How data analytics is being used to simplify consumers’ personal finances


by AnalyticsInsight
November 19, 2021

The need for data analysis to offer personalized financing to consumers

Personal finances are complicated. There are many moving parts and it is virtually impossible to capture everything someone needs to know without consulting a financial professional. But in the digital age, data analytics make it possible for companies to simplify consumers’ personal finances in a big way.

How data analytics is used in personal finance

The concept of data analytics is simple: companies take large sets of data, analyze it, and turn it into meaningful, easily digestible patterns. These patterns are then used to inform new product design, anticipate customer preferences, and increase profitability.

In the personal finance space, powerful data-driven decision-making tools are being introduced at every stage of the product decision cycle, from initial product comparisons to delivering personalized offers and maintaining customer engagement. long-term. Here are three ways we’re seeing data analytics being 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 are still unsure how to build an investment portfolio that takes into account their risk aversion. Companies are looking to change that by leveraging data analytics to create data-driven portfolios based on investors’ risk tolerance.

An app like Acorns allows clients to press a button to indicate their risk tolerance, from conservative to aggressive. The app then takes that input and automatically decides on a set of investments and invests in those funds. This creates a perfect investment option for consumers who don’t have the time, energy, or knowledge to build their own portfolio.

AI-based recommendation tools lead to smarter decision making

Years ago, someone looking for debt consolidation loans may have sat down with their financial advisor or bank to discuss options. Today, tools like Credello’s AI-based debt consolidation recommendation engine cut out the middleman. Instead, they leverage an advanced algorithm that takes basic information and user goals and produces a personalized list of solutions.

The beauty of a simple platform experience like this is that it presents users with debt consolidation recommendations that are easy to understand and easy to follow. And that means customers are more likely to take out a loan that helps them improve their financial situation.

Personalized offers increase conversion rates

Personal finance companies can now take a customer-centric approach to their marketing, onboarding, and retention strategies. And in an age where customers expect top-notch service, it’s more important than ever for businesses to offer personalized offers.

Data analytics presents opportunities to target individuals based on their search patterns, spending patterns, and even their geographic location. For example, a person doing several searches a day about buying new homes is an opportunity to receive a specific email about low-interest mortgages. Someone who has spent twice their regular monthly budget on home improvement may be an opportunity to submit notices on personal loans for home improvement projects.

These personalized offers can help attract more customers and retain existing customers by offering them things they may already be considering.

The bottom line

Personal finances remain personal. But data analytics enables companies to offer customers customized solutions at scale. Data-driven portfolios, AI-powered 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 further simplify personal finance in the years to come as companies find new and creative ways to use it.

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Analytics Insight is an influential platform dedicated to insights, trends, and opinions from the world of data-driven technologies. It monitors the developments, recognition, and achievements of AI, big data, and analytics companies around the world.

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