Intelligence Vault: Inclusive Credit Strategies

We recently carried out research into the use of artificial intelligence and data analytics within Credit Risk Management within financial institutions.

This short article in our Distinctive Insights Intelligence Vault series delves into one of the key highlighted themes: Inclusive Credit Strategies.

Our aim in publishing this content is to help finance professionals further understand how artificial intelligence and data analytics are being applied to support key business processes within financial institutions.

The Strategic Shift

One of the more interesting trends we’ve been tracking in our research is the growing focus on inclusive credit strategies.

It’s not just about expanding access — it’s about rethinking how banks – and other financial players – assess creditworthiness in the first place.

We’re seeing financial institutions experiment with new signals: behavioural and psychometric data, cashflow-based modelling, even localised scorecards tailored to communities that have been underserved by traditional methods.

At the same time, fairness and bias mitigation are starting to move from a regulatory feature to a core design principle. That’s a significant shift.

What stands out is that these approaches aren’t just ethically motivated — they’re proving to be commercially viable too. Inclusion and performance aren’t mutually exclusive.

Techniques, Tools, and Players

Let’s get into the mechanics.

When we looked deeper into how institutions are approaching this, a few techniques stood out:

• Behavioural and psychometric profiling — using responses, habits, and micro-signals to uncover credit potential where traditional history is thin.
• Cashflow underwriting — simulating affordability and future earning potential, rather than relying on legacy scorecards.
• Localised scoring frameworks — models tailored to specific markets or community characteristics.
• Fairness optimisation — actively tuning models to reduce bias and monitor impact on protected groups.

These aren’t just theoretical. A number of vendors are building tools to support this shift — and we found some genuinely interesting ones:

FairPlay is doing real-time fairness testing and monitoring, helping lenders integrate bias analysis directly into their decisioning.
Stratyfy focuses on interpretable AI and transparency — their models are built to explain themselves, which is rare and valuable.
Nova Credit helps institutions use international and alternative data to unlock access for migrants and thin-file customers.

Real-World Momentum

Over the past 12 months, we’ve seen a steady stream of real-world moves pointing to one thing:
Inclusive credit strategies are gaining serious momentum.

Banks, fintechs, credit unions — across regions and business models, institutions are now operationalising fairness, explainability, and expanded access.

A few standouts from our research:

• Chime, Upgrade, and LendingPoint have all partnered with FairPlay to embed real-time fairness testing into their underwriting processes.
• Nova Credit has rolled out its cross-border credit solutions with the likes of RBC and Scotiabank — helping migrants carry their financial history with them.
• Experian launched cashflow-based tools that give lenders new ways to assess consumers with little or no credit history.
• Ant International and Dock are building inclusive lending platforms for MSMEs in Brazil.
• Stratyfy and Prism Data are working together to widen credit access using digital deposit account insights.

And the funding continues: FairPlay alone raised $10 million this year from JPMorgan Chase, Nyca Partners, and others.

Taken together, this isn’t just innovation — it’s a shift in what “good” credit decisioning looks like.