Synopsis: The rising popularity of small and independent businesses has challenged fintech lenders to develop innovative lending models to acquire the market. Let’s examine some of the popular lending models and understand how they work.

Traditional lending practices have significantly transformed due to recent technological advancements in the fintech domain. The Indian fintech market size alone is expected to reach ~$150, a valuation of $150 billion by 2025. Due to the rise of small and medium businesses post-COVID, fintech companies are changing their credit access methodologies. The aim is to offer greater flexibility, speed, and convenience than conventional banking methods to attract more applicants. Let’s take a look at some prominent lending models that are shaping the future of fintech businesses all over the world.

Types of FinTech Business Models

Alternative Credit Scoring

Alternative credit scoring determines the applicant’s loan repayment history by analyzing reliable past data across several points.

The model considers the applicant’s online presence (digital footprint) as the major source for credit scoring models. A verified digital profile assures that the applicant is not fake, and the additional data points may further provide data about the applicant’s financial stability. Usually, the red flags come in the form of throwaway addresses, a burner number, or a shady digital presence.

For instance, if an applicant has a verified LinkedIn account that proves his regular employment, it would be easy to guess the income level and make an informed decision.

Peer-to-Peer Lending Model

P2P lending models are also known as marketplace lending, where the loan is funded by a person rather than any bank or financial organization.

Applicants fill out an online form through a platform and get connected with interested investors for further discussion.

P2P lending models come with higher potential returns than other types of investment. Certain P2P systems can also facilitate reserve cash in case borrowers default or experience problems.

You can withdraw your money immediately, but there may be fees. Also, if the borrower pays off the loan early, you may get lower returns than projected.

Alternative Underwriting Model

Beyond unconventional credit evaluations,  fintech companies are now integrating personal information to make risk evaluations. That includes examining lifestyle logs and wellness records for actuarial clues. Through AI, these Insurance startups can automatically choose clients, customize policies, and offer alternative payment options. Yet evaluating intimate details necessitates careful handling and full consent without privacy infringement and discrimination.  fintech companies such as Carpe Data are leveraging such premium scoring models with alternative data points for evaluation.

Small Ticket Loans

Till September 2023, 77% of the loans offered by fintechs were below Rs 1 lakh. Fintech offers small-ticket loans to individuals and businesses looking for quick and relatively small loans. The entire process is carried out by technology to analyze alternative data points beyond traditional credit scores for risk assessment. Since the risk profile of most borrowers is unknown during the process, fintechs often charge high-interest rates to compensate.

Digital Wallets

Digital wallets use the applicant’s existing digital financial information to process loan applications and disbursals directly within the app. This is one of the popular fintechs lending models that has now 3.4 billion digital wallet users (42.6% of the world population). This streamlines the process, removing the need for visits to physical banks or lengthy paperwork. However, digital wallets are typically ideal for small loan amounts due to the perceived risk associated with quick approvals.

Challenges and Considerations

Before engaging with any fintech lending model, it is imperative to acknowledge the potential challenges and prepare accordingly. Let’s examine three major challenges and see how to address them easily.

Data Privacy and Security:

Fintech models often collect vast data from multiple sources beyond traditional credit scores. This includes social media information, mobile phone usage, and online transactions. Storing and managing this vast amount of personal data requires robust cybersecurity measures to prevent unauthorized access, data breaches, and potential misuse.

AI Bias in Regulatory

Critics worry that AI and ML algorithms can introduce historically discriminatory lending practices into automated credit fintech models.

For example, many regulators are closely analyzing the potential of automation to trigger unfair practices, such as redlining. They suspect that algorithms could intentionally take out potential borrowers as on their race, ethnicity or other geographical data.

Algorithms could potentially misuse data points associated with race and ethnicity in a similar way to historical lending practices, which relied on factors like neighbourhood location to discriminate against borrowers.

One of the best ways to mitigate AI bias is to preprocess data to exclude factors like race, gender, or other sensitive characteristics. Though this will not eliminate potential bias completely, it will create models that will go “blind” to such features during decision-making.

Addressing these Challenges

Collaboration between Stakeholders: Regulatory bodies, fintech companies, and consumer protection agencies must work together to establish robust data security standards, implement clear regulations for various fintech lending models, and address potential risks.

Promoting Financial Literacy: Fintech companies should also take the Initiative to educate applicants about responsible borrowing practices and managing personal finances, which are crucial for informed decision-making.

End Thoughts

Even most creative fintech lending models are not safe from challenges. Potential issues like data privacy concerns and the risk of overborrowing will continue challenging fintechs to leverage more responsible practices. However, with a well-oiled streamlined process, fintechs can unlock huge potential benefits such as wider financial inclusion, faster approvals, and convenient access to credit. Above all, with every model upgrade, fintech companies need to adhere to strict regulations and robust security measures to ensure a sustainable and responsible lending ecosystem. In this regard, this guide can further help you understand the best practices for credit risk management in SMEs.