AI Risk Decisioning Software for Banks: How Tejas AI is Leading the Way
In the complex and fast-paced world of banking, risk decisioning is a critical, yet painfully slow, process. Every time a bank grants a loan, it relies on intricate, manually maintained credit rules that govern who qualifies and under what terms. These credit rules are deeply embedded in legacy systems and are managed by teams of analysts, compliance officers, and risk managers. Even a minor update—say, tightening the rules in a specific zip code—can take as long as six months to roll out.
The result? Banks hemorrhage billions annually due to missed opportunities, regulatory penalties, and defaults. Risk managers, sometimes leading teams of 200 or more, spend their days buried in fragmented systems, trying to make sense of millions of loan records. Meanwhile, regulatory environments shift, customer profiles evolve, and the competition grows more agile.
This lag and manual burden often leave financial institutions behind the curve, reacting to problems rather than proactively managing risk. In a data-rich yet insight-starved environment, banks need a way to update and optimize their risk strategies—not in months, but in minutes.
What Is Tejas AI and Why Was It Created?
Tejas AI is a 2025-born startup that aims to modernize risk decisioning for the banking and financial services industry (BFSI). Founded by Gaurav Luhariwala and Bhavesh Tolia, the startup emerged from firsthand frustrations with the sluggish and manual decision-making processes banks face today.
Gaurav, a product and business strategist with a track record of building KYC and data products for Indian banks, teamed up with Bhavesh, a seasoned technologist from Microsoft and Texas Instruments. Bhavesh had already delivered enterprise AI solutions for financial giants like Allianz, Deutsche Bank, and Angel One.
Together, they envisioned a platform where banks could test, optimize, and deploy new credit policies on the fly—with full transparency and AI-powered intelligence.
Their mission? To eliminate the guesswork in risk decisions and give banks the speed, agility, and confidence they need to thrive.
How Does Tejas AI Work?
Tejas AI functions as an AI-powered risk decisioning platform, offering a comprehensive suite of tools that turn outdated processes into agile, data-driven workflows. Here's a closer look at how it works:
- Data Ingestion & Policy Input
Banks begin by uploading their existing loan data, risk models, and policy documentation into the Tejas AI platform. Whether their goal is conservative lending or bold market expansion, the system tailors its models to support the bank’s strategic direction.
- Real-Time Impact Analysis
Tejas AI instantly analyzes how proposed changes would affect default rates, profitability, and growth—before a single decision is implemented. These analyses aren’t black-box predictions: they come with full explainability so that stakeholders understand every risk tradeoff.
- AI-Powered Policy Exploration
Want to know what would happen if you loosened criteria in one market while tightening it in another? Just ask. Tejas AI lets users input questions in natural language—like “What happens if we lower the minimum credit score in Texas?”—and then runs simulations to reveal potential impacts.
- Automated Policy Execution
Once a policy looks promising, Tejas AI turns it into executable code compatible with the bank’s Business Rule Engine (BRE). There’s no need for manual coding, system rewrites, or months of delay. The deployment is instant and seamless.
- Continuous Learning
As loan performance data comes in, Tejas AI adapts. The system continuously refines its models using borrower behavior, macroeconomic trends, and real-time loan outcomes. Banks receive alerts and updated recommendations, ensuring policies evolve with the market.
What Makes Tejas AI a Game-Changer for Banks?
Tejas AI doesn’t just digitize existing processes—it transforms the way banks think about risk and growth. The platform delivers a set of competitive advantages that set it apart:
- Speed: Credit rules that used to take months to revise can now be changed in minutes.
- Automation: Manual, error-prone tasks are replaced with AI-driven insights and execution.
- Hyperlocal Strategy: Banks can roll out targeted, region-specific lending strategies backed by data.
- Natural Language Interface: Policy exploration becomes as simple as typing a question.
- Real-Time Adaptation: Continuous learning keeps risk models sharp and responsive.
This isn't just about operational efficiency—it’s about strategic agility. Tejas AI enables banks to pivot quickly, seize new opportunities, and respond to emerging risks with confidence.
Who Are the Founders Behind Tejas AI?
Behind Tejas AI are two complementary minds who bring product vision and technical prowess to the table.
Gaurav Luhariwala, Co-founder and CEO, previously led product and business at Tartan. There, he helped scale revenues eightfold in a year, largely through products aimed at Indian banks. His entrepreneurial streak also includes building and selling a D2C conversion product—all while still in college.
Bhavesh Tolia, Co-founder and CTO, has a background in AI development for some of the world's biggest financial firms. At Microsoft and Texas Instruments, Bhavesh built scalable enterprise AI systems, giving him the technical edge to design the infrastructure behind Tejas AI.
Together, they bring a unique blend of banking expertise, startup hustle, and enterprise-grade engineering.
Why Is Tejas AI Positioned for Rapid Adoption?
The financial services industry is at a crossroads. Traditional methods of risk assessment are buckling under pressure, and regulatory landscapes demand faster compliance. With digital banking and fintech disrupting the space, legacy banks can no longer afford slow adaptation cycles.
Tejas AI arrives at a perfect moment. It doesn’t ask banks to scrap their existing systems—it enhances them. Its plug-and-play capability, combined with real-time explainability, removes adoption barriers. Banks no longer need to choose between innovation and compliance; they can have both.
Moreover, the founders' prior experience with BFSI institutions gives them a deep understanding of internal pain points, allowing Tejas AI to address not just technical challenges but also organizational ones.
What Is the Future of Risk Decisioning with AI?
As AI continues to reshape industries, the next frontier is intelligent decision-making. Tejas AI is part of a larger shift toward autonomous financial systems, where data isn’t just stored and visualized, but actively interpreted and acted upon.
In this future, banks will:
- Simulate and optimize credit policies in real time
- Automatically adapt to regional market changes
- Reduce human error and operational costs
- Innovate new lending models with confidence
Tejas AI is leading this movement, turning policy complexity into a competitive advantage.
Conclusion: Can Tejas AI Become the New Standard for Risk in Banking?
If the early traction is any indication, Tejas AI is well on its way to becoming a foundational layer in the risk decisioning stack of modern banks. By transforming slow, manual processes into intelligent, AI-powered workflows, it enables banks to keep pace with today’s challenges and tomorrow’s opportunities.
In an era where precision, speed, and adaptability define success, Tejas AI doesn’t just offer a tool—it offers a new way to think about risk. And that might just be banking’s biggest competitive edge yet.