What Banks Must Know About AI and the Personal Financial Data Rights Rule

After years of slow momentum, open banking has gained its first significant regulation since GDPR. Introduced in October 2023 by the Consumer Financial Protection Bureau (CFPB), the Personal Financial Data Rights rule requires banks to make consumer data available in a structured and consistent way, enabling them to share it with other institutions offering better products and services.  Doing so creates an incredibly powerful data set for the financial institutions savvy enough to ingest it. 

How should banks prepare to thrive in the new era of open banking? Embracing AI and ML can help banks leverage this data set, paving the way for competitive pricing, expanded credit offerings, and improved customer retention. 

At its core, the proposed Personal Financial Data Rights rule takes away banks’ edge in underwriting loans based on their own transaction data. As consumers gain the power to switch providers effortlessly, banks that stick with old-school underwriting and approval methods will  struggle to keep up with more nimble competitors. Banks that take advantage of AI and ML to harness the data set made available by the Personal Financial Data Rights rule will expand the range of customers served and tailor offerings to their individual needs.

For one, accessing this new data source will enable financial institutions to assess risk more accurately. They’ll be empowered to confidently extend credit to a wider customer base and price credit products more aggressively. AI and ML can offer real-time predictions for various risk outcomes, such as the probability of default or eligibility for credit limit increases.

AI and ML also help them retain existing customers. Since the Personal Financial Data Rights rules gives consumers more power to switch to better providers, banks need to get serious about deepening customer loyalty — and offering them satisfying products and experiences will go a long way here. Analyzing open banking data can help them proactively identify customers’ evolving needs, including upsell and cross-sell opportunities, and gain insights into consumer behavior, preferences, and financial health.

For banks, this rule is a game-changer. It's time for banks to get on board with AI in their lending processes (or risk falling behind) for a few reasons:

Streamlined underwriting processes

Institutions still engaging in manual underwriting processes will struggle to handle the complexity and volume of open banking data. Policies that rely on rule-based decision-making require frequent updates to stay relevant and may not capture nuance and edge cases. AI and ML algorithms, on the other hand, excel at processing and extracting valuable insights from unstructured data. They can spot patterns, trends, and abnormalities in data on the fly, learning as they go. 

Enhanced Decision-Making

Under the proposed rule, banks will no longer need to hoard consumers’ transaction data — they can leverage AI and ML to make better lending decisions based on a much broader dataset. These algorithms can analyze vast amounts of open banking data in real time, accounting for factors such as customer spending habits. AI and ML-driven credit decision and underwriting processes give banks a more holistic view of creditworthiness, helping them make more accurate and personalized lending decisions.

Fraud Detection

The Personal Financial Data Rights rule mandates that certain data relating to consumers’ transactions and accounts be made available, giving banks a valuable dataset to improve their fraud detection methods. AI and ML models can analyze real-time transaction data to detect suspicious activity patterns, helping banks protect their customers from fraudulent transactions. 

The Pressure Is on: Adopt ML and AI Now

The Personal Financial Data Rights rule is a wake-up call for banks: they must harness the power of AI and ML to extract insights from this vast open banking dataset. And the clock is ticking. After the final rule is published, mid-market banks ($850M-$50B assets under management) will have 2.5 years to gain compliance, and small banks (less than $850 million in assets) will have four years. 

The race to leverage open banking data has begun, and those who respond quickly and strategically will emerge as strong competitors in this new landscape. With AI and ML, financial institutions can offer more aggressive pricing, expand their credit offerings, retain existing customers, and make real-time, data-driven lending decisions. The future of banking belongs to them. 

Learn the nuts and bolts of using AI loan technology to streamline your consumer lending process in our latest guide — written especially for small banks and credit unions. Download “The Beginner’s Guide to AI Loan Approval” now.