Microsoft Research India

Microsoft Research India• Established Jan 2005 - Bangalore

• Goals– World-class academic research– Contributions to Microsoft

products and businesses– Support growth of research

programs in India and elsewhere

• Six research areas– Cryptography– Digital Geographics– Hardware, Communications, and

Systems– Multilingual Systems– Rigorous Software Engineering– Technology for

Emerging Markets

• Collaborations with government, academia, industry, and NGOs

Computer-skills camp in Nakalabande, Bangalore(MSR India, Stree Jagruti Samiti, St. Joseph’s College)

Understand potential technology users in economically poorer communities

Adapt, invent, or design technology that contributes to the socio-economic development of poor communities worldwide

http://research.microsoft.com/india

© 2007 Microsoft Corporation

Towards gains in (contextual) efficiency and user experienceInnovations in Information Technology for the Client and MFI

Asia-Pacific Regional Microcredit Summit, July 29 2008, Indonesia

Aishwarya Lakshmi RatanMicrosoft Research India


Overview: IT in microfinance

• Aggregation of client data– Report generation– Actuarial analysis– Targeting offerings

• Account creation (loan, savings & insurance)

• Transaction data

Back-end Front-end

Info System

Cash/ payments

• Bank/ investor MFI HQ MFI branch MFI retail outlets

• Payments from MFI/bank customer

• Payments from customer MFI/bank


(1) IT investments by MFIs




Back-end Front-end

Info System

Cash/ payments




Work by Aishwarya Ratan, Mahesh Gogineni


Reductions in transaction costs?

• Examine client-facing information collection and processing transaction tasks in microfinance workflows

• Can technology deliver cost savings to the MFI through efficiency gains?

• Create an analytical framework in which the cost for a given transaction τ is described by a cost function C (Vl, Vk, O, L, F, N)

• Examine the relative cost accrued for task τ under alternate arrangements, LT (low-tech, baseline channel)and HT (high-tech), for a given MFI

(For details on the costing model, please see http://research.microsoft.com/~aratan/Cost_Realism_May08_final.ppt )

1


Cases

Customer AcquisitionUrban NBFCImprove efficiency of customer acquisition processSmart phone used by field officerData sent via SMS or GPRSCut variable cost by 50%Positive RoINegative NPV over 6 years

Installment ProcessingRural SHG FedStreamline book-keeping and installment data collectionSmart phone used by field officerData sent via SMSLittle reduction in variable costsHigh fixed costs for HT channelNegative NPV over 6 years

Installment ProcessingRural NBFCStreamline installment data collectionHandheld device used by field officerData uploaded through USBCut variable cost by 73%Positive NPV over 6 years

1 2 3

1


Cost savings comparisonCase 1+ Case 2 Case 3

Labour component 1(front-end)w1 (per month, Rs.)* 4500 800 4500A1,LT - A1,HT (Productivity gain in minutes)

19-19 = 0 2-2 = 0 3.46 - 0.81= 2.65

Productivity gain 1 (share of baseline)

0 0 0.76

Labour component 2 (back-end)w2 (per month, Rs.)* 4000 800 6000A2,LT - A2,HT (Productivity gain in minutes)

14-0 = 14 2-1.75 = 0.25

0.6 - 0.033 = 0.57

Productivity gain 2 (share of baseline)

1 0.125 0.95

Vk,LT - Vk,HT (Rs.) 5.65-0.05 = 5.6

0 0.78 - 0.33 = 0.45

Variable capital cost reduction (share of baseline)

0.99 0 0.58

G (Rs.) 10.97 0.019 1.92N (number of task τ transactions per yr per branch)

2400 22,992^ 64,800

TG (per yr per branch, Rs.) +26,304 +437 +124,416OLT – OHT (per L, Rs.) -2030 -1680 -970L (per branch) 8 8 12OG (per yr per branch, Rs.) -16,240 -13,440 -11,640π (cost savings, Rs.) +10,064 -13,003 +112,776FLT - FHT (per branch, Rs.) -98,462 -68,000 -138,000NPV of π over 6 years^^ <0 <0 >0(PV of π over 6 years) / |FLT - FHT| ^^ 0.5 <0 3

1


Implications: Cost-realistic IT deployments

•The higher the labour productivity gains from the HT channel, the greater the transaction cost savings.

•The higher the local wage for the task, the higher the productivity-linked transaction cost savings.

•The higher the variable capital cost reduction, the greater the transaction cost savings.

• A larger number of transactions per unit of labour/per device greatly multiplies the power of productivity gains per transaction from the use of the HT channel.

•The larger the operating costs required to run the HT channel (e.g. connectivity costs), the lower the gains from overall cost reduction.

•The higher the fixed capital investments called for in the HT channel, the more substantial the requirements for high transactional cost savings and low operating cost differentials to ensure the HT channel’s financial sustainability.

1

Excel-based costing template available at http://research.microsoft.com/~aratan/costing.htm





Back-end Front-end

Info System

Cash/ payments




Work by Indrani Medhi, Jonathan Donner, Aishwarya Ratan

(2) IT in the hands of the client


Virtual currency: Cash-in/ cash-out• Rich customers use ATMs & a

bank savings account to “store value”

• Most of the rich live in dense urban areas and conduct high-denomination transactions

• The poor are spread out in rural areas and conduct low-denomination transactions

• Current solutions: ATMs in low-income urban neighborhoods; use existing retail networks that serve the urban and rural poor: e.g. pre-paid talktime outlets

2

Mobile ‘stored-value’ outlet


Cash-less transactions• Rich customers use PC- or

phone-based internet banking; use cheques

• The poor do not own or access PCs regularly; often have literacy barriers

• The mobile phones they own are not data-enabled

• Current solutions: Use SMS or USSD channels, and/or SIM-based applications for mobile payments

2

M-payments user


Critical issues in uptake

• The intermediaries to the IT channel are critical as informal and flexible mediators (ATM lobby assistants, m-payment agents)

• Focus on the density and locations of cash agent networks in low-income neighbourhoods as a core strength

• Text entry is very challenging for low-literate customers; SMS applications difficult for direct use

• Clarity on charges is critical

2

Cash agent


Questions going forward…• What is an optimal User Interface for mobile-banking

interactions among low-literate users? – Medhi, I. , A. Sagar and K. Toyama. “Text-free UIs for Low-Literate PC

Users,” ICTD 2007

• Is the development impact of mobile-banking services sizeable; is it widespread or specific to particular kinds of poor households?

• What happens to microcredit repayment rates when the group’s regular social interaction is interrupted (by IT-enabled channels)? – Related CMF study on meeting frequency and repayment rates by Roy and

Davies.

• Will efficiency gains in payments channels translate to lower lending rates for microcredit?


Acknowledgements: CGAP, PRADAN, CCD/Ekgaon, BASIX, Ujjivan, Eko, EQUITY Bank, Safaricom,

Kentaro Toyama, Shabnam Aggarwal, Angelin Baskaran, Rajesh Veeraraghavan, Rahul De

Updates on our research projects are available at http://research.microsoft.com/~aratan/FSD.htm

? [email protected]

Microsoft Research India

Documents

Transcript of Microsoft Research India