Published by Wanda Rich
Posted on January 29, 2024
5 min readLast updated: January 31, 2026
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By Solomon Lax, Chief Executive Officer at Revenued
Over the past decade, financial comparison sites such as Bankrate, the Points Guy, and NerdWallet have become the go-to platforms for small businesses seeking information about banking products and financial services. Simultaneously, these sites have taken advantage of Search Engine Optimization (SEO) strategies and played a pivotal role in shaping SEO and search behaviors. The breadth of content generation has influenced search engine algorithms, guiding them to prioritize and reward platforms that deliver the most information. The symbiotic relationship between financial comparison sites and search engines has contributed to the perpetuation of their dominance in online searches related to banking and financial products. And their dominance makes it easy to lose sight of how generic and devoid of nuance the information presented on the platforms tends to be.
But the SEO trap is ending. Today, we are in a narrow window where artificial intelligence (AI) is revolutionizing search, and the banking industry has an opportunity to not only help shape this significant transformation but leverage this technology. AI’s potential in guiding small businesses toward the most suitable banking partners is shifting the competitive landscape, breaking the cycle of SEO-driven one-size-fits-all solutions, and creating new opportunities for banks. This piece will first describe the ongoing competitive landscape shift, facilitated by AI tools, that will challenge traditional comparison sites and will outline strategic approaches banks must leverage in this critical window of technological advancement to achieve direct access to potential customers.
AI’s ability to offer customized recommendations resides in its capability to analyze vast amounts of data, including traditional sources like banking products, interest rates, fees, and customer service ratings, as well as untapped data sources, such as customer banking data. With the ability to analyze specific business needs and deliver better recommendations, AI platforms shift the competitive landscape away from filter and content-based sites, which primarily focus on presenting commentary and data without extensive customized insights.
The content-driven nature of traditional financial sites, which are geared toward maximizing clicks and advertising revenue, may compromise the depth and accuracy of the information provided. AI’s entrance introduces a new paradigm where the value of generic SEO-optimized content is devalued.
Product comparison can and should provide more than a broad catalog for banks to present rates and fees. When powered by AI, product comparisons are capable of predictive analysis and tailored advice. We can now answer complex questions that simpler matrix-based filters, using one or two criteria like APR or rewards, can’t address. For example, with access to a small business’s bank account, bank fees can be analyzed and compared to alternatives. Then, their seasonal cash flows can be compared to their industry peers and suggest lending products. The AI-driven approach provides a more nuanced understanding of a small business’s unique needs, transforming how they choose their banking partners.
Amid this transition, banks find themselves at a critical juncture. Banks must employ the following strategies to successfully capitalize on AI-powered decision-making and its potential for great growth.
As AI reshapes the landscape of banking advice for small businesses, banks must adapt to stay relevant. Banks should be aware that the window of opportunity to take advantage of this transformation is limited. Banks currently own customer data necessary for the development of AI models behind a data wall. This will soon change with open banking. Once open banking begins, a bank’s customer data will be more broadly available, and competition for current customers, powered by customized offerings, will only increase. Banks should invest in AI and data analytics now, forge strategic partnerships that can leverage their current data responsibly, and focus on customized offerings before the offerings of the next fintech firm lure their customers.
Solomon Lax
About Solomon Lax:
Solomon Lax serves as the Chief Executive Officer at Revenued – a leading fintech that offers a small business card and Flexline based on machine learning scoring that is based on small business cash flow independent of FICO. Revenued also publishes a small business weather report with cash flow analysis and relative bank fee information derived from a panel of over ten thousand small businesses. Follow him on LinkedIn for strategic insights on fintech, credit cards, and small business financing.
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. AI can analyze data and provide insights for decision-making.
A financial comparison site is an online platform that allows users to compare various financial products, such as loans, credit cards, and bank accounts, to find the best options for their needs.
Data analytics involves examining data sets to draw conclusions about the information they contain. It helps businesses make informed decisions based on data-driven insights.
Customer data refers to information collected from customers, including their preferences, behaviors, and transaction history, which can be used to improve services and marketing strategies.
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