What is Personalized Finance?
Financial products and services are becoming increasingly commoditized and consumers are becoming more discerning as the media and retail industries have increased their penchant for personalized experiences. To remain competitive, banks have to offer an engaging banking experience that goes beyond traditional banking via personalized insights, recommendations, setting financial goals and reporting capabilities – all powered by advanced analytics like geospatial or natural language processing (NLP). Personalized finance, also known as open finance, is based on data-sharing principles that can empower banks to offer a broader range of possibilities to their clients that are suited specifically to their needs. Personalized finance is made possible through open banking (refer to next section) standards and evolving regulations across the world.
What does Personalized Finance look like in practice?
In today's on-demand culture, personalized finance means that customers want their banks, insurance carrier or wealth manager to meet them where they are—in the products and channels that they use. For example, real-time installment lending, also called Buy Now Pay Later (BNPL) is automatically added on to your retail shopping experience. Perhaps you've recently opened your banking app and noticed some new features to add accounts from other banks to help you monitor all your accounts at once, or you added your bank account to your investing app to see how much you can invest this month. These are examples of personalized finance that gives consumers more control over their financial well-being. Another example, Spanish bank BBVA's recent blog1 describes in detail how the bank "uses data science to identify the characteristics that define them (always with their prior consent) and therefore offer recommendations on how to manage their everyday finances, lower their debt, save or plan for the future."
Why is Personalized Finance important?
Customers want more choice, control and a seamless customer experience. Beyond their account or credit card balances, customers increasingly want access to information about their finances that can help them make more informed decisions about their money and financial goals. At the same time, they expect to be presented with personalized offers that best fit their investment posture and preferences.
> 72% of customers rate personalization as "Highly Important" in today's financial services landscape
> 60% of consumers say they are likely to become repeat buyers after a personalized shopping experience
For the financial services institution (FSI), personalized finance benefits are:
- Foster customer loyalty and retention by providing an enhanced customer experience that is targeted to their needs and behavior.
- Increase in engagement and conversion rates, resulting in a greater share of wallet/ higher customer lifetime value.
- Stronger marketing ROI through targeted marketing campaigns and consistent messaging across channels.
What are the challenges in implementing Personalized Finance?
Legacy Infrastructure. Legacy technologies can't harness insights from fast-growing unstructured and alternative data sets — and don't offer open data sharing capabilities to fuel collaboration.
Strict data and privacy regulations. A number of high profile instances of data theft and breaches have made many consumers more cautious about sharing their personal data.
Access to third party data. Vendor lock-in and disjointed tools hinder the ability to do real-time analytics that drives and democratizes smarter financial decisions.
Data silos. Highly complex workflows, disparate technologies, and spreadsheet-culture makes collaboration difficult and keeps data trapped in silos across multiple business units.
How does Databricks help financial institutions with Personalized Finance?
Databricks Lakehouse for Financial Services provides banking, insurance and capital markets companies with the ability to unify data and AI on an open and collaborative platform to deliver personalized customer experiences, minimize risk, and accelerate innovation. It eliminates the technical limitations of legacy systems, and enables FSIs to leverage all of their data to minimize risk while accelerating transformative innovation. It allows FSIs to aggregate different types of data — from market to alternative data — enabling hyper-personalized experiences that drive cross-selling opportunities, customer satisfaction and share of wallet. By unifying data and AI, FSIs are also able to simplify the complexity of regulatory reporting, risk management and compliance by securely streamlining the acquisition, processing and transmission of data to empower better data governance practices.