Integrate identity, device, behavior, channel, repayment, customer service, and external data sources.
AI Decisioning & Risk
Controlled AI decisioning with Dimens Copilot
Dimens Copilot connects data ingestion, feature engineering, model scoring, rules, staged rollout, human review, and performance monitoring in one controlled decisioning flow.
Build user profiles, relationship networks, device fingerprints, behavior-shift features, and channel-quality features.
Support onboarding, credit decisioning, anti-fraud, credit limits, portfolio monitoring, and post-loan strategies.
Support rule combinations, strategy orchestration, staged rollout, version management, and rollback.
Track model performance, asset quality, strategy hit rates, and operating results.
Agentic AI risk management
Bring risk signals from different operating stages into one controlled decisioning framework
Risk is not confined to the moment of approval. Channel quality, marketing promises, user behavior, service interactions, and post-loan feedback all affect asset performance. Dimens Copilot consolidates these signals while rules, permissions, and human review govern subsequent actions.
Cross-stage risk awareness
When acquisition or marketing identifies anomalous channel traffic or conversion patterns, the system can create a risk signal and trigger review; authorized policies determine whether onboarding rules change.
From recommendation to strategy flow
Recommendations from specialized AI agents enter Dimens Copilot, where rules, models, permissions, and human review determine execution.
Post-loan feedback loop
Outreach, repayment commitments, repayments, and complaints become review records that support approved updates to risk models and marketing strategies.
Why AI Matters
Digital lending in emerging markets needs explainable, monitorable, and iterative intelligent decisioning
Dimens Copilot places model scores, rules, staged rollout, and performance monitoring in one decisioning system to support traceable decision rationales and operating records.
Sparse data
Where traditional credit data is limited, device, behavior, relationship, channel, and operating data help better understand users.
Fast-changing fraud
Fraud rings, channel quality, and user behavior can change quickly, so models and strategies need regular evaluation and updates through approved version controls.
Operational complexity
Multi-country, multilingual, and multi-team operations use systems and AI to support consistent service quality.
Capability Modules
Integrate Dimens Copilot into real business workflows, not just model demos
Dimens Copilot
AI Decisioning Core
Connect identity, fraud, credit decisioning, portfolio alerts, post-loan outreach, and model governance in one strategy flow with permissioned monitoring and review.
Identity verification
Combine document recognition, liveness detection, device fingerprints, and local data sources to improve onboarding efficiency.
Abnormal relationship detection
Identify abnormal devices, fraud rings, channel anomalies, and high-risk behavior combinations.
Limit and pricing
Use scoring models, rules, and real-time decision flows to support limit, term, and pricing decisions.
Risk alerts
Monitor behavior shifts, asset quality changes, and strategy performance to identify risk earlier.
Intelligent outreach
Improve post-loan operations through customer service, outbound calls, task flows, and quality assurance.
Auditable models
Manage model versions, strategy changes, staged rollout, and performance review so decisions are traceable.