Vaanijya - Mobile Solutions for Microfinance Institutions

1. Name of Innovation: ‘Vaanijya’-A sustainable model for micro-credit
solutions
Team/ Individual Name: Vaanijya
Members of the Team: Akshay Raghuwanshi, Shobhit Gupta, Soumyadeep Majumdar, Vivek Kumar
Name of College and City: IIT-Kharagpur
Course of specialization: Humanities, Electrical, Civil
Year/ Batch: 2014
Name of the Professor/ Placement officer involved in this project: Prof. N.C. Nayak

2. Stage of Innovation
• Prototype: The mobile application is currently in the Beta phase of its development after successful testing of its model and algorithms.
Idea Prototype Established Scaling

3. The Innovation
Chosen industry: Finance
Chosen technologies: Mobility and Analytics
Objective – Vaanijya aims at devising a self-sustainable model for providing risk management solutions to the
Micro-Finance Institutes(MFI) by promoting financial inter-dependence among the rural community.
Its three main objectives are:
 Risk-minimizing solutions for MFI’s.
 Expanding market outreach targeting rural community
 Self-help groups formation to ensure effective loan repayment
Approach:
 Expanding market outreach for MFI’s via data mining using government-issued AADHAR cards/NPR data.
 Utilizing postal and telecom services for marketing micro-credit loans
 Algorithm based group formation of borrowers based on geography and profession
 Customized credit score for filtering the borrower database
 Priority - based reallocation of MFI funds based on loan repayment history

4. The Innovation(cont..)
Describe the innovation:
Vaanijya is a mobile based application that focuses on end to end microfinance solutions. It integrates information available via AADHAR cards,
National Population Register(NPR) and Credit Bureau in its database. Postal/Telecom services are used to create awareness thereby encouraging
registration of the people of a particular area with the MFI. The registered data is then used by Vaanijya to calculate a customized credit score
based on personal and loan variables such as loan default history, number of outstanding loans, financial condition of the individual etc. to filter the
database for ensuring participation of people above a minimum credit score. This updated database groups the borrowers of a particular profession
together and the MFI funds are allotted to each group. Group repayment is ensured using the Grameen self-help group model which ensures
timely repayment before consideration of a reissue of loans by a particular group. For reissuing loans, the MFI funds are prioritized and re-allotted
based on previous repayment history of borrower groups. Integrating self help and priority based models ensure minimal risk for the MFI funds and
establish a sustainable system of microcredit lending in the long term.

5. Compelling Need
Market penetration:
 Huge potential market
 Resources not utilized efficiently
 Lack of financial literacy
Operational Efficiency:
 RBI proposal for interest-rate cap of 26%
 Existing loan disbursement is too manual and
resource intensive
 Conservative lending leads to loan labyrinth
Risk Minimization:
 Present client default rate of 22% out of which 27% default willingly .
 Number of loan defaulters are estimated at around 9.2 million with loan overdue amounting to 4000-6000
crores (Mani, 2010). Creating self-help groups helps in alleviating credit risk

6. Impact
Vaanijya is first of its kind application which will integrate current technological innovations in the MFI
working structure to bridge the existing gap between its market outreach and operational efficiency. The
expected impact of Vaanijya will be:
• Enhancement of the security of high-risk transactions for MFI funds
• Increase in the outreach of microcredit and financial services to the needy
• Improvement in the financial health of individuals
• Promotion of small scale businesses
• Discouragement of conservative lending practices
Metrics:
The success of Vaanijya would be gauged by the following factors:
• Loan repayment growth rate
• Increase in the number of people registering for loans
• Increase in the amount of total outstanding loans
• Cost to Borrower ratio
• Return on Investment

7. Impact(cont..)
Sustainability:
• The algorithmic framework for Vaanijya is based on dynamic prioritization of industry with respect to macroeconomic conditions. This model
ensures that MFI funds are lent mainly to industries which showcase a healthy rate of return thereby suggesting a long term appreciation in MFI
lending capital
• Vaanijya aims to promote self-help groups as a means for achieving long term stability. Based on the study of building social business models
(Yunus, 2010), it is known that individual borrowers have a higher probability of a loan default as compared to group based borrowing. Making
borrowers inter-dependent by forming self-help groups not only ensures timely repayment for the MFIs but also encourages effective loan
management for the group.
• The lender database is updated after the maturity period of every loan. This database is utilized for client retention by updating them about new
loan schemes thereby ensuring demand side pool for the business.

8. Implementation
Schematic
Approach
Credit Score
GUI
Timeline
Challenges
and Solutions

10. 𝑪𝒓𝒆𝒅𝒊𝒕 𝒔𝒄𝒐𝒓𝒆 = 𝜶𝒂 𝟏 + 𝜷𝒂 𝟐 + 𝜸𝒂 𝟑 + 𝜹𝒂 𝟒 + 𝝐𝒂 𝟓 + 𝜽𝒂 𝟔
𝒂 𝟏, 𝒂 𝟐, 𝒂 𝟑, 𝒂 𝟒, 𝒂 𝟓, 𝒂 𝟔 are the 6 financial parameters shown on which credit scoring is done,
α, 𝜷, 𝜸, 𝜹, 𝝐, 𝜽 are weights based on experimental data and its empirical study

13. Challenges and Suggested Solutions
Challenges:
• Collection of data from national records such as Aadhar and NPR from the government machinery may be subject to procedural delays.
• Borrowers may be hesitant to adopt responsibility for covering loan dues for others in the group in case a member default.
• Credit scoring model restricts the ability to reach the extremely poor.
Solutions:
• Alternative sources of data extraction such as municipal corporations may be explored
• Group based lending is promoted by informing the lenders about the risk mitigation and effective loan management solution provided by
Vaanijya. In case of a request for an individual loan only, the lender needs to have a credit score above a set minimum.
• Vaanijya shall provide the filtered list of the individuals who have a poor credit score to the MFIs so that they could be invited to MFI organized
workshops for improving their credit scores.

14. Competitive Advantage
Competitive Innovation:
Vaanijya will have a first mover advantage as it is trying to create a niche by being a MFIs service provider using data-analytics and mobility as a
tool. New technological adoption by MFIs via Vaanijya will give an edge over existing practices in different ways such as :
• Low-cost marketing for a large area via postal/telecom services
• Fully integrated end to end solution for microcredit loans
• Industry based grouping on borrower's side
• Instant decision for loan disbursement based on credit score
• Systematic way of fund utilization as given for a particular sector
• Financially inter-dependence of similar group-members will influence loan repayment capacity of an individual
Patent:
• Under Indian Penal Act, 1976 an algorithm can not be patented. However, we plan to copyright our mobile application.

15. Source of guidance:
Vaanijya is constantly guided and mentored by Prof. N. C. Nayak , Humanities and Social Science Department, IIT Kharagpur
References:
[1] http://www.mftransparency.org/
[2] http://www.mixmarket.org/
[3] M-CRIL Microfinance Review 2012: MFIs in a Regulated Environment
[4] Mani Arul Nandhi, Incidence of Loan Default in Group Lending Program, Microfinance Researchers’ Alliance Program, Center for Microfinance,
Chennai

16. Thank You