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Small and medium-sized enterprises (SMEs) are the backbone of the UK economy. According to a recent report by the British Business Bank, they account for 99.9% of all businesses in Britain. Yet, they only receive 20% of all bank lending.
That’s a telling statistic as it means that many are suffering from cash flow challenges or missing out on growth opportunities due to the lack of affordable funding available. It’s a familiar problem facing thousands of SMEs across the country who have to contend with a long and complex loan application process requiring them to submit vast amounts of paperwork, go through arduous verification steps and then wait weeks or even months for a decision.
All that is changing now, however, thanks to advances in technology. Using fintech solutions, the loan application process can be streamlined to provide quicker and easier access to finance.
Key benefits
These alternative financing options harness the power of digital platforms, artificial intelligence (AI), data analytics and automation to simplify the application process. It also enables the lender to improve their underwriting criteria, provide competitive pricing and instant funding.
The key advantage that fintech lenders have over traditional banks is the ability to automate many of the manual tasks involved in processing the loan, which are both time-consuming and inefficient. The use of robotic process automation (RPA) also allows them to speed up workflows and processes, eliminate human errors and reduce operational costs.
The end result is that lenders can provide a far more personalised, responsive and flexible customer service. Here, we examine some of the main benefits that fintech lending can provide.
AI for improved underwriting
As previously mentioned, one of the biggest advantages of using AI and machine learning (ML) is for lenders to improve their underwriting processes. By utilising advanced algorithms and data analytics, they can quickly and more accurately assess a borrower’s creditworthiness.
Taking into consideration a multitude of factors, including the borrower’s income, expenses, assets, liabilities, credit history, business performance and market conditions, the lender can assess the risk and profitability of their loan application. From there, they can decide whether to approve or reject the application. If they choose to approve it, then the underwriting will also inform the loan amount, interest rate and repayment terms offered.
The problem is that traditional banks use manual or rule-based underwriting models that rely on limited or outdated data sources, such as credit scores, financial statements and collateral. Because they are often rigid, inconsistent or biased, they fail to capture the applicant’s full and accurate risk profile.
According to a McKinsey study, AI and ML underwriting models can increase the loan approval rate by up to 50%, reduce the default rate by up to 40% and lower the interest rate by up to 20%. Automated underwriting models such as this can also help improve lending decisions and the customer journey, as well as reduce costs and risks.
RPA’s capabilities
RPA uses AI to mimic human actions and perform repetitive tasks such as data entry, verification and compliance checks. By following pre-defined rules, it can also deal with exceptions and errors or escalate them to human supervisors.
The technology enables both the lender and the customer to speed up and make the loan application process easier. Because RPA can automatically extract the required data from the documents provided to populate it into the application form, it saves customers having to manually input it, and lowers the risk of mistakes and fraud.
From a lender’s standpoint, it helps them to automatically verify the data against external sources, such as credit bureaus and government databases, and flag any anomalies or discrepancies. This ensures accurate and complete data that meets the necessary regulatory requirements.
A further advantage of RPA is that it allows lenders to automatically provide loan offers, contracts and reports based on the data and underwriting criteria via email or SMS. The efficiencies this affords are evidenced in a Deloitte study, which found that the technology can reduce processing time by up to 90%, accuracy by up to 100% and lower costs by up to 80%.
Open banking and open accounting
Open banking and open accounting take the loan application process one step further. With instant access to the borrower’s up-to-date financial information through their bank account or accounting software, lenders can make instant decisions on loan eligibility, amount and terms.
By using application programming interfaces, which allow systems and applications to communicate and exchange data securely and efficiently between each other, lenders can quickly and effectively aggregate and analyse large amounts of data to gain greater insight into an applicant’s financial performance and health. They can also look at their financial activity, behaviour and preferences.
Improved customer service
By using digital tools, such as chatbots, live chat and video calls, lenders can provide 24/7 help with their loan application. They can also use customer relationship management systems to monitor preferences and behaviour and receive feedback in the form of net promoter scores and customer satisfaction ratings and reviews, in order to be able to develop more customised solutions for them.
Lenders also make the loan application process more user-friendly and efficient by utilising digital platforms such as websites, online portals and apps, so they can apply for one anywhere and at any time. The use of digital tools, including digital signatures, biometric authentication and electronic know-your-customer to verify a borrower’s identity and eligibility also makes the process more streamlined, while digital channels like SMS or emails improve communication with them as well.
Fintech is the key to a quicker and more efficient loan application process for SMEs. It’s helping them to secure the vital funding needed to grow their business and thrive.
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
Ben Parker CEO at eflow uk ltd
23 December
Jitender Balhara Manager at TCS
22 December
Arthur Azizov CEO at B2BINPAY
20 December
Sonali Patil Cloud Solution Architect at TCS
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