by Analytics Insight
November 19, 2021
The need for data analytics to deliver personalized financing to consumers
Personal finances are complicated. There are many moving parts, and it’s virtually impossible to grasp everything someone needs to know without consulting a financial professional. But in the digital age, data analytics allows businesses to dramatically simplify consumers’ personal finances.
How data analytics is used in personal finance
The concept of data analysis is simple: companies take large sets of data, analyze it, and turn it into meaningful, easy-to-digest models. These models are then used to inform the design of new products, anticipate customer preferences and increase profitability.
In personal finance, powerful data-driven decision-making tools are introduced at every stage of the product decision cycle, from initial product comparisons to providing personalized offers and long-term customer loyalty. term. Here are three ways we see data analytics used in the personal finance market to simplify the process for consumers.
Data-driven portfolios simplify investing
These days, the opportunity to invest is literally in the palm of your hand. But many consumers still don’t know how to create an investment portfolio that takes their risk aversion into account. Companies are looking to change this by leveraging data analytics to build data-driven portfolios based on investors’ risk tolerance.
An app like Acorns allows customers to push a button to indicate their tolerance for risk, from conservative to aggressive. Then the app takes this input and automatically decides on a series of investments and invests in these funds. This creates a transparent investment option for consumers who don’t have the time, energy or know-how to build their own portfolio.
AI-powered recommendation tools lead to smarter decision-making
Years ago, someone interested in debt consolidation loans may have sat down with their financial advisor or bank to discuss options. Today, tools like Credello’s AI-powered debt consolidation recommendation engine are cutting out the middleman. Instead, they exploit an advanced algorithm that takes into account basic information and user goals and produces a list of tailor-made solutions.
The beauty of a simple platform experience like this is that it presents users with debt consolidation recommendations that are both easy to understand and easy to apply. And that means a greater likelihood that customers will take out a loan that will help them improve their financial situation.
Personalized offers increase conversion rates
Personal finance companies can now take a client-centric approach to their marketing, onboarding and retention strategies. And in an age where customers expect top-notch service, it’s more critical than ever for businesses to deliver personalized offers.
Data analytics offers opportunities to target individuals based on their search patterns, spending habits, and even geolocation. For example, someone who searches multiple times a day about buying new homes gets an email targeted at low rate mortgages. Someone who has spent double their monthly home improvement budget may be an opportunity to send out personal loan notifications for home improvement projects.
These personalized offers can help attract more customers and retain existing customers by offering them things they might already be considering.
The bottom line
Personal finances remain personal. But data analytics enables companies to deliver customized solutions to their customers at scale. Data-driven portfolios, AI-driven recommendation tools, and personalized offers are just a few of the ways companies are leveraging data insights to create customer value. Expect to see data analytics simplify personal finance even further in the years to come, as businesses find new and creative ways to use it.
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