Maloni — applied AI for lending and diagnostics
Maloni develops applied AI systems and software for lending workflows (including scoring and collateral-backed loans) and AI-assisted diagnostics.
- Workflow mapping: intake → decisioning → review → monitoring
- Structured outputs: scores, explanations, and reports for review
- Governance: documentation, audit artifacts, and evidence
Key pages
Start with SolutionsCapabilities
Decision support workflows
Define inputs, outputs, and decision points for assisted human review.
Data ingestion and feature pipelines
Transform raw data into standardized features with versioned lineage.
Model evaluation and monitoring
Evaluate performance and drift; monitor and alert on changes over time.
Governance and audit artifacts
Produce documentation and evidence suitable for internal governance.
How Maloni engages
Maloni typically delivers decision-support systems as a scoped workflow: define inputs/outputs, implement models and evaluation, then integrate monitoring and governance artifacts.
Delivery steps
- Discovery: scope, constraints, data sources, and success criteria.
- Pilot: baseline, evaluation, and review workflows for decision outputs.
- Integration: deployment, monitoring, and operational handover.
Typical deliverables
- API-ready outputs (scores, explanations, structured reports).
- Evaluation evidence (test sets, metrics, drift checks).
- Governance artifacts (documentation, logs, change records).
Typical stakeholders
Risk/credit, product owners, compliance/governance, and engineering/data teams.
Trusted AI Technology Partner
Maloni combines deep financial services expertise with cutting-edge AI technology to deliver solutions that meet the rigorous standards of regulated environments.
Solutions
View allAI Lending
Applied AI for lending workflows such as intake, scoring, underwriting, and monitoring.
AI Diagnostics
Applied AI for diagnostic-adjacent workflows where inputs are analyzed to produce structured outputs for review.
AI Scoring System
Credit scoring and risk assessment with explainability outputs for review.
Phone Collateral Loans
Workflow for loans backed by mobile devices as collateral.
Car Collateral Loans
Vehicle-backed loan workflow, including valuation and LTV calculation.
AI Car Diagnostics
Analyze vehicle-related inputs and generate structured outputs for review.
AI Tongue Diagnostics Scanner
Image-based analysis workflow that generates a structured report for review.
Technology
The platform is implemented on Microsoft Azure. AI capabilities can be delivered using Azure AI Foundry and Azure OpenAI Service.
Use cases and projects
View allFrequently Asked Questions
What AI techniques does Maloni use for credit scoring?
We employ ensemble methods including gradient-boosted decision trees and neural networks, trained on historical loan performance data. Models include SHAP value explanations for each prediction, enabling human review and regulatory compliance.
How long does implementation typically take?
Typical timeline: 2-4 weeks for discovery and scoping, 4-8 weeks for pilot development and evaluation, and 2-4 weeks for production integration. Total: 8-16 weeks depending on data availability and integration complexity.
Is Maloni's AI compliant with EU regulations?
Yes. Our systems support GDPR data rights, model explainability for AI Act compliance, and comprehensive audit logging for regulatory review. We emphasize human-in-the-loop workflows for automated decisions per GDPR Article 22.
What data is required to get started?
Minimum requirements include applicant demographics, income verification, and credit bureau data. Optional data that improves accuracy: bank statements, collateral valuations, and behavioral data. We can work with your existing data infrastructure.
How do we get started with Maloni?
Contact us via phone (+420 775 625 664) or email (maloni@outlook.com) to discuss your use case, constraints, and data availability. We'll propose an implementation approach and realistic timeline based on your specific needs.
Insights
View allArticles and notes describing concepts, implementation patterns, and governance considerations.