Using the newest technologies, providing clients with personalized suggestions has quickly become standard practice in the retail sector.

But thus far, it has been difficult to supply consumers with suggestions that are as individually tailored, especially for legacy financial services firms.

This is the reason why many financial institutions (FIs) are still mostly unaware of recommendation methods, according to Harry Hanson-Smith, VP of Sales at Dynamic Yield by Mastercard.

Why FIs need to use suggestions wisely
Financial product decision-making has become more complicated as the financial industry expands and consumers turn more and more to digital banking services.

As a result, there is a lot of room for customization and ongoing improvement when making suggestions. According to Hanson-Smith, recommendations may be made for more than only goods.

He claims that financial advisors (FIs) may use suggestions to give clients insightful financial guidance, individualized content, and instructional materials so they can make well-informed decisions regarding their financial health.

But a lot of financial institutions haven't been able to successfully use personalization to promote learning and exploration.

"FIs can adopt a similar approach to offer personalised, relevant, and seamless customer engagement through product and resource recommendations based on user behaviour, where eCommerce has the 'guided selling' concept that helps users discover products."

The financial services industry is dynamic, and as a result of new technology developments, client tastes are also changing. As a result, recommendation systems need to be flexible enough to adjust to these rapid changes in the market.

Hanson-Smith continues, "Recommendations may be a potent weapon to set FIs apart from their rivals as emerging fintech businesses are changing the way FIs interact with their clients.

"FIs can deliver highly personalized recommendations that truly resonate by leveraging machine learning and data analytics to unlock deeper insights into financial goals and behaviors."

How to pick an appropriate recommendation system

Hanson-Smith lists the following criteria to take into account while determining the best recommendations approach for financial institutions (FIs):

Objectives: Establish key performance indicators (KPIs) for personalization initiatives, such clicks to open accounts, application launches, and downloads of mobile apps. The selection of recommendation tactics and where to display them on digital platforms are determined by these objectives.

Audiences: Divide the audience into four main divisions, with an emphasis on three or four based on engagement level, customer lifecycle stage, or product accomplishment. The specific recommendations that are given to each section are determined by their own needs.

Data feed: To properly power suggestions, a well-structured data source is necessary. Recommendations are guaranteed to be pertinent and useful when metadata is properly tagged according to product categories, characteristics, customer status, and engagement levels.

Choose recommendation tactics based on the preferences and different user segments. These tactics could include making product recommendations based on the user's preferences, recently seen products, comparable options, or often viewed products together. Customize these suggestions to fit particular user types and improve their experience in general.

On-page location: The importance of recommendations changes according to the page on a FI's website. Recommendations on the homepage, blog pages, and account summary pages are more successful when they are customized to the expectations and purpose of users.

EXAMPLES OF RECOMMENDATIONS IN FINANCIAL SERVICES INCLUDE:
 • Chatbot recommendations
 • Article recommendations
 • Improved customer acquisition and lifetime value recommendations

Considering data governance

In fact, FIs need to give data governance and data quality a priority if they want to fully realize the potential of recommendations.

According to Hanson-Smith, "A strong framework for data governance guarantees that customer data is correct, safe, and complies with legal requirements." Additionally, it makes it possible for financial institutions to efficiently handle data from a variety of sources, such as transactional, customer, and behavioral data.

Furthermore, data governance is essential to preserving consumer confidence. Consumers' worries around the security and privacy of their financial information are growing.

"FIs can gain credibility and trust from their customers by showcasing a dedication to safeguarding customer data through robust data governance procedures."

The advantages of more customization
It's evident that, when applied skillfully, suggestions have enormous potential in the financial services sector.

"The above framework can enable FIs to follow a path to greater personalization, improved customer engagement, and enhanced business metrics," writes Hanson-Smith in her conclusion.

"FIs can harness the power of personalization in the digital age, adjust to shifting industry dynamics, and establish themselves as trusted advisors in their customers' financial journeys by adopting recommendation strategies catered to their specific needs."