How AI is Taking Debt Collection Practices to a Whole New Level

I recently got to know that one of the leading collection agencies in the Philippines S. P. Madrid has been honored with another prestigious award from HDMF (Pag-IBIG Fund) . A heartfelt congratulations to the company's C-level executives and the entire operational team for this well-deserved recognition. It's a testament to the hard work and time invested to achieve such outstanding results.

By the way, did you know that in the Philippines, failure to repay a debt can lead to imprisonment? Far from being a deterrent, this fact underscores the importance of understanding local laws to smoothly adapt to life in a new environment, whether you're dreaming of retiring in the resorts of Boracay or Manila.

Let's delve into the world of debt collection and explore why integrating artificial intelligence into this sector benefits both the debtor and the collector, whether it's an external agency or a lending company.

Being a leader in the collection sector is an art form—it's about managing clients' debt portfolios to enhance recovery rates while maintaining the lender's reputation. And reputation is crucial, especially in collections. Financial companies are ethically bound to treat debtors with courtesy and respect. The Securities and Exchange Commission (SEC) in the Philippines strictly enforces these standards, with guidelines outlined in the Civil Code of the Philippines, the Fair Debt Collection Practices Act, and the Memorandum on Unfair Debt Collection Practices. These rules prohibit abusive, deceptive, and unfair collection practices and respect the personal time of debtors, ensuring no late-night calls to discuss overdue payments.

However, these regulations also mean collectors have fewer tools to influence debt repayment, complicating their ability to increase their own earnings, especially under the No Cure No Pay business model. Legitimate communication channels with debtors in the Philippines include phone calls, emails, and sending demand letters or initiating legal action.

In this challenging landscape, how can collection agencies interact with debtors to efficiently and painlessly recover debts? Enter artificial intelligence, the cornerstone of 2023's motto: the future belongs to companies that harness AI to its full potential . In a previous article, I discussed how GCollection aids banks in debt recovery . But what about collection agencies, debt buyers, and business process outsourcing companies that provide staff for collection services?

How Collection Agencies, BPOs, and Debt Buyers Take Advantage of AI

Each of these three players play a distinct role in the life cycle of debt management. While their methods and motives may differ, they share a common goal: to maximize efficiency and returns in the debt collection process. Here, we explore the challenges each entity faces and how the advent of AI is transforming the debt recovery landscape.?

Collection Agencies

These agencies work with portfolios from banks and non-bank lenders without owning the debt. Their indirect responsibility for the creditor's reputation and their dependence on the volume of collected repayments directly affect their future compensation.

Business Process Outsourcing Companies

They offer telecommunication services to remind clients about upcoming or overdue payments without owning the debt portfolio. They may lack specialized knowledge in collections, as they serve a broader target audience.

Debt Buyers

They purchase debt portfolios and are directly responsible for their company's reputation. They have a vested interest in maximizing collection volumes to increase ROI and expedite investment returns.

The challenge is clear. According to GiniMachine AI statistics, it takes a collector from 4 days to 3 weeks to recover a debt, depending on various factors. For debt buyers, the complexity increases with the portfolio purchase stage, requiring careful analysis of potential payback and the reasonableness of discounts from creditors.

Time is money, and every moment spent on collections is costly. By integrating GCollection's AI, which is grounded in machine learning techniques, you gain numerous benefits:

• Rapid scoring of debt portfolios before purchase to assess ROI.
• Reduction of human bias in analyzing debt portfolios and deciding on communication channels with debtors.
• Fast evaluation of debtors for effective segmentation.
• Data-driven segmentation for prioritizing collection efforts.
• Strategic collection planning in seconds, not days or weeks, to reduce operational costs and cycle time.
• Increased recovery rates through customized and stress-free collection strategies for debtors.
• Compliance with local regulations on unfair collection practices, positively impacting the collector's reputation.
• Attracting more creditors for collection services and increasing financial rewards for collectors on a No Cure No Pay basis.

Wrapping up

@GiniMachine AI is empowering the banking and alternative finance sectors with advanced AI algorithms, streamlining processes, and aiding managers in making more informed and unbiased decisions. If you're interested in learning more, please feel free to contact me.