The building blocks of AgriStack – State farmer registry

Posted on by Adityaraj

 

This blog builds upon our previous exploration of . Here, we address a fundamental question that affects millions of people: Who is a farmer, and how much land do they own? This blog further examines why India needs a unified farmers’ registry and how this registry is being created.

Countless farmers in India define their entire livelihood in terms of their relationship with the land. Yet, many cannot prove this relationship when it matters the most. Each government program, loan application, or support program demands fresh documentation, a cycle of manual verification that is slow, costly, and frequently ineffective. AgriStack offers a pathway to transform this, anchored on foundational registries, including the state farmer registry.

The farmer registry consists of unique farmer IDs assigned to all the owners of agricultural land parcels in the land records, often referred to as the record of rights. The farmer ID is a 10-digit number followed by a checksum digit, and it contains the farmer’s key details. These include the farmer’s name, their Aadhaar number, the plot area, and the plot number, among others, of all the land parcels owned by the farmer across the state. The farmer registry links the farmer ID with the land parcels to verify the farmer’s identity.

Currently, the farmer registry only includes land-owning farmers, despite India’s agricultural sector also comprising numerous tenant farmers and sharecroppers. It does not include those involved in allied activities, such as livestock, dairy, or fisheries. However, the Government of India plans to expand the registry to include them as well, which will ensure that all types of farmers are recognized and can access relevant government programs and services.

A comprehensive farmer registry is essential because, without it, neither the central nor the state governments have a clear understanding of who qualifies as a farmer. This leads to inefficiencies in policy planning, resource allocation, and subsidy distribution, among other areas. The struggle is even more intense for small and marginal farmers, as they face difficulties when they seek to obtain a digitally verified land ownership certificate. The absence of this certificate limits their ability to access agricultural services. This lack of reliable data also weakens the delivery of key agricultural services, such as insurance payouts, input subsidies, and credit access.

States do not currently link farmer databases to official land title records, which leads to incorrect identification of the farmers and the exact size of their land. The farmer registry will connect directly to state land title records so that there is consistency in farmer records and any change in land ownership is automatically updated for each farmer.

To address this, the government has outlined a six-step process for creating the farmer registry:

 

State readiness   

Digitized land records serve as the foundation of the farmer registry. As a first step, a joint committee comprising of members from central and state governments is formed to ensure proper oversight. After this, the state government appoints a state-level nodal officer and technical coordinator to manage operations and technical needs. The government also establishes a project management unit to monitor progress and ensure adherence to timelines.

State land title records data provisioning   

Next, the state assigns unique farmland plot IDs to each farmland plot in the land title records to enable accurate mapping. The majority of the states in India have developed and integrated a unified land API to transfer land title records smoothly. The unified API ensures the consistency and reliability of information across the farmer registry.

Bucketing

The state then consolidates land records within each village. It groups land parcels that belong to the same farmer for easier identification and verification. The state links data from multiple databases that are seeded with the national digital ID or Aadhaar to confirm farmer’s identity. These databases include the PM-KISAN, the cash transfer program, and the PM-FBY, the insurance program for farmers among others. This step ensures that the state can categorize lands accurately based on program data and minimizes duplication of efforts during field activities. Post bucketing, each farmer is assigned a “temporary farmer ID.”

Preparation for field activity

Pilot districts are selected to test and model the registration process, supported by trained master trainers. They lead implementation and build capacity among the field staff. The states conduct awareness campaigns to ensure widespread understanding and participation among farmers. These campaigns inform farmers about the registry, its advantages, and the registration process.

Land claim processing and farmer ID creation

Farmers claim their land buckets through self-registration, assisted registration, or by attending government camps. After registration, a farmer receives an enrolment number to monitor the status of their application in the farmer registry. State-specific policies are followed to verify the enrolment application. The policies focus on criteria, such as the name match score (NMS) and approval guidelines. NMS is essential to determine whether auto-approval is possible.The states categorize accuracy into three levels: excellent (80–100) for auto-approval, average (31–79) for manual verification, and poor (0–30) for correction before proceeding. A Farmer ID is then generated within 24 hours. Applications that do not qualify for auto-approval are subject to an on-field manual review.

Post go-live 

After the registry is operational, the state should keep land title records data updated with the latest information on land ownership. Ongoing system oversight and regular enhancements ensure the accuracy of data and the effectiveness of the farmer registry over time.

The state farmer registry will build a complete farmer profile once it is integrated with the georeferenced village maps and crop-sown registry. However, India faces several challenges in developing a unified farmer registry, as land is a state subject.

The following points highlight some of these key challenges.

  • Variation in the manner of maintenance of land records and taxonomy

There is significant variation in how states maintain and record land data, making it difficult to create a standard taxonomy or data format. For instance, the survey number is called “surnoc” in Karnataka and “khasra” in Uttar Pradesh. States also differ in how they record names and land details; some include aliases or salutations in the name field. Similarly, land IDs are recorded in different formats, such as 12/1 or 12-A. These inconsistencies make it challenging to electronically integrate land records, ensure data accuracy, and develop interoperable digital systems.

  • Land title records are not updated in real time

The level of land records digitization and its maturity differ across states due to incomplete, inconsistent digitization and delays in updating land title records. In many cases, mutations are not linked to the digital system, causing mismatches between physical and online records. Often, the next of kin do not update ownership details after a death, and land use changes, such as conversion from agricultural to non-agricultural, are not recorded. These gaps result in outdated and unreliable land records, making accurate verification and integration difficult.

  • Field verification and consent collection from the farmers

State government authorities, such as Agriculture Extension Officers, Village Revenue Officers, etc., struggle to locate farmers for field verification and collect their consent due to migration. Many people from nearby cities purchase agricultural land as an investment and are not physically present in the village. Moreover, revenue officers also do not know who owns some land parcels. These issues result in unverified farmers in the farmer registry.

  • Aadhaar-linked challenges:

A farmer’s Aadhaar number is used to link all the land parcels they own. However, challenges arise when some farmers do not have an Aadhaar, such as minors or elderly individuals unable to enroll, or when their Aadhaar details, like mobile number or address, are outdated. These gaps make it difficult to link and verify land ownership records accurately.

These issues hinder efforts to verify and update the identities and addresses of farmers when state governments create the farmer registry. 

 

In summary, the farmer registry improves transparency and targeting, but advanced features like personalized advisory services, better market access, and customized financial products are possible only when it is linked with georeferenced village maps and crop-sown registries.

Together, these form the complete building blocks of AgriStack and power a more inclusive digital ecosystem for agriculture.

  • Record of Rights (RoR): It is a document that contains essential information about land ownership, usage rights, and legal claims. It helps establish clear property rights, which makes it easier to resolve disputes, conduct property transactions, and assess land taxes.
  • Aadhaar is India’s foundational ID system for residents. It is a 12-digit number linked to biometrics and used to authenticate identity for a wide range of services.
  • Mutation means the recording in the revenue record of transfer of rights of the property from one person to others.

 

AgriStack: A DPI approach to transform Indian agriculture

Posted on by Adityaraj

An invisible crisis is strangling Indian agriculture, a sector that sustains about 40% of the country’s people and contributes 18% to its GDP. Millions of India’s farmers remain trapped in a system that does not recognize them, even though agriculture remains their main and often only identity. Farmers work tirelessly to ensure that the country’s diverse population has access to food and nutrition. Yet, it faces ongoing challenges that hold back its full potential. Low productivity from outdated farming methods, degraded soil, and fragmented landholding limit the benefits of scale. Additionally, farmers face post-harvest losses due to poor storage and weak market linkages. Price fluctuations and exploitation by middlemen also affect their earnings and financial resilience.

Tackling these issues requires stronger systems that begin with better information on farmers and their activities. Farmers often struggle to prove their identity as cultivators, the land they own, or the crops they grow, because verified and trustworthy records are missing. Databases are static, fragmented, and vary across states, which leaves farmers dependent on repeated manual checks. Without reliable real-time data, every new scheme or service requires fresh verification, making access slow and costly. This not only delays support but also increases the expense for both government and private providers. As the country grapples with climate change, population growth, and resource scarcity, digital technologies could be a transformative force.

The Indian government recognized the need for modernization and has introduced several initiatives to use technology in agriculture, one of the most significant of them being AgriStack. MSC (MicroSave Consulting) played an active role throughout this journey—from building digital registries and developing consent frameworks to piloting applications, ensuring that the system remains inclusive and that technology adoption delivers real, tangible benefits to farmers.

AgriStack is a federated digital public infrastructure (DPI) that comprises registries, datasets, application programming interfaces (APIs), and IT systems. It integrates digital databases and technologies to answer three core questions at the center of most issues that plague the agriculture sector:

  • Who is a farmer, and what is the extent of land they own?
  • Where are those land parcels located?
  • What crops does the farmer grow in each season on the land parcel?

The Government of India (GoI) has created three foundational registries to answer these three questions: The state farmer registry, the georeferenced village maps registry, and the crop sown registry. These registries are the foundation that integrates stakeholders and enhances Indian agriculture through data-driven digital services. MSC supported the design and validation of these registries by collaborating with farmers, agriculture and revenue departments, and technology partners to ensure their design was practical, scalable, and responsive to on-ground realities.

  1. State farmer registry: This registry records details of all the farmers in the state. The state farmer registries then federate at the central level and adhere to the defined standards to create a unique farmer ID. It is a crucial building block among the three registries. The ID creates a trusted database of farmers that ensures government support, subsidies, and financial aid target the intended beneficiaries. The system assigns each farmer a unique Farmer ID, which is a digitally verifiable credential and a functional ID based on Aadhaar as per the InDEA 2.0 (India Digital Ecosystem Architecture 2.0) framework. The farmer registry uses the revenue records or Records of Rights (RoR) data foundation.[1] The system dynamically links the registry to farmers’ land records, and the system updates the ownership of the land parcel based on the mutation of the land records. The registry does not confer land ownership rights. It solely identifies farmers as beneficiaries of various agricultural services.
  2. Georeferenced village maps registry: This registry combines the physical village cadastral maps with geographic information system (GIS) technology to answer the second question. It integrates the land parcel information contained in the revenue records with geographic coordinates. This allows the registry to spatially represent and digitally record cadastral boundaries and related attribute data on a map. This registry maps the geographical locations of the farmers’ plots to enable accurate land tracking for customized services.
  3. Crop-sown registry: The registry records information on various crops that farmers sow every season for all agricultural plots across the country. It maintains a historical plot-level record of crops that farmers plant in each cropping season and creates a comprehensive record of plot-level agricultural activity. It seeks to improve and streamline the previously prevalent paper-based methods of crop survey on a sample basis, as it introduces a smartphone-based digital survey on a census basis.

The diagram below shows how the AgriStack will function once the registries are interlinked:

The AgriStack system is based on the InDEA 2.0 principles, which include ecosystem thinking, reusable building blocks, open API standards, open-source development, and national portability. The system seamlessly integrates digital platforms across sectors to promote interoperability, innovation, and user-centric service delivery in India’s digital public infrastructure.

The AgriStack initiative is designed with a vision to simplify farmers’ access to agricultural services, which includes affordable credit, high-quality farm inputs, personalized advice, and convenient market linkages. It also seeks to streamline government planning and implementation of farmer-centric programs. The three core registries exist as the foundational building blocks of the AgriStack. Besides the three core registries, other major components of the AgriStack architecture (see Figure 1 below) include the data exchange layer called the Unified Farmer Service Interface (UFSI), consent manager, national agriculture applications, state applications, and private sector services.

IDEA concept paper.

Apart from the three core registries, the AgriStack architecture also integrates agricultural data from multiple sources, which include government schemes, private sector partners, market prices, weather information, and research repositories. AgriStack integrates existing systems and consolidates various services to enable farmers to access suitable assistance at the right time. The UFSI helps keep all farmers’ information organized and private, with a consent manager that ensures that data is only used with the farmer’s agreement.

The AgriStack operates as a federated system that ensures that ownership of the three registries remains with the respective states. The system has a strong focus on privacy and adheres to the Digital Personal Data Protection (DPDP) Act of 2023. Per the strict guidelines of the DPDP Act, authorized data seekers can only access data after they obtain explicit consent from the farmers.

The AgriStack follows the UIDAI’s regulations and encrypts and securely stores sensitive data, which includes Aadhaar details, in designated vaults. States strictly adhere to the guidelines established by the Ministry of Electronics and Information Technology (MeitY) when they manage and store data to strengthen data security further. This strong consent management framework ensures data privacy, security, and transparency within the AgriStack ecosystem. MSC played a facilitative role in shaping the architecture by first supporting the definition of data schemas and the incorporation of Metadata and Data Standards (MDDS) to ensure uniformity across states, then contributing to the design of consent flows and interoperability standards that make AgriStack usable across multiple stakeholders.

Once the AgriStack is fully developed and has access to data from public and private databases, it will create a single digital ecosystem for the agricultural sector and enable digital solutions across the entire agriculture value chain (see Figure 2). Farmers in Andhra Pradesh, Bihar, Kerala, Maharashtra, and Odisha will be able to use their digitally verifiable farmer ID issued under the AgriStack to access pre-approved, paperless credit from various public sector banks.

It will provide farmers with easier access to government programs, advice, and markets. At the same time, the government can improve the efficiency of targeted interventions. Based on the principles of AgriStack, the Government of Bihar has developed the Bihar-Krishi application as a one-stop digital platform to empower farmers with easy access to vital agricultural resources and services. Private companies can also make better data-based decisions and have more scope to develop new ideas.

We will go into further detail about the creation of the three foundational registries in the following blog posts. The first, “Building blocks of AgriStack: State farmer registry,” will explain how and why it is important to create a unified farmer registry in India. The second, “Building blocks of AgriStack: Georeferenced village maps registry,” will detail the creation of geo-referenced digital maps. The third, “Building blocks of AgriStack: Crop sown registry,” will cover the significance of a crop sown registry and how to develop one.

 

How women dairy farmers in Bihar are building fairer and stronger markets through collective action

Posted on by Adityaraj

A quiet revolution is brewing in the small village of Manikpur in India’s Bihar state. Ruby Devi, a 34-year-old woman and a mother to four children, leads a story of empowerment and transformation. Her vision now reshapes the economic landscape for women dairy farmers in her community. What began as her effort to secure a fair price for milk has grown into a thriving enterprise that employs more than 30 women dairy farmers and connects them directly to formal markets. Her journey reveals how targeted financial support and collective action can improve the lives and livelihoods of entire communities.

Structural barriers that women dairy farmers face

India is the world’s largest milk producer. The country generates around 239 million tons of milk annually and provides livelihood opportunities to nearly 80 million people. Women perform nearly 70% of the work in India’s dairy sector as they feed and care for livestock.

Bihar, a state that produced around 12 million tons of milk in 2024, holds significant potential for dairy-led growth. Yet, the state’s dairy sector faces unique challenges. Although dairy farming is a key part of the rural economy, it remains largely unorganized and dependent on small-scale farmers, most of whom are women. These women grapple with systemic barriers that limit their potential. They are often forced to sell milk to intermediaries who offer unfair prices.

Limited access to finance further hinders the growth of these women. They are unable to invest in productive assets, such as livestock, quality feed, or veterinary services. Poor infrastructure, such as limited cold storage and testing facilities, further compounded the problem. As a result, Bihar’s dairy industry remains underdeveloped and inefficient. For women like Ruby Devi, the absence of fair pricing and resources created a cycle of poverty that proved nearly impossible to break. However, Ruby, a member of a self-help group (SHG), had a vision for change that would improve her life and have a ripple effect on the entire community.

A vision for change  

Ruby’s journey began with the bold decision to cut out the intermediaries who had long controlled the milk market in her village. She created a direct market for the milk collected by the women dairy farmers in her community.

Ruby wanted to expand her dairy enterprise but required a larger amount of capital than what the SHG group loans could provide. Ruby accessed a  MUDRA loan under the Pradhan Mantri MUDRA Yojana through an enterprise financing initiative supported by JEEViKA and MSC. This access to personal credit marked a turning point. She opened a milk collection center and invested in two buffaloes, an ambitious move in a rural economy where women frequently struggle to access resources for enterprise growth.

Before Ruby’s intervention, Manikpur’s women dairy farmers had no choice but to sell their milk to local vendors who paid just INR 40 (USD 0.48) per liter. This low, unfair price was a direct result of the inefficient supply chain, where the intermediaries absorbed a large share of the profits. Ruby recognized the exploitative nature of this system and decided to take action. She eliminated these intermediaries and allowed farmers to sell directly to her milk collection center.

The milk collection center is equipped with weighing scales and basic testing kits that enable transparent fat-content testing and fair pricing. The center serves as a direct milk procurement point within the village and allows the women dairy farmers to sell milk locally and retain a greater share of their earnings. Women also receive immediate cash payments after testing, which ensures transparency and trust.

The impact has been substantial. Farmers now earn INR 55 (USD 0.66) per liter from their previous earnings of INR 40 (USD 0.48), which represents a 30% increase in their income. This improvement also fueled significant business growth for Ruby. Her monthly turnover increased by more than 400%. It increased from INR 32,093 (USD 366) to INR 160,380 (USD 1,829). More than 30 women farmers now supply milk to her center. The initiative has strengthened the confidence and bargaining power of women in the area and provided them with a sense of financial stability that once seemed unattainable.

The role of collective action

Ruby’s success was not an isolated achievement. This effort focused on the power of collective action among women dairy farmers to create a stable market and improve the dairy supply chain in Bihar.

MSC helped women dairy farmers form milk cooperatives, where they could pool their resources and share knowledge. This collective action allowed them to establish five regional milk collection centers and address the fragmented nature of the dairy supply chain. The farmers worked together and could negotiate better prices, eliminate the exploitative role of intermediaries, and gain improved market access.

Through collective action, the farmers also connected with the State Milk Cooperative Federation, which provided valuable services, such as affordable cattle feed, vaccination, and artificial insemination. This strengthened the network and resources available to dairy farmers to ensure sustainable growth for their enterprises.

How one woman’s success transformed a community

Ruby Devi’s story reflects the strength of community-driven change. Through MSC’s intervention, Ruby and the other women in her cooperative have improved their incomes and gained greater financial independence. Many other disempowered women will learn from and follow their example.

The success in Manikpur demonstrates the potential for broader transformation across Bihar, home to more than 1 million women entrepreneurs, many of whom are members of self-help groups. Ruby’s story is one among many such examples of how access to dairy financing and collective action can unlock the economic potential of rural women and strengthen entire communities.

A future of opportunity

India’s White Revolution 2.0 calls for a dairy sector that truly includes all and empowers the country’s women. Ruby’s story offers valuable lessons that rural women can replicate across rural India. With targeted credit, local infrastructure, and technical guidance, women can strengthen dairy value chains and create dignified livelihood opportunities for others.

However, systemic challenges, such as unequal access to finance, limited control over assets, and a lack of formal market linkages, continue to hold women back. Institutions, cooperatives, and government programs must work together to address these gaps. Government initiatives, such as, need to help all those who are stranded by a lack of opportunities and structural help across various sectors.

Ruby Devi’s story in Manikpur demonstrates what becomes possible when systems recognize and support women. The transformation she sparked reveals that when women have the tools and trust to lead, change extends far beyond individual enterprises. With the right support, rural women can drive the next phase of India’s dairy growth.

A digital key to women’s credit: Integrating SHGs with India’s finance system

Posted on by harshita

As India deepens its journey toward inclusive growth, the next leap may lie in recognising the financial power of its women collectives. In this compelling article, Nishant Kumar, Global Lead – Startup Innovation and Acceleration at MSC, and Abhishek Varshney, Senior Lead – Partnerships at Sahamati, explore how integrating self-help group (SHG) records with the Account Aggregator framework can bridge a long-standing gap between grassroots enterprise and formal finance. Drawing on their rich experience in financial inclusion and digital innovation, they illustrate how this integration can transform SHG members from programme beneficiaries into financially visible, creditworthy individuals—unlocking access to credit, insurance, and investments, and setting the stage for a more equitable financial ecosystem.

A Digital Key to Women’s Credit: Integrating SHGs with India’s Finance System

India sits on a huge financial paradox. More than 100 million women participate in the world’s largest microfinance project through self-help groups. While self helpgroups (SHGs) receive support from the National Rural Livelihoods Mission (NRLM) and participating banks, internal transactions data history among SHGs and members remains invisible to the formal banking system. This financial data lies trapped in government databases and is missed while measuring the creditworthiness of the SHG members by banks, insurers, or FinTechs eager to serve them.

This data can be made accessible by integrating SHG records with India’s Account Aggregator (AA) framework, which promises to transform financial inclusion by shifting access to credit and services from mere program membership to performance-based criteria.

SHGs have evolved far beyond their humble origins. Today, these groups have formed sophisticated multi-tier institutions with formal governance structures: Village Organizations (VOs), which are groups of SHGs that work at the grassroots level, and Cluster-Level Federations (CLFs), which operate at the block or sub-district level. The National Rural Livelihoods Mission (NRLM) supports these institutions through its digital platform, LokOS—a management information system that records savings, loan repayments, attendance, and training metrics across more than 9 million SHGs that have collectively accessed loans worth INR 2.54 trillion.

Yet, this treasure trove of financial behavior data remains locked away. NRLM-linked banks extend loans to borrowers based on historical performance. But there is an opportunity for members to showcase their SHG history to financial institutions to access additional support if needed.

Consider Lata Devi, a weaver from rural Jharkhand. She has faithfully repaid three internal SHG loans and maintained regular savings through her SHG for years. To any lenders, she represents an excellent credit risk. To the larger financial system, she does not exist.

India’s AA framework, launched by the Reserve Bank of India (RBI), enables individuals and institutions to share their financial data across entities securely and with consent. By onboarding NRLM (via LokOS) as a financial information provider (FIP), a source of verified financial data, the SHG ecosystem could plug into this digital infrastructure.

This integration would enable consent-based data sharing between platforms that hold SHG records, such as LokOS, and those that deliver services like banks or government programs. It will bridge a critical gap in the ecosystem as paper trails turn into digital credentials that unlock formal financial access.

We return to Lata’s case here. With AA integration, she could share her SHG transaction history with a lender to secure working capital for her loom or with an insurer to enroll in an insurance plan tailored to her income cycle. She can become an independent financial actor, not just a beneficiary of group-based lending.

The benefits extend beyond individuals. Well-governed VOs and CLFs can use verified performance data to access market-based credit and diversify funds beyond government grants. This opens the road to partnerships with social impact investors and others who can now underwrite institutions based on objective metrics rather than subjective assessment.

Over time, verified SHG and federation-level performance data could be aggregated into standardized credit scores. Much like the Grameen Credit Score model, these scores would provide investors and lenders with an objective, risk-based lens to underwrite community institutions—moving beyond anecdotal assessments to data-driven trust.

Integration will require combined efforts. On the regulatory side, current AA rules restrict financial information providers to regulated entities, leaving out institutions like NRLM. A policy exception will be critical. On the technical front, group accounts demand new consent workflows, and LokOS records—often manually entered—may require stronger validation. Finally, trust must be built through privacy safeguards, opt-out choices, and robust grievance redressal. Without these, the promise of SHG–AA integration could falter.

Success demands concerted action from multiple stakeholders. The NRLM and the Ministry of Rural Development can champion pilot integrations in high-performance states. Sahamati can facilitate the development of consent workflows for community-based organizations.

Financial providers should come forward to leverage the data to underwrite SHG-tailored products through structured data. Meanwhile, technology partners should build multilingual interfaces for field agents and SHG members.

India’s SHG–AA integration is not just a financial innovation, but a social innovation. It marks a transition from eligibility to accountability. For millions of women like Lata, it means moving from surviving to thriving. For India, it offers a chance to set a global benchmark in inclusive finance—demonstrating how digital infrastructure can unlock the power of community institutions at scale.

This article was first published on “The CSR Universe” on 5th Nov 2025.

29th Conference of the Parties: Expectations, outcomes, and debates around major agenda items

Posted on by harshita

This article analyzes the expectations and outcomes of COP 29 held in Baku, Azerbaijan, focusing on the new climate finance goal, adaptation progress, and loss and damage mechanisms. It highlights how negotiations often compromise justice-based priorities of developing nations, particularly on finance quality and equity. The piece underscores the urgency of restoring trust, ambition, and fairness in global climate governance to keep the 1.5°C goal alive.

This article was first published on “CPRD” on 20th September, 2025.

From data to SupTech: A phased approach for smarter regulatory transformation

Posted on by harshita

The volume of data worldwide is exploding. The IDC projects that by 2025, all the world’s data will reach a volume of 175 zettabytes or 175 billion terabytes, which would make manual supervisory processes untenable. This data comprises information stored in data centers, mobile towers, branch offices, PCs, smartphones, and IoT devices, and is collectively referred to as the datasphere.  

Today, regulators struggle to keep pace with the speed of financial data. The growing volume and complexity of data require more than manual processes. They demand robust and adaptable systems that enable smarter supervision. MSC’s Data Maturity Framework seen below provides a structured roadmap to help regulators progress from basic data collection to integrated, data-driven supervisory systems, enhancing risk detection, operational efficiency, and preparedness for future regulatory challenges. As discussed in our previous blog, SupTech begins with the creation of strong and flexible data foundations, which is a crucial first step in the effective implementation of supervisory technology. 

Foundations of a good data system  

Robust data systems are essential for effective SupTech, as they enable timely collection, secure storage, and seamless integration of high-quality data needed for proactive, risk-based supervision. Structured data supports advanced analytics, while sound governance and cybersecurity ensure compliance and protection against threats. We can evaluate the effectiveness of a good data system across multiple stages, as seen below, each of which is vital to enable scalable and intelligent SupTech deployment. 

Before we discuss the three main dimensions of data collection, standardization, and storage, we must understand that some basic pillars span every phase of the data life cycle. Data granularity, data governance, and data security and privacy are not discrete phases, but ongoing facilitators that form the foundation of how well data is gathered, processed, managed, and consumed. Granularity ensures data is detailed enough for risk-based supervision without being overwhelming. Governance frameworks provide transparent guidelines for acquisition, validation, and responsible sharing, which promotes consistency and accountability. 

Also crucial is for stakeholders to ensure data privacy and security at all maturity levels. Since supervisory data typically contains sensitive financial and consumer-level information, cybersecurity, encryption, and privacy-by-design must be present from start to finish. Regulators at all stages must ensure that these standards are met to avoid breaches, maintain confidentiality, and uphold trust. These cross-cutting foundations work in parallel with technical pillars to define the long-term effect of each SupTech endeavor. 

If institutions intend to implement SupTech effectively, they must first assess their data maturity on these pillars, identify gaps where they exist, and align their solution with both their current and future needs. 

Data collection 

As financial sector supervisors evolve from basic to intermediate and advanced data collection systems, their capabilities must keep pace. At the basic level, data is submitted by regulated entities to regulators manually via tools, such as Google Forms or MS Excel over email, which requires minimal IT skills and basic protection, such as antivirus software and password controls. 

At the intermediate level, supervisors have been adopting structured digital reporting through bulk-upload web portals and traditional APIs. The Bank of Ghana implemented its ORASS platform to enable API-based reporting, as reported publicly by the central bank, while NAMFISA, Namibia’s nonbank regulator, uses its statutory ERS web portal for regulated entities. Separately, the Bank of Namibia operates its own reporting arrangements and announced an automated regulatory reporting system in 2023. These require skilled IT staff and safeguards, such as the implementation of HTTPS (to ensure secure, encrypted communications), API gateways, and audit logs. 

At the advanced level, supervisors use real-time APIs, streaming tools, such as Apache Kafka, AI and NLP platforms, such as spaCy or Amazon Comprehend, and middleware, such as MuleSoft and Apache NiFi for integration across systems. For example, the Bangko Sentral ng Pilipinas implemented a real-time API solution to improve data submission. These setups demand strong cybersecurity and legal frameworks for consent, provenance, and live supervisory oversight. 

Data standardization

Through MSC’s extensive work with several central banks, including projects in Africa and Asia, we have observed that the adoption of data standardization tools and automated validation aligns with international best practices and accelerates SupTech maturity. At the basic level, reporting relies on MS Excel templates, manual validation via macros, and email submissions, primarily supported by spreadsheet analysts and IT staff. 

In the intermediate stage, regulators shift to structured formats, such as XML or XBRL, and use schema validators and submission portals to streamline reporting. For example, the Central Bank of Ireland’s ONR platform enables firms to upload XBRL files directly, which improves accuracy and efficiency by involving schema experts and governance teams. 

At the advanced level, institutions deploy automated validation engines, NLP pipelines for unstructured document analysis (e.g. parsing audit reports), and global standards, such as ISO 20022, which have found increasing use in cross-border payment reporting frameworks. German Bundesbank’s NLP-based prospectus parser automates the interpretation of PDF documents with more than 90% accuracy.  

Institutions have also adopted the legal entity identifier (LEI) system maintained by GLEIF, alongside ISO 20022, to ensure clear entity identification in global reporting. The Bank of England mandates the inclusion of the LEI in FI-to-FI payments through its CHAPS high-value payments system, effective 1st May 2025, as publicly announced by the Bank of England. 

These advanced processes demand a skilled blend of NLP engineers, regulatory data analysts, and compliance technologists to take full advantage of automation, standards, and data intelligence in regulatory oversight. 

Data storage  

At the basic level, data is stored locally, on USB drives, shared network drives, or on-site servers, which are managed by basic IT staff and protected by simple file encryption, restricted physical access, and regular backups. These setups are low-cost but have limited resilience. 

At the intermediate level, supervisors use secure transfer protocols, such as HTTPS, SFTP, and FTPS, alongside cloud storage platforms, such as AWS S3 or Azure Blob Storage, typically managed by specialized IT teams. Institutions have been increasingly adopting cloud storage for better resilience. For example, the Bank of England has been expanding cloud usage, while the Reserve Bank of India plans to launch IFS Cloud for regulated entities.  

However, as adoption grows, central banks are concerned about the risks of storing sensitive supervisory or financial data outside national borders, particularly regarding data sovereignty, privacy, regulatory compliance, and resilience. Such concerns are significant, especially against the emergence of new technologies, such as Central Bank Digital Currencies. Many are now exploring sovereign or locally managed cloud options to address these issues. 

While many organizations are transitioning, there is no publicly available evidence confirming that any institution has completed full-scale supervisory data migration. This mirrors earlier blog: Global cloud usage remains relatively low overall. Yet, many regulators are entering the intermediate maturity phase where secure, partial cloud adoption is becoming common. This phase involves moderate costs and requires compliance with advanced security measures, such as encryption-at-rest, identifying Access Monitoring (IAM) policies, audit trails, firewalls, and Multifactor Authentication (MFA). 

At the advanced level, organizations deploy data lakes and warehouses, supported by cataloguing tools, such as AWS Glue or Azure Purview for real-time data sync. This infrastructure, maintained by cloud architects and metadata specialists, supports enterprise-scale analytics and governance. For instance, Banco de España manages more than 850 TB of regulatory data and performs thousands of analytical queries each week for robust, AI-ready supervision. 

The growing adoption of SupTech highlights that despite significant upfront costs, the long-term benefits in resilience, scalability, and regulatory capability far outweigh initial investments. Institutions preparing for SupTech upgrades must prioritize needs assessments, gap analysis, stakeholder consultations, cost-benefit analysis, and strategic planning to ensure successful transformation.