Artificial intelligence has become a gamechanger in the banking industry in recent years. The global market for AI in Fintech was valued at nearly $8 billion last year. It is projected to be worth nearly $27 billion by 2026.
There are a number of reasons that AI is becoming an integral part of the banking industry. One reason is that it is driving process automation. However, AI is starting to show potential with even more complicated automation issues.
AI has made open banking possible. New advances in AI could help open banking become even more popular in the near future.
AI Drives the Future of Open Banking
Open banking is the technical process that allows financial providers to dip in and see the banking history and activity of a customer before they apply. It has been made possible through new developments in AI technology.
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The process was recently introduced in the UK and many suggest that it could be the future of underwriting and eligibility for products such as credit cards, loans and mortgages. Antonio Tinto wrote an article about the evolution of open banking in the context of AI in fintech in his LinkedIn post Open Banking and AI – The Rise of Cognitive Banking.
Customers must agree for lenders to see their transactional history and financial information during the application process – but this should be able to provide lenders with a better understanding of the customer’s borrower spending, including highlighting any gambling or debt problems with machine learning algorithms.
For lenders this offers a very insightful look into a customer’s spending habits and should provide much better decisions in terms of loan approvals, credit limits, loan amounts and more.
Budget planning programs and also fall under the umbrella of open banking. These machine learning programs compile data sourced from multiple locations such as credit cards and bank accounts, providing a full picture of spending habits.
What Are the Benefits of Open Banking with AI?
Open banking gives lenders a better picture of a spender’s habits, allowing them to make an informed decision regarding potential loan and credit applications. Lenders use complex data-driven algorithms to make these analyses.
Currently, lenders rely heavily on customer credit scoring and other metrics including income checks and affordability checks, but for the average personal loan or credit card, there is no real delving into someone’s banking activity or machine learning analysis.
This allows lenders to find concrete information if there are recurring gambling issues, multiple loans taken out or huge overdrafts – something that typically goes unnoticed by lenders in basic checks.
Beyond this, lenders and credit providers can use these findings to improve their underwriting and build models to determine eligibility patterns – and thus approve better customers and increase their repayment rates.
What Are the Risks Associated with Online Banking?
Risks associated with online banking tend to include concerns about privacy policies and data protection. Financial data from various sources is merged in order to be analyzed in comparison with other datasets to create predictive algorithms. This can then forecast future spending habits.
This requires the access of private financial data, giving firms access to any transactions. Lenders are able to see any financial transactions taking place with customer consent, which could prevent them offering a loan.
The Difference Between Open Banking and Credit Scoring
Open banking can potentially offer more accurate reflections of a person’s financial situation and can also utilize existing credit scores to make decisions surrounding potential loans even stronger.
As open banking increases in popularity, different types of loans will be able to use it to provide lenders with clear insights of borrowers financial habits. Mortgages and other types of loans have the potential to operate in this manner, as open banking is adopted by more and more businesses.
Will Open Banking Take Off as AI Becomes More Widely Used in the Financial Sector?
AI technology has made open banking possible. Banking institutions are relying more heavily than ever on machine learning algorithms.
David Beard, founder of price comparison site, Lending Expert, commented:
“Open banking is certainly revolutionary and will definitely help lenders to better understand their applicants. Being able to see a customer’s bank statement history can highlight potential risks such as gambling debts or if they are starting with huge debts to begin with. This could help lenders steer clear of troubled customers or approve those that look more appealing.”
“The only challenge is that people have to opt into open banking, which not every customer will want to do – and ideally you need real volumes to make a difference to your bottom line and to build future models.”
“If lenders and providers can present this in a smart way that is data compliant and abides by regulation, open banking could be transformative.”
