See Risk Before It Happens, Act Before It Hurts

From portfolio management to collections, Straive integrates advanced analytics and intelligent automation to help you anticipate threats, mitigate risks, and make smarter decisions—faster.

In today’s fast-evolving financial landscape, fintechs must embrace AI and ML-driven Risk Analytics to mitigate multiple challenges with precision and speed

Whether automating credit risk assessments or leveraging ML for early warning signals, our advanced analytics capabilities can seamlessly integrate into your risk focused workflows. Our capabilities enable fintechs to evaluate borrower profiles, detect anomalies in repayment behavior, and predict default risks to make informed lending decisions, reduce exposure, and drive sustainable growth.

AI + Data = Tangible Business Impact

$6M+

Increase in credit card portfolio revenue post credit line increase

$4M+

In additional collection recoveries post AI/ML driven optimization of contact strategy

3x

Lift in sales conversions basis automation and enrichment of lead management pipelines

5%

Increase in Y-o-Y portfolio growth post implementation of expansion program within risk guardrails

250+

Financial and Statistical Models validated enabling SR11-7 compliance

Our Perspective and Solutions

Straive’s Solutions Redefine Proactive Protection

Emerging Fraud Landscape

Emerging Risk Landscape

Rapid proliferation of new players and participants in the market is altering the risk landscape

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Case Studies

Discover how we are  addressing real-world risk challenges for banking and financial institutions

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Our Integrated Framework

Comprehensive risk expertise across Analytics, MLOps, Model Governance, and Data Operations

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Today’s Battle Lines

Major Challenges in Risk Management

Emerging Business Models:
Rise of BNPL, Installment Plans lengthens recoveries and enhances embedded risk

Model Risk & Explainability:
AI/ML models need to be transparent and explainable to mitigate regulatory concerns, reduce bias, and enable governance

Evolving Impersonation Tactics: Synthetic IDs, document forgery, and impersonation have become common in digital lending creating friction for genuine users

Balancing Customer Experience: Excessive adverse actions like limit reductions, warning letters hurts customer trust requiring a balance for seamless user experience

Data Fragmentation & Complexity: Excessive adverse actions like limit reductions, warning letters hurts customer trust requiring a balance for seamless user experience

Risk Infrastructure Scalability: Legacy systems often lack the flexibility and speed needed for real-time decisioning

Unleash Strategic Risk Insights & Accelerate Smarter Decisions

AI/ML-Driven Insights

  • Detect hidden risk patterns and drive faster, more accurate decisions across credit, liquidity, and operational domains.

Robust Data Platforms

  • Build resilient pipelines that cleanse and transform data for reliable risk models and analytics.

Real-Time Risk Alerts

  • Modular frameworks for credit scoring, liquidity forecasting, and stress testing for fintechs, banks, and insurers.

Scalable MLOps & Model Governance

  • Automate, monitor, and validate models with transparency and compliance.

Regulatory-Ready

  • Align with Basel III, IFRS 9, and CECL through explainable AI and audit-ready reporting.

Domain & Tech Expertise

  • Deep financial services knowledge combined with advanced analytics for context-rich insights.

The Risk Landscape Has Changed. Have Your Models?

A five-year journey showing how post-pandemic dynamics, subprime growth,
and GenAI adoption have reshaped the way fintechs must assess and manage risk.

Explore Case Studies on
Risk Analytics

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