Revolutionizing Ethical FinTech Debt Collection: Can AI Lead the Way?

As global debt balloons, the burden on financial services sectors is escalating. Not only does this growing amount of debt remain an issue for conventional banking systems, but it now poses a competitive threat to the swiftly besetting FinTech industries going through significant hurdles in accumulating debt. Amidst this global shift, Indonesia’s FinTech has also been dealing with growing debt pressures in the peer-to-peer (P2P) lending industry.

Global Debt Trends and Their Impact on Ethical FinTech Debt Collection

Total global debt is set to exceed $100 trillion, or about 93% of global GDP by the end of 2024 and nears 100% of GDP come 2030 according to the International Monetary Fund. That is an increase of 10% compared to pre-pandemic levels in 2019. Norton Rose Fulbright pointed out that private debt continues to grow fast with the global size of the asset class set to almost double from $1.5 trillion early this 2024 to $2.8 trillion over 2028.

Debt Pressures in Developed Markets

In addition, the debt problems have been observed in developed markets as well such as the United States, China and Canada with record levels of debt ratios according to CEIC data. For China, private debt soared to a record 200.56% of GDP in the March quarter of 2024, while Trading Economics reports that by June 2024, it had also reached a staggering 214.5% of GDP in Canada with an expectation for it to rise further by 260% forecasted for year-end. In the United States, the private debt-to-GDP ratio is expected to hit 211% by the end of 2024. The growing private debt burden is straining financial systems globally, complicating debt management and collection. In the U.S., for example, the Consumer Financial Protection Bureau (CFPB) has flagged the growing prevalence of illegal debt collection practices, such as inflated charges, misrepresentation of rights, and unsubstantiated debt claims.

Debt Collection Challenges in Indonesia’s FinTech Sector

Apparently, these issues are not confined to the West. In Indonesia, the Financial Services Authority (IFSA) reported that specifically the FinTech peer-to-peer (P2P) lending industry had an outstanding financing balance—representing the total debt that remains unpaid—amounting to IDR 74.48 trillion as of September 2024, marking a 33.73% increase year-on-year. Meanwhile, the aggregate non-performing loan (NPL) ratio was recorded at 2.38%.

Consequently, debt collection practices in FinTech are facing similar scrutiny. The IFSA recorded over 400 complaints in 2024, mainly against debt collectors in the FinTech sector, with grievances about aggressive tactics and intimidation. To address these issues, the IFSA has imposed administrative sanctions under IFSA Regulation No. 22/2023, prohibiting the use of threats, violence, and tactics that can cause embarrassment to the consumer.

Regulatory Measures and AI Solutions in Debt Collection

In addition to conducting the debt collection themselves, Article 61 of IFSA Regulation No.22 Year 2023 also regulated that financial services providers including FinTech providers may partner with a third party for the purpose of collecting debt. However, FinTech providers must ensure that debt collection is conducted without threats, violence or actions that humiliate consumers. Article 62 also mandates that they must refrain from using pressure either physically or verbally while carrying out the procedure.

Considering the continuing incidents of violence perpetrated by debt collectors working with FinTech providers, other measures need to be taken to mitigate such abuse. Artificial Intelligence (AI) can be one of the game-changing ways to transform traditional debt collection processes where compliance, efficiency, and consumer protection can be established.

Also See: “Fintech” Set To Change the Financial System via Innovation and Mutual Cooperation

The Role of AI in Debt Collection Transformation

According to Grand View Research, 11% of debt collection firms in the U.S. utilize AI for debt recovery, while the global debt collection software market value is anticipated to expand at almost ten percent every year from now until 2030. Other Indonesian FinTech providers have also started to integrate AI, such as automating tasks like sending reminders, creating reports and managing communication between the platform with debtors. The increase in automation improves efficiency while reducing operational costs and streamlining the entire process.

AI additionally thought about providing a much more customized technique to personal debt collection. AI can foresee how debtors will behave and then emotionally modify the collection strategy according to each scenario by synthesising data from various sources. This minimizes the need for overwhelming measures. Moreover, AI may also be crucial to the use of high dimensional data such as financial behaviour, credit history, and repayment capacity checks during borrower screening in compliance with Indonesian regulations. By being proactive in this way lenders will know what borrowers are more of a risk than others before a loan is even released which means the chances of that loan becoming delinquent will be smaller and also keep their loan portfolio healthy.

Ethical Use of AI in FinTech Debt Collection

Indonesia Financial Services Authority (IFSA) together with the major FinTech associations launched an AI Code of Conduct in 2023 to support the ethical use of AI within FinTech. This framework emphasizes principles around fairness, accountability, transparency, and security. The guidelines encourage FinTech providers to design AI applications that promote the dual objectives of improving the operational effectiveness of businesses and serving consumer interest, including financial inclusion and sustainable economic growth. The goal is to ensure that AI applications do not violate consumer privacy, introduce biases, or cause discrimination. The AI Code of Conduct also advises FinTech providers to implement strong cybersecurity protocols that can safeguard information about debtors.

Challenges in AI Adoption and Future Outlook

Despite its potential, the widespread adoption of AI in debt collection may face several challenges. One important point to consider is that debtors in Indonesia are highly heterogeneous with respect to financial literacy and inconsistent repayment behaviour. All of these represent considerable obstacles for AI solutions that must adjust to local consumer behaviour. Data privacy and cybersecurity issues must also be resolved, given that the ability of AI systems to make accurate predictions depends on consuming large datasets and as a consequence, questions about how debtor information will be processed. In order to protect consumer privacy, it must also mean complying with Indonesia’s data protection laws. Moreover, the opacity of AI algorithms is a concern, noting that in the absence of transparency, AI systems might be biased and lead to discrimination against some groups of debtors.

Overcoming Barriers to AI Integration in Indonesia’s FinTech Sector

Another issue is the tech infrastructure needed to deploy AI. While the most advanced AI systems can be resource-heavy, larger financial institutions might have the access to extremely sophisticated technology, yet smaller FinTech providers could find it more expensive and challenging to integrate with AI solutions in their entire cycle of service products. Hence, this AI-based disparity may hinder the full scale of adoption in the industry at large to derive its promise. Localisation of the AI solution to tackle these challenges made sense.

FinTech providers must work hand in hand with data scientists who can conduct research on a decentralized network to design and train AI-based models that track the subtleties of the local market. With local data, AI systems are more effective, making it easier to solve problems that exist in the Indonesian consumer market. Collaboration of FinTech providers with regulators will be essential to overcome the problem of securing ethical and legal use of AI applications. These collaborations can provide better assurance to customers and the financial system that AI technology will be implemented appropriately.

The Promise of Ethical AI in Debt Collection

Moving forward, as Indonesia continues to embrace AI in debt collection, it is important to strike a balance between innovation, regulation, and ethical considerations to protect consumers and maintain the integrity of the financial services sector. Although its use can be transformational in the long run for how debts are collected in Indonesia, much of AI adoption will depend on overcoming challenges such as data privacy, transparency of algorithms, and ensuring equitable access to technology. Through collaboration between FinTech providers, regulators, and data scientists, this promise can be achieved—transitioning towards an AI-powered ethical debt collection system for Indonesia that works not only for the benefit of the financial services sector but also in the best interest of consumers.

The views expressed in this article are the author’s own. They do not necessarily reflect the editorial policy of the South Asia Times.

Alya Nabila

Alya Nabila is a Legal Analyst at the Financial Services Authority, specializing in financial regulations for institutions, venture capital, and microfinance. A graduate of Universitas Indonesia, she has also completed executive education at Cambridge and Oxford, focusing on regulatory innovation and sustainable finance. Her articles have been published in The Jakarta Post, covering topics like PayLater schemes, FinTech loans, and combating online gambling.

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Revolutionizing Ethical FinTech Debt Collection: Can AI Lead the Way?