ESG Blind Spots: Why Investors Fall for Fintech’s False Narratives
- Tassos Stassopoulos
- 52 minutes ago
- 3 min read
ESG Investing’s Blind Spot: How Motivated Reasoning misses Predatory Fintech
In ESG investing—particularly in fintech firms claiming to address social issues like financial inclusion—investors are dangerously prone to motivated reasoning, a cognitive bias that leads them to favour information aligning with their ideals while ignoring contradictory evidence. This bias is amplified because investors rely heavily on company-supplied data and lack firsthand exposure to the realities of low-income users.
Many ESG-focused fintechs market themselves as ethical disruptors, touting AI-driven lending models, awards for social impact, and narratives of "banking the unbanked." But without ground-level verification, investors risk falling for ESG decoupling—where a firm’s marketing diverges sharply from its actual impact.
Juan’s Story: The Human Cost of "Inclusion"
Juan[1], a university worker in Mexico City, is in his late 30s, married with two children. He wakes at 4:30am to cook for his family before enduring a long commute. Life was hard but manageable—until 2017, when a major earthquake destroyed his home.
Stress triggered a serious illness; depression followed
Seven years later, when we met him as part of a recent ethnographic study, Juan was trapped in a predatory debt cycle. He’d turned to "financial inclusion" apps to manage expenses. At first, the convenience felt like a lifeline. But by 2024, he was juggling repayments across multiple apps, borrowing new loans to repay old ones. Stress triggered a serious illness; depression followed. "What else can I do?" he asked.
When we reviewed his contracts, the truth emerged: these fintechs charged him usurious rates. One loan of MXN 12,200 (US$635) required repayment of MXN 17,124 (US$892) in 30 days—a 40.4% monthly rate (or 5,000%+ APR).
The Disconnect Between ESG Narratives and Reality
Mexico’s microcredit and BNPL app market—worth US$6bn and to growth at a 24.9% CAGR over the next 5 years[2] —is built on ultra-short repayment periods and exploitative tactics.
Through interviews, we’ve seen how these apps lock users in:
• "Credit score" nudges that incentivize perpetual borrowing.
• Discounts that only activate after reaching dangerous debt levels.
• Algorithmic pressure to take new loans to "prove" creditworthiness.
From boardrooms, these apps appear heroic—serving those excluded by traditional banks. On the ground, they perpetuate financial servitude. The consequences ripple outward: for the 50% of Mexicans in informal work, debt cycles trap them in precarious jobs, stifling upward mobility.
Investors’ Cognitive Traps
Our desire to drive social impact, exposes us to three dangerous biases:
Motivated reasoning: Embracing data that aligns with our values and ideals without scrutiny.
Confirmation bias: Prioritising reports that validate optimism.
Overconfidence: Trusting ESG claims without scrutinising the practices.
The Way Forward
True financial inclusion requires fair, sustainable services—not instant loans masking exploitation. Investors must:
Demand ground-level data beyond company metrics.
Question tidy narratives with ethnographic research.
Rethink "impact" through a human-centred lens.
Juan’s story isn’t an outlier—it’s a warning. Only by confronting our biases can we avoid funding predation in the name of social progress.
[1] For reasons of privacy, this isn’t the respondent’s real name, but all other details of his lives are accurate.
[2] https://www.globenewswire.com/news-release/2025/03/06/3038353/28124/en/Mexico-Buy-Now-Pay-Later-Business-Report-2025-2030-Accelerated-Expansion-Competitive-Landscape-Regulatory-Development-Integration-in-Physical-Retail-Strategic-Partnerships-Enhancin.html
Trinetra Investment Management disclaimer: This material has been prepared by Trinetra Investment Management LLP (“Trinetra”) for information purposes only and it is not intended to be relied upon as a forecast or research. While the information herein is considered to be correct, no representation or warranty can be given on the ultimate accuracy or completeness of such information.
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