What is the potential and feasibility of alternative channels of agricultural insurance, specifically at the meso-level? Based on a review of published literature, policy documents and models of meso insurance across the world as well as key informant interviews, this study commented on the potential of meso insurance particularly in the agricultural sector in… Continue reading The Market for Meso Insurance
How Information and Communication Technology (ICT) and mobile phones specifically act as catalysts that enable women to secure sustainable and flexible livelihoods? This study aimed at identifying use cases of smartphones, feature phones and mobile applications in the mobilisation of rural women into self-employment and entrepreneurship. Through focused group discussions and case studies of… Continue reading Mobiles for Mobilisation of Women
The study aimed at unpacking the mobile phone usage patterns of rural women from three states with varied levels of economic development – Rajasthan, Madhya Pradesh and Gujarat. Six focused group discussions and a survey of 900 men and women from across 78 villages done to disentangle some patterns in women’s use of mobile phones.… Continue reading Rural Women’s Use of Mobile Phones
The unique study in India, gathered fortnightly financial diaries data from 120+ households in Chennai slums over 12 months. This added up to 24 rounds and 5000+ household level interviews about incomes, expenditures, assets, liabilities, shocks and other socio-economic variables. Findings threw light on the various aspects of the financial lives of this customer segment… Continue reading Financial Lives of Urban Poor Households
How can visual design replace complex contractual and service related term in digital financial products and transactions? In-depth interviews with respondents affected by financial frauds in Rajasthan and Gujarat revealed the gaps in understanding of terms and conditions common to financial agreements. Through qualitative analysis of data, the study developed suggestions for graphical grammar… Continue reading Exploring a New Paradigm for Contracts
How can credit assessment of thin-file micro and small enterprises be done with confidence? A survey of 400+ micro and small enterprises was conducted in Karnataka, Maharashtra, Gujarat and Delhi NCR. Analysis of data revealed a typology and a model for credit assessment of MSMEs.
First level analysis to track changes and advances in households’ financial inclusion between 2016-2022
How do Medium and Small Medium Enterprise (MSME) clusters grow in India? This study includes extensive case studies of five prominent industrial clusters – Trichy, Tirupur, Coimbatore, Sivakasi and Chennai. Applying systems analysis, it draws patterns of change and growth in each cluster. The study surfaces system level insights that may be useful… Continue reading MSME clusters as systems
How mutuals, cooperatives and community-based (MCCOs) insurance can be scaled up to improve the Bharat customer’s access to insurance? Extensive study of 19 mutual and cooperative insurers in India contributed to an understanding of the current gaps in mutual insurance and identification of future opportunities. The study concluded with sharply defining four use cases… Continue reading Scaling Up Community-based Insurance Models in India
In what ways can a platform where gig workers own their data with split-incentives to share non-rival data (transactional data) result in their improved physical, social and financial wellbeing? An extensive survey of over 4000 gig workers engaged with platforms across tier 1, 2, 3 cities and towns (including Bengaluru, Mumbai, Kochi, Calcutta, Guwahati,… Continue reading Data Ownership and the Gig Worker in the Gig Economy
What can be the promising use cases of open banking in India? A thorough sampling frame constructed to identify metro/non-metro cities and towns across north, south, east and west regions. Survey data collected of 160+ individuals from each region and analysed to understand the customers’ perception of open banking.
Survey data of 2000 farmers associated with 50 FPOs in Andhra Pradesh and Telangana were analyzed using advanced machine learning algorithms. Regression Tree and Random Forest algorithms were applied to identify variables that predict ‘farmer embeddedness’ in an FPO.