We’re proud to be highlighted in Visa’s latest industry report, “Opportunities for Generative AI in Financial Services.” This recognition highlights the transformative role of Generative AI in reshaping financial services.
Visa’s details the enhancements in fraud management, customer communications, and credit risk assessments – advancements that are crucial for increasing access to underserved markets.
Before GenAI, lenders were strapped by the amount of data they could analyze effectively.
With GenAI, lenders can utilize large datasets to improve risk decision-making and optimize financial services.
GenAI facilitates growth of open banking and cashflow analytics
Traditional banking barriers have often excluded thin-filed consumers, such as minorities, immigrants, and young people, due to inadequate data and outdated tools.
This created a gap in the market, allowing innovative fintechs to leverage the growing availability of open banking data to assess the risk of the 100M+ underserved and credit invisible consumers and businesses in the US. They’ve uncovered an untapped treasure trove of insight into a consumer or businesses’ income and revenue, recurring bills & subscriptions, and rental history to assess risk beyond traditional credit history.
As underserved segments, namely younger consumers, enter the market and adopt fintech apps to manage their daily financial needs, there is an unbounded opportunity to harness genAI to create tailored financial products for these previously underserved groups in ways traditional banks had never done.
Fintechs lead the charge in GenAI innovation
Fintechs like Chime are surpassing established giants like Chase in primary customer numbers, with only 25% of Gen Z holding a primary account at a big bank, according to FICO. These fintechs use AI to get a real-time, comprehensive view of consumer affordability, significantly enhancing their credit risk decisions.
Pave.dev harnesses GenAI to analyze diverse data sources like bank transactions, delinquency data, and loan performance, providing deeper insights into individual financial behaviors beyond traditional credit scores.
Pave enables lenders to analyze cashflow data in real-time, allowing them to tailor financial products to the unique needs of underserved markets. Additionally, Pave partners with companies like Fairplay, helping to improve fairness and compliance risk assessments by identifying and eliminating biases.
As GenAI evolves, its continuous learning capabilities help lenders improve their credit risk models to account for new data and user segments.
How this results in greater financial inclusion
By leveraging cashflow and liabilities data through large language models (LLMs), as noted by Jon Lear, founder of Fintech Meetup, financial services can offer richer, more personalized customer experiences.
This significantly broadens financial inclusion by allowing lenders to extend credit to underserved groups like gig economy workers and small business owners— who are responsible, yet typically overlooked due to traditional credit data and models.
Leveraging diverse datasets through GenAI allows lenders to better understand and meet the needs of a broader customer base, enhancing financial accessibility and inclusivity.
The way forward with AI in financial services
As AI advances, its applications in financial services are expanding, from enhancing customer interactions to improving risk management tools. Pave is committed to using these advancements to foster inclusivity in financial services. Looking ahead, GenAI and cashflow analytics will drive innovation and inclusion, allowing providers to offer more personalized products that cater to the diverse needs of their customers. Read the full Visa report here.
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