Balancing Growth and Profitability: Why the Future of Lending Depends on Smarter Risk Assessment
By Tamara Kumposcht, Head of Financial Services at Taktile
Lenders today face a dual imperative: grow profitably while expanding access to affordable credit. To balance profitability and financial inclusion, lenders must excel in accurately assessing borrower risk in the market they serve. This article provides an overview of three distinct but interdependent capabilities for unlocking higher accuracy in risk assessment: advanced modeling using non-traditional data, highly tailored policy segmentation, and continuous experimentation and iteration.
While profitability remains a top strategic priority for lenders, the need for financial inclusion in today’s global community has never been greater.
Millions of customers—particularly in underserved segments such as students, freelancers, and small and medium-sized enterprises—have limited access to affordable credit. In this context, the lenders who succeed will be those expanding credit access in inclusive and sustainable ways.
At Taktile, we believe this balance between growth and profitability is achievable for fintechs who build their risk strategies around one core competency: accurately assessing borrower risk in the market they’ve chosen to serve.
To unlock such unparalleled accuracy, lenders need to excel in three distinct but interdependent capabilities: advanced modeling using non-traditional data, highly tailored policy segmentation, and continuous experimentation and iteration.
Advanced Modeling: Using Alternative Aata to Gain Deeper Visibility Into Borrowers’ Financial Behavior
Lenders wanting to balance growth and profitability should expand the data used in credit decisions. With advanced, predictive modeling that incorporates alternative data on one’s financial health, lenders can approve more of the right customers and outprice competition.
While historical data sources such as credit scores are useful, they often miss critical context for thin-file or no-file borrowers. For example, credit scores are static, creating a lag in accuracy on a customer’s financial behavior. Credit scores are also not all-encompassing—they might not reflect when a customer defaults to a buy-now-pay-later arrangement.
With the ability to evaluate other indicators such as cash flow or rent, lenders gain a more accurate picture of a customer’s real-time financial situation. This enables more inclusive, personalized strategies that improve credit access and portfolio quality.
With nearly 60% of lenders looking to enhance their ability to integrate new data sources into their credit decisions, there is a need for decision infrastructure to support advanced modeling. Adopting modern decision systems can help lenders achieve this goal, resulting in a more holistic approach to risk strategy that maximizes inclusivity and profitability.
Highly Tailored Policy Segmentation: Customizing Credit Decisions for Fairness, Accuracy, and Growth
The value of alternative data comes from using it effectively for risk decisions. While traditional lenders often apply broad rules and uniform thresholds, fintech lenders can design segment-specific credit policies, reaching a better balance between financially inclusive growth and risk-adjusted returns.
By tailoring policies to reflect differences in geography or income, lenders can price risk with greater accuracy and make fairer decisions across customer segments. For example, the underwriting logic that works for salaried workers in urban areas may not work for small businesses in rural markets. Recognizing these distinctions is key to expanding credit access in a sustainable and profitable way.
Fintech lenders that create tailored credit policies are better equipped to serve underserved segments while managing risk. Modern infrastructure providers empower non-technical teams to build data-driven credit decision workflows that can be easily segmented to better match the real-world complexities of their customers. As a result of this more personalized approach, pricing and offers become more precise and inclusive.
Experimentation and Iteration: Empowering Credit Teams to Continuously Test Decision Logic for Optimal Performance
While advanced modeling and tailored segmentation can improve accuracy, even the best risk strategies must continue to evolve. In today’s dynamic financial landscape, the lenders quickest to adjust decision logic based on their performance can more easily achieve financially inclusive growth.
For example, through A/B or shadow testing, lenders can trial new rules in a controlled environment to optimize for their goals. In the underwriting use case, credit teams could test an inclusive approval threshold, monitor results for four weeks, and confidently expand coverage to accept more customers as they see fit.
In other words, the more lenders iterate on what works and what doesn’t, the better they can serve their customers while improving returns on investment. And in recent years, a vast majority of lenders are recognizing the value in this capability, with nearly 40% wanting to increase the frequency of their policy optimizations.
With sophisticated decision infrastructure, risk teams can do exactly that—self-serve on experimentation at a speed and efficiency previously unattainable. This can result in making more inclusive, profitable decisions that pave the way to success for businesses and their customers.
Future-ready Lending for Growth and Profitability Starts with Modern Decision Infrastructure
Now more than ever, lenders must reimagine the balance between growth and profitability as a viable result of accurate risk assessment.
Achieving higher accuracy requires more than incremental improvements—it demands a foundational shift toward modern decision infrastructure that empowers teams to harness diverse data, build highly adaptive policies, and iterate faster than before.
Modern decision infrastructure providers such as Taktile equip lenders with the tools to strike the right balance: enabling more inclusive access to credit while optimizing for profit. Whether you’re fine-tuning risk models with alternative data, expanding into new customer segments, or adjusting policies to real-world market changes, smarter decision systems help you move with speed, precision, and control.
When lenders are empowered to assess risk more intelligently, they can unlock sustainable business growth, true market leadership, and lasting impact on the customers they promise to serve.
Photo Credits:
- Tamara Kumposcht: Taktile