How Behavioral Science Gives Bankers an Edge Acquiring Customers

A consumer’s behavior is about much more than their social media presence, their digital banking activity, or even their banking product profile. A Financial Brand Forum legend talks where banks and credit unions go wrong with customer behavior — and why.

The “social proof” theory is simple: When people don’t know what to do, what decision to make, or which direction to run, they look at what people around them are doing. The pandemic offered a powerful example of social proof in action.

“Everyone was running out to buy toilet paper. And you know what, we all went out and we bought toilet paper,” says Nancy Harhut, Co-Founder of HBT Marketing. “We were hoarding toilet paper! If people wore masks, we wore masks. If people didn’t wear a mask, we would maybe be more inclined to not wear a mask.”

Though the context of that behavior was the pandemic, the cause can be explained by behavioral science (the social proof theory) and Harhut says that’s highly relevant in banking.

In a way, behavioral science is a common discussion topic in banking: When are customers buying homes? What season do people look for new cars, and are they therefore more likely to need an auto loan? How can we design a fall marketing campaign for new checking accounts that will resonate with students entering college?

But, while those questions address customer habits, they don’t get to the root of customer behavior. They don’t ask what intrigues customers because they don’t address the emotionality of banking products.

Asking such root questions is so effective, says Harhut, that leaders should integrate behavioral science into banking strategy, especially if financial institutions want to keep up in a digital landscape.

“There are companies now that have Chief Behavioral Science Officers,” Harhut explains. “Marketers are all about human behavior, about influencing behavior. Behavioral science allows you to do that, so why wouldn’t you want a C-level person at the table?”

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.