By Chirag Shah, founder and CEO of Nucleus Commercial Finance.
In recent decades, the landscape of banking and lending has undergone significant transformation. In the past, traditional high street banks were the go-to for all financial transactions and loan applications, but now, everything can be done with the click of a button. Looking ahead, the convergence of artificial intelligence (AI) and open banking is set to revolutionize credit services.
AI’s Role in Modern Lending
AI plays a crucial role in tapping into the potential of lending. By conducting real-time analysis to more accurately evaluate borrowers’ risks, AI empowers lenders to make faster and well-informed decisions. This also aids in enhancing portfolio management and eliminating human errors.
When coupled with speech recognition technology, AI can capture and analyze verbal customer interactions, empowering more effective sales prompts, bolstering fraud detection, and refining feedback mechanisms. Furthermore, explainable AI allows for comprehensive scrutiny of the decision-making process.
The Significance of Data
Data holds the key to enhancing AI-driven credit decisions. By amassing substantial relevant data, lenders can facilitate the development of appropriate AI and machine learning (ML) tools necessary for driving this decision-making process.
While retail has embraced AI early on, the business lending sector has not fully harnessed its potential. Nonetheless, given the considerable financial stakes involved, the slower adoption of AI is not unexpected.
Organizations are now beginning to embrace this innovative technology. However, wide-scale adoption necessitates all stakeholders, including lenders, technology firms, and capital-providing banks, to fully comprehend the capabilities of AI. Lenders must also exercise caution in adopting AI, avoiding rushed full automation of the lending process to prevent irreversible mistakes. Gradual comfort with the technology is essential, utilizing human intelligence to guide its development.
Open Banking as a Catalyst
Open banking technology serves as a catalyst for the effective integration of AI. It enables loan providers to access businesses’ accounts, fostering enhanced transparency and secure data sharing essential for evaluating applicants’ creditworthiness and making informed credit decisions while reducing default rates. Additionally, it enables lenders to tap into previously untapped borrower segments.
The use of open banking data is especially advantageous for startups lacking sufficient data to secure funding. As more data on various businesses seeking finance becomes available, lenders can make more accurate predictions, expanding the pool of businesses they can support, particularly newer businesses in need of financing.
Risk Management and AI Adoption
By providing regular data-driven insights into their financial performance, companies can improve their prospects of loan approval, swiftly identifying and addressing common issues like cashflow gaps. When combined with open banking, AI enables lenders to rapidly gauge a borrower’s default probability and identify low-risk customers, leading to a more sustainable customer base and improved profitability.
Securing Funding Successfully
Businesses can enhance their chances of securing funding by seeking it proactively rather than waiting until they are in dire need. The goal is to accelerate loan approval and implement instant lending solutions through embedded finance, powered by AI and ML. Despite the slow progress due to data segregation in business lending, optimism surrounds future prospects as small-to-medium-sized businesses show increased demand for funding, signaling a potential rebound from the impact of the ongoing pandemic and government support.
About the author
Chirag Shah, founder and CEO of Nucleus Commercial Finance, founded the company over a decade ago with a mission to offer flexible funding solutions to the UK’s business sector. By leveraging AI-powered automated underwriting, Nucleus Commercial Finance aims to provide transparency in the lending process and work closely with clients to ensure a more supportive and informed loan application experience.
