The Data Behind the Decision: How Physical Climate Risk Providers Are Reshaping Financial Planning

Starting FY 2025-26, Indian financial institutions have to submit mandatory climate-related financial disclosures. This is covered under the RBI's phased framework. 

Following this, all commercial banks, all-India financial institutions, and top and upper-layer NBFCs must begin governance, strategy, and risk management disclosures from FY 2025-26, with metrics and targets following from FY 2027-28.

Institutions that cannot quantify their exposure to floods, droughts, and cyclones face both regulatory risk and portfolio risk at once.

Why Standard Financial Data Is No Longer Sufficient

Physical climate risk describes the financial harm caused directly by extreme weather events. Floods damage collateral. Droughts push farm borrowers into default. Cyclones disrupt the supply chains of businesses that a lender has financed.

A 2025 study in the Applied Economics journal found that climate change increases non-performing loans in Indian commercial banks, with nationalised banks being more exposed than private ones. This is a practical case that shows up on balance sheets.

RBI Governor Sanjay Malhotra, speaking at a climate risk policy seminar in March 2025, noted that extreme weather, longer summers, and uneven monsoons have pushed climate risk from intellectual debate to active policy concern.

The core problem is data. Financial institutions currently work with:

• Fragmented meteorological records across different formats and frequencies

• No standardised hazard or vulnerability datasets at the portfolio level

• Limited tools to translate weather events into credit or collateral risk scores

This is a gap that physical climate risk data providers are built to fill.

RBI's Climate Disclosure Timeline: What Banks Must Prepare For

RBI intends to follow the following timeline for mandatory disclosures:

Institution Type	Governance, Strategy & Risk Disclosures	Metrics & Targets Disclosures
Commercial Banks, AIFIs, Top/Upper Layer NBFCs	From FY 2025–26	From FY 2027–28
Tier-IV Urban Cooperative Banks	From FY 2026–27	From FY 2028–29
Payment Banks, RRBs, Local Area Banks	Excluded for now	Excluded for now

Source: RBI Draft Disclosure Framework on Climate-Related Financial Risks, February 2024; Business Standard, February 2024

What Do Physical Climate Risk Data Providers Do

A physical climate risk data provider is an organisation (public, private, or a combination) that collects, processes, and delivers location-specific climate hazard data in formats that financial analysts can use. Their outputs typically include:

• Hazard data: flood frequency, cyclone tracks, drought probability, heatwave intensity by location

• Exposure data: which assets, borrowers, or regions sit within affected zones

• Vulnerability data: how sensitive a particular sector or collateral type is to each hazard

• Forward projections: how hazard intensity is expected to shift over 10, 20, or 30-year credit horizons

A climate risk analytics platform takes these raw inputs and converts them into metrics a credit committee or risk officer can actually use: stressed probability of default, projected collateral degradation, sector-level concentration risk under different climate scenarios.

The distinction from general weather data is resolution and purpose. Weather data tells you what happened or is likely to happen. A climate risk analytics platform tells you what that means for a specific loan book or investment portfolio.

How This Applies to an Indian Financial Institution Today

Consider a public sector bank with significant agricultural lending across Maharashtra, Madhya Pradesh, and Rajasthan. These states each carry different drought and flood profiles. A single national-level weather average tells the bank almost nothing useful about its actual exposure.

A physical climate risk data provider would deliver district-level or block-level hazard scores. The bank's credit team could then:

• Identify which PIN codes in its agriculture portfolio face the highest drought probability over the next crop cycle

• Assign higher expected loss estimates to borrowers in high-hazard zones

• Adjust provisioning or set covenant conditions on new lending in those areas

• Build the stress-testing outputs required under the RBI's phased disclosure framework

This is where AI climate risk assessment becomes relevant. Combining historical weather records with machine learning models allows a provider to generate forward-looking risk scores faster and at finer resolution than manual analysis allows.

Recent Advancements in Obtaining Hyperlocal Climate Risk Data

India's own Bharat Forecasting System (BharatFS), launched by the Ministry of Earth Sciences on May 26, 2025, now delivers weather predictions at a 6-kilometre grid, down to the panchayat cluster level. That level of resolution feeds directly into the hyperlocal climate risk data that financial institutions need for asset-level exposure mapping.

On May 29, 2025, RBI itself launched the Reserve Bank Climate Risk Information System (RBI-CRIS), a two-part data platform intended to give regulated entities access to standardised hazard, vulnerability, and transition risk datasets. The first part is a publicly accessible directory of meteorological and geospatial data sources. The second is a restricted portal for processed datasets available to regulated entities.

These two developments, BharatFS and RBI-CRIS, significantly raise the floor of data quality available to Indian financial institutions for physical climate risk assessment.

Where Physical Climate Risk Data Has Limits

Data quality and coverage vary significantly across India's geography. Remote districts, hilly terrain, and areas with sparse weather station networks produce less reliable hazard estimates.

Key limitations to plan around:

• Historical data gaps: Many district-level hazard records are incomplete before 2000. Projections built on shorter records carry wider uncertainty.

• Scenario dependency: Forward-looking risk scores change depending on which climate pathway is assumed. Two providers can produce meaningfully different outputs for the same location.

• Translation gap: Raw hazard data does not automatically become credit risk. A bank still needs internal capability to connect hazard exposure to borrower financials.

• Data latency: Even the best public data systems have update cycles. For rapidly evolving seasonal risks, a snapshot from three months ago may not reflect current conditions.

These limitations do not reduce the value of physical climate risk data. They argue for using it as one input in a broader risk framework, not as a standalone answer.

Wrapping Up

The question for Indian financial institutions is no longer whether climate data belongs in financial planning. The RBI disclosure framework has settled that. The more pressing question is whether institutions have the data systems to meet those requirements accurately. 

India's public infrastructure, RBI-CRIS and BharatFS, are raising the baseline. How institutions build on that baseline will shape the quality of climate risk management across the sector.

Time to Map Your Climate Exposure?

Start by identifying which parts of your lending portfolio sit in high climate-hazard zones. Public tools like RBI-CRIS and IMD's BharatFS data are now available to support that assessment.

Frequently Asked Questions

What is physical climate risk in the context of banking?

Physical climate risk refers to the financial losses that banks face because of extreme weather events. When floods damage borrowers' assets, droughts reduce farm incomes, or cyclones disrupt supply chains, loan repayments weaken and collateral values fall.

How often should financial institutions update their physical climate risk assessments?

Climate risk assessments should be updated regularly, ideally annually or whenever significant changes occur in portfolio composition, climate models, or local hazard conditions. Continuous monitoring using AI climate risk assessments helps institutions maintain accurate and timely risk management strategies.

Which sectors are most vulnerable to physical climate risks?

Agriculture, real estate, infrastructure, energy, manufacturing, and logistics are particularly vulnerable because their assets and operations are directly exposed to floods, droughts, extreme temperatures, and severe storms.

Are climate risk assessments relevant only for large financial institutions?

No. Smaller banks, NBFCs, investors, and businesses can also benefit from climate risk assessments because climate events can affect loan performance, asset values, operational continuity, and long-term financial stability.