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Lead Generation for Banks and Insurance: AI at the Service of Financial Consultants

5 April 2022

Financial institutions have never fully used them, but thanks to new machine learning applications, their data can make banks and insurance companies the protagonists of highly successful communication campaigns.

Whether it’s traditional email campaigns, website or social media marketing campaigns, or even digital advertising or traditional media campaigns, it’s clear that the better banks and insurance companies know their customers, i.e., their audience, the more effective the campaign will be, resulting in additional revenues.

Based on this simple reasoning, one might think that the banking and insurance industry, which gathers a wealth of information about their customers due to regulatory and product requirements, would execute particularly high-performing campaigns.

Often, this is not the case.

A new, ever-evolving regulatory context

Only recently have financial and insurance companies started considering the immense potential their informational advantage can offer. With the rapid digital evolution of the industry, combined with the General Data Protection Regulation (GDPR) and the impending ban on (often unscrupulous) third-party cookies, financial companies can certainly become the driving force behind highly successful digital campaigns.

The Wealthype team, always focused on Data Analytics applications for the industry, along with Nirtya, a leading company in Data-Driven Marketing and sustainability, has developed a range of solutions aimed at increasing the competitiveness of the financial services industry in a constantly evolving context.

From First-Party Data to Financial Personas

Until now, financial companies have found it more convenient to rely on third-party data collection for advertising campaigns. Actually, without excessive burden, more targeted and effective campaigns can be created using their own customer knowledge.

First-Party Data, for example, refers to all the data owned by the financial intermediary. It includes online behavior data obtained from the website (and other web properties), demographic and contact data, MIFID and IDD data, as well as transaction data related to products and current accounts (also obtainable through “account aggregation” thanks to PSD2), and CRM data.

From here, using data analytics and Wealthype’s proprietary financial data enrichment tool, it is possible to reconstruct a large number of highly detailed and granular financial personas specific to the banking and insurance industry.

We use over a hundred of these financial personas, hierarchically aggregating them to a smaller number. These financial personas comprise a wealth of information (over a hundred different attributes) including income-related aspects, financial information, specific needs for insurance and financial products, ESG propensity or digital channel usage data, and lifestyle aspects.

Sharper Financial Personas through their Online Behavior

By listening to and analyzing online behaviors, we are able to increasingly refine our knowledge of financial personas. For example, our algorithms can attribute the five major personality factors (the so-called Big Five) to different segments. These factors, according to one of the most accredited theoretical approaches, define personality as the sum of five behavioral traits inferred from data.


Understanding psychological and behavioral aspects helps optimize service and marketing campaigns, and translates into the differentiation of creatives themselves.

Among the behaviors that can be tracked is sensitivity to sustainability issues. Through Nirtya’s proprietary algorithm, interests related to ESG can be analyzed and classified, enabling users to be clustered based on their knowledge and propensity for action.

Optimizing the Customer Journey and Performance through Content Personalization

The next step after creating rich clusters of information perfectly aligned with the banking and insurance context is personalizing the creatives. This includes both static and dynamic creatives tailored to the characteristics of different clusters. This allows for a highly personalized level of engagement that can be utilized in various activities.

  • Engagement on site: delivering tailored content on the page or in the mobile app based on behavior, without latency and without user perception.
  • Engagement on delivery: personalization of emails and marketing automation, delivering different messages based on propensity and affinity.
  • Ads optimization: targeted advertising purchases and lookalike activities.

This system follows a learning curve, with increasing results on different KPIs. The results derived from personalization become more impactful as user knowledge grows.

Using dynamic creatives that adapt to the user’s context, the impact on the business can be observed, starting from an initial level of campaign response, with an increased effectiveness of the campaigns themselves, leading to increased conversions and ultimately a positive effect on customers’ lifetime value by anticipating their needs with the most suitable proposals in their context.

Decentralizing a Portion of Digital Marketing to the Relationship Manager

Through a dedicated platform, a portion of digital marketing activities can be controlled directly by those who interact with the customers, such as financial consultants, private bankers, and insurance agents.

Essentially, the relationship manager can digitally engage the customer directly, leveraging storytelling paths and pre-existing personalized content designed for financial personas and made available on the platform. These can be easily and quickly combined, adding a touch of personalization while fully utilizing the wealth of upstream information obtained through advanced analytics.

In this way, a financial consultant or insurance agent can send “their” newsletter to their clients using a secure corporate framework in full compliance with GDPR.

The vertical approach for the financial sector and the level of detail in our profiling process make the solutions provided by Nirtya and Wealthype unique in the industry. It is the tool for significantly more performant campaigns. Today, we offer financial companies a design approach, and we will soon launch a tool that can “give a face to the data” automatically and quickly: the first automatic creator of financial personas.

Stay tech.

Wealthype & Nirtya

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If this topic intrigues you, contact us using the link below and discover how to apply Machine Learning principles to your business processes.

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