India’s Leap Towards Digital Debt Collection

Debt collection is the fair and ethical process of recovering delinquent and past-due payments from the borrower. This is done on behalf of the creditor. The debt collection industry is rapidly expanding. Consequently, the relevance of debt collecting agencies is also increasing.

In 2015, the average debt of millennials was $49,722, which rose to $78,396 in 2016, marking a? whopping increase of 58%. The recovery of these rising debts is now increasingly characterised by digitisation.

Find the attached link of the average debt across generations and the percentage variation over time

Digital Collections: India vs. Other Economies

Since the Indian economy got on the digitisation bandwagon, the debt collection software market in India is flourishing. This is a two-way flow—one negative, and the other positive.

The growth of the software debt collection market reflects the increase in delinquencies and payment failures. As of 2022, India’s debt collection market stood at $174.98 million. It is expected to grow at a CAGR of 9.28% and reach $272.7 million by 2027.?

The global revenue of the debt collection market was $3120 million in 2019. By 2027, it is predicted to touch $6778 million, growing at a CAGR of 10.2%.?

In the US, one in every four Americans has at least one debt in collection. The debt collection market in the US generated revenue worth $1790 million in 2022.?

In absolute terms, although the size of the debt collection looks huge, the growth has not been remarkable. This implies a high payment failure. Therefore, the software or digital debt collection market in the US is booming. In 2019, the debt collection software market was valued at $2.9 billion. It is expected to grow at a CAGR of 9.6% and reach $4.6 billion in 2024.?

Meanwhile, the Europe debt collection software market was valued at $961.27 million in 2019. It is expected to grow at a CAGR of 11.1% between 2020-2027and reach $2.23 billion by 2027.?

China, another giant in the software debt collection market, is expected to achieve a CAGR of 9.3% between 2022 and 2032.?

An overview of debt collection software market CAGR across regions

Delinquency in the Indian Debt Collection Market

In the last two decades, lending in SMEs, retail, and the private sector witnessed a dramatic increase. Among the emerging markets, India now ranks third in total debt, which amounts to $4.65 trillion. This debt is spread across the private sector, non-financial corporate debt, and household debt.?

While this has triggered further distribution of credit and increased revenues for financial institutions, it has also led to a massive rise in loan defaults.?

Recently, the Reserve Bank of India (RBI) took a significant step toward checking the hardening inflation. It hiked the Cash Reserve Ratio. This has led to a lot of volatility in the fixed income or bond market. This is because it is a market dynamic—an increase in bond yield is inversely proportional to the price of the bond. The fall in the price of the fixed income securities resulted in market-to-market losses for the investors. The sequential impact of such losses in the bonds market is increased delinquency on the part of those who invested in bonds.

In terms of consumer credit, there is a major concern about loans given by non-banking financial companies (NBFCs). Delinquencies on two-wheeler loans, loans against property (LAP), and personal loans are on a continuous rise.?

As of November 2021, delinquencies in the LAP segment were the highest at 4.14%—30 basis point up from 2020. In the two-wheeler segment, loans due past 90 days were the second highest at 3.64%, recording an increase of 140 basis points from the previous year. Furthermore, in the individual segment, consumer durable loan delinquencies were the third highest at 2.81%. Interestingly, delinquencies in the credit cards segment have eased by 77 basis points and were at 2.22%. On the flip side, in unsecured loans, there is a lot of insolvency in microfinance, followed by personal loans and credit cards.?

Another significant aspect is the deterioration of the portfolio of fintech companies. They have 43% more delinquent accounts than private banks. These fintech companies need an immediate review of their debt collection management. Reports show that these fintech companies have onboarded customers with low credit scores and leveraged a high amount of alternate data. Interestingly, the repayment structure and rate of Micro Finance Institutions (MFIs) have improved post-pandemic. As far as NBFCs and fintech companies are concerned, they need to put effort toward loan restructuring and partial repayment. This can be effectively materialised using the digital mode of debt collection.?

Benefits of Digital Collections

Digital debt collection is the process of using modern technology such as Artificial Intelligence (AI) and Machine Learning (ML) to collect debt from borrowers. The traditional approach requires debt collecting executives to continually call or email the borrowers for repayment. This setup does not allow the executives to analyse or intimate the customers, leading to a below-par result. Sometimes, muscle power and coercion are used to collect the debt, but it mostly intimidates the borrowers forcing them to go into hiding. Making recorded calls hardly creates any impact. Thus, aggressive agents and robocalls do not deliver.?

Instead, today’s digi-conscious customers prefer an effective mode of interaction that does not encroach on their personal space and time. Also, there are many benefits of digital collections such as:

Enhanced recovery rates: Digital communication allows an optimised point of contact. Contacting customers through digital platforms improves customer interaction and keeps any intimidating tactics off the bay. This helps in better recovery.

Reduced call volumes: Software-based debt collection method reduces the need for constant calling. It not only reduces the call volumes but also saves a significant amount of time and money.?

Compliance maintaining: Manual maintenance of compliances, documentation, and intimations are always associated with some levels of errors. This possibility is eliminated in the digital collection which allows easy and convenient maintenance of compliances.

Customer-centric solutions: Using software for debt collection allows the lender to design custom-made repayment schedules and loan restructuring. This helps the customer to adhere to repayments regularly and without any hassles.?

Outlooks and Challenges in Digital Collection

Given the wide range of benefits and future-looking inertia of digital debt collection, it is no surprise that more and more debt collection management is becoming software-centric. There is a clear transition from muscle power and aggressive calls to artificial intelligence and machine learning. Data-backed AI can help develop optimal strategies for both customers and lenders.?

On its way forward, digital collection is slowly making its way to rural India. Software-led debt collection is a significant component of the digital transformation of rural India. The underreach of finance and fin-tech recovery tools, be it in urban space or rural areas, will hinder the economic growth and development of the country.?

However, there are some major challenges in implementing software-based recovery of debt collection. While it is true that software is customisable, it can be done only up to a certain extent. Making customised schedules for every set of customers will require extensive technological and financial input. So, at some level, there remains a similar problem as one size does not fill all. It is so because one algorithm won’t work for all. In addition to the aspect of restricted applicability, there is also the issue of data debt. Irrelevant or bad data can create way more problems than finding repayment solutions. Without good data, driving solutions is next to impossible. Instead, significant resources would be necessarily required to filter the data, further adding to costs by magnanimous amounts. In turn, this gives rise to the possibility of high technical debt for software providers.

Despite these issues, AI and ML-backed software-based digital debt collection is the way forward. The challenges faced by digital collection are common to technological advancement and penetration. Today’s customers essentially seek data-based authentic information and real-time efficient communication. Both of these can be easily achieved through software-based debt collection.?

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Sources

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