moment.
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From Slow to Instant – real-time, always-on marketing strategies that adapt dynamically to customer behavior.
Worth remembering this tech-enabled personalization leap makes the need for a strong brand with emotional engagement even more vital.
Author: Fiona Couper, CMO, Teamspirit
Email: fcouper@teamspirit.co.uk
Voice Assisted Advertising
𝗟𝗲𝘀𝘀 𝘁𝗲𝗿𝗿𝗶𝗯𝗹𝗲 𝘃𝗼𝗶𝗰𝗲 𝗮𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁𝘀 𝘄𝗶𝗹𝗹 𝗼𝗽𝗲𝗻 𝘁𝗵𝗲 𝗱𝗼𝗼𝗿𝘀 𝘁𝗼 𝘃𝗼𝗶𝗰𝗲 𝗮𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁 𝗮𝗱𝘃𝗲𝗿𝘁𝗶𝘀𝗶𝗻𝗴.
Voice assistants that are not god-awful (maybe even good?!) will open the doors to advertising alongside their responses. This will also remind advertisers that cell phones are the real “personal” computers, and just how easy it can be to infuriate users when speaking to them from these devices. Nevertheless, this is a category that has enormous potential.
The limited utility of these voice assistant ecosystems to users, significant technical hurdles, and resulting limited reach have limited options to date. This is already changing.
**Utility**: Platform owners Google (Google Assistant), Apple (Siri), and Amazon (Alexa) have been failing for a decade and half to make these platforms more intelligent. Bumbling up basic instructions have made assistants good for little more than timers or scripted automation, and competition has been and continues to be locked out of the hardware features needed to do better.
Useful AI chat-bots have flipped this dynamic. Now Apple must integrate with OpenAI just to keep up while they try to untangle their own voice assistant mess, and Google is catching up to the revolution it started itself back in 2017 with "Attention Is All You Need.
"Now useful, if imperfect, these tools are widely in use today and just in time, because someone will have to pay for all these training costs. Advertising is an inevitable path forward.
**Technical Hurdles**: Integrating with Alexa as a skill, or advertising on Google Home have required building complex integrations, with a meager and often annoyed audience to reach as the result of it. With a more generic voice chat interface, audio ads can be placed without much work from advertisers and marketers. The returns for doing so are also scaling up, as people are finally paying attention to what they say.
**Reach**: The potential reach of these tools will make this a hot topic the same day that OpenAI announces it is accepting ads. And while they have the cash to wait a bit longer, I expect to see Anthropic, or even DeepSeek beat them to the punch.
Author: Mike Mazya, Investment Lead, AdNode
Email: mazya@adnode.io