Tech Mahindra launches i.GreenFinance for AI-driven green loan compliance
Tech Mahindra has introduced i.GreenFinance, a platform that manages the end-to-end lifecycle of green and sustainability-linked loans. It brings AI, advanced analytics, and Amazon Web Services (AWS) infrastructure together to help banks, asset managers, and lenders meet fast-rising disclosure and assurance demands.
The focus is simple: standardize ESG data, automate assessments, and tie loan disbursements to verified sustainability milestones with real-time monitoring. For finance teams, that means fewer manual checks, clearer audit trails, and faster decision cycles.
What the platform does
i.GreenFinance centralizes ESG data management and automates sustainability assessments and reporting. Loan disbursements connect to documentary proof and milestone verification, building a defensible line from commitment to outcome.
Lenders can tune business rules across 15+ industry sectors to match internal policies, risk models, and sector nuances. The platform supports multi-jurisdiction requirements and updates as standards change.
- ESG data operations: ingestion, normalization, and tracking across counterparties and facilities.
- Automated assessments: policy rules applied to sector-specific metrics and thresholds.
- Milestone-linked disbursements: funds released against verified sustainability evidence.
- Audit-ready reporting: per-loan artifacts suitable for internal audit and regulators.
- Configurability: adjustable business rules across more than 15 sectors.
- Cloud-scale deployment: built on AWS for security, availability, and governance needs.
Why this matters for lenders and investors
The biggest blockers in green lending have been fragmented ESG data, inconsistent rules across markets, and uneven evaluation models. As Sandeep Chandna, Chief Sustainability Officer at Tech Mahindra, noted, the platform aims to address these issues with "a unified, transparent, and intelligent platform that automates complex assessments, streamlines data aggregation, and delivers verifiable sustainability reporting."
In practical terms, this can help scale portfolios without stretching compliance teams, reduce greenwashing risk, and improve pricing confidence. It also supports faster onboarding of borrowers as documentation and evidence flows become more structured.
AWS under the hood
The platform uses AWS analytics and generative AI to support data-driven lending decisions aligned to ESG criteria. According to Satinder Pal Singh, Director of Solution Architecture at AWS India and South Asia, the collaboration shows how cloud infrastructure can enable institutions to meet sustainability goals while delivering more value to customers.
Compliance and reporting
Each loan generates audit-ready documentation tied to disbursements and milestones. That structure can streamline submissions as more jurisdictions expand rules for traceable, measurable disclosures.
If you report under emerging global baselines, this approach can sit alongside frameworks such as the ISSB sustainability disclosure standards and the EU's Taxonomy for sustainable activities.
Global reach and updates
i.GreenFinance targets institutions in mature markets with established climate rules and in emerging markets where green lending is gaining pace. Tech Mahindra states the platform will be updated as ESG standards and reporting expectations change, reducing the need for custom rebuilds.
What finance teams can do next
- Map current green and sustainability-linked loan workflows and pinpoint manual choke points.
- Define sector-specific KPIs and evidence requirements that trigger disbursements.
- Pilot with one sector (e.g., renewables, real estate, transport) and standardize the playbook.
- Set model governance for AI-supported assessments, including overrides and second-line checks.
- Align reporting outputs to internal audit and regulator-ready formats before scaling.
- Integrate with core lending systems to avoid duplicate data entry and reconcile faster.
If you're upskilling teams on AI for lending, risk, or reporting, explore practical resources here: AI tools for finance.
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