Score card template for MSME lending with objective to create automatic underwriting engine using flow based lending framework. Data points can e taken from various sources like GST portal, Account statement, UPI, India stack, Bharat bill payment, Digilocker to create robust underwriting engine.

1. 1. Introduction:
Being one of the largest employer of blue workforce and backbone of industrial progress,
government & policy makers are cognizant of importance of SME. Multiple policy initiatives and
incentive schemes have been brought into by central & state governments, RBI, & commercial
banks. As an eco-system, India has definitely progressed, but, when data states that around 65-
70% of micro & small businesses face problem in availing loan from formal financial system, and
total loan to MSME account less than 10% of GDP (Source: Morgan Stanley Research Blue paper:
India’s digital leap) it indeed calls for the change in approach.
In above context, present attempt is to propose a, data intensive flow based lending framework,
utilizing consent-based artifacts. Due to SME being unorganized in their working, there are a few
data points available. As a result, traditional Banks & Financial Institutions have shied away from
lending to this segment. Less data points meant no means to assess credit risk while lending to
SME. This has resulted into banks focusing towards collateral backed lending.
Structural changes in Indian digital landscape, like higher penetration of smart Phones, digital
identity authentication system like Aadhar covering more than 90% of population, and almost
every family having a bank account has brought the paradigm shift. Upcoming policy of Bharat
net with objective to connect all villages with optical fiber network and provide public Wi-Fi spot
will create a virtual market, enable commerce and lead to data explosion.
Going forward, real time data will be available on payment track record, business volume on GST,
e-way invoice for transport data, Aadhar for KYC authentication, payment Bank and small business
banks, API from ERP providers, data authentication by Digi locker and e-sign facility. Data from
multiple sources when combined and seen in right context can help in upgradation of credit
underwriting model used be banks/NBFC.
Data which is generated by users, but locked within various government & private entities
database will not be useful. This hindrance can be overcome by following consent-based artifacts
model. Under this model, the user or creator of data is real owner and based on his/her or
commercial entity’s consent, the consent collector collects all the data from data providers like
banks, Aadhar, India stack, GST, tax departments, credit scoring agencies, Digi locker, ERP and
post e-signature of user, will be shared with Banks/Financial institutions.
The real time, verified and wholistic data, can enable lenders to change their perspective from
asset backed lending to cash flow-based lending. Robust credit risk model can be build. Data
availability in digital format and instant electronic consent can enable on demand credit
availability reducing current TAT of 2 weeks to 6 weeks to less than a day. Other impact can be
customized offering, wherein time line, repayment schedule, staggered repayment, variable
monthly installment, can be serviced to each and every micro borrower. Lastly, due to
technological innovation, loan servicing and maintenance cost will reduce drastically and micro
loan markets unviable for commercial banks will be viable to serve. This will help in bringing these
businesses into fold of formal financial system. It will also increase competition by lowering entry
barrier and new alternate lending/fintech firms will enter and cater to specific markets.

2. 2. Stakeholders involved
1. Applicant/Borrower 14. ERP software companies
2. Lender -Banks/NBFC/Digital lenders 15. Insurance & Mutual Fund companies
3. Consent taker 16. Payment/ small finance banks
4. GSTN 17. Wallet providers
5. India Stack 18. Income Tax
6. Registrar of companies 19. Telecom service providers
7. Chartered accountants 20. Social media
8. CERSAI 21. Public distribution system
9. Central government 22. e-commerce companies
10. State Government 23. Education boards, Universities, Skill
training
11. Local municipal body 24. Credit rating agencies
12. Industrial associations 25. GAS connection providers
13. Local RTO 26. Defaulters Database
3. Risk assessment framework

3. 4. Methodology
The framework has been built in order to target two borrower pools , a) Micro borrowers unsecured in
nature and loan limit upto Rs 10 lacs, b) Small borrower with loan amount covered by collateral like
physical assets, gold, or covered under credit guarantee trust fund for MSME. Framework proposed is a
combination of subjective and financial assessment.
Approach followed is to enable a SME proprietor focus on his business activity and facilitate timely
availability of funding from banks & financial institutions without compromising on underwriting
framework. Unsecured borrower with complete verifiable data set can provide online consent, fill online
application form and finish discussion over telecon, without leaving day job. For secured borrower pool,
data, documents & consent can be taken online with one visit for site/collateral visit by banker.
The risk assessment is carried in score card format, wherein data related to promoters, business, past
operational history, industry factors, collateral charge data, conduct of account from all possible sources
are collected. The collected data is used to create risk assessment and mitigation framework.
The standalone data point is source of valuable information, but, when used in conjugation with other
data point it provide can real business insight. Example- GST invoice data when coupled with account
credits and ERP data about receivables shows real time exact verified sales data. For a proprietorship firm,
debt, combined with existing personal credit data (Home loan, vehicle loan) extracted from CIBIL show
the over all debt exposure of a proprietor firm.
The risk factor associated with each of these collected data source can be assigned a relative weight and
a score to it depending on quality of information. Weightage & scores are to be assigned by respective
institutions on basis of past portfolio behavior & sound rationale. The overall weight and score together
should sum to 100. A threshold score of say 60 can be considered as loan application that can be funded.
Also, based on scoring, (that is higher the score, secure the loan amount shall be), better pricing can be
offered.
For parameter not applicable to specific industry or sector, weight for the same can be assumed to be
zero and sore be finally normalized to 100.
I. Risk assessment score card for unsecured micro loans up to ticket size of INR 10.0 lacs.
Parameters Data point /Proxy data Type of
Risk
Source to validate
the same
Weighted
Score
e-KYC authentication W, A
Proprietor, Partners, directors, Identification and
address validation
MnR Aadhar detail, Digi
Locker
W1a1
Age of company & line of activity Proxy for business
standing in market and
anti -fraud
BR Business aadhar,
RoC API,
Partnership deed,
Digilocker
W2a2

4. PAN Card details of promoter & company Verification of PAN
cards as caution against
fraud
MnR,BR Income Tax API,
Digi Locker
W3a3
Promoters/Proprietor/Partners/Directors
detail
Age (Between 18 to 65) MnR Self-declaration,
Digi locker
W4b1
Academic qualification, Skill India Certificate PG,
UG,12+, Matriculate,
under 10th
.
MnR Self-declaration,
Digi Locker
W5b2
Experience in line of trade Greater than 1 year MnR Self-declaration W6b3
Spouse detail Working or homemaker MnR Self-declaration W7b4
Children involved in business For applicant above 55
years
MnR Self-declaration W8b5
Owns a house/property Yes or no SR Self-declaration W9b6
Social media Profile authentication &
psycho analysis
MnR Social media search W10b7
Type & name of vehicle owned Assets ownership &
registration data, loan
detail if availed loan
MnR,
SR
B-Extract copy &
vahana.nic.in
W11b8
Account conduct (Promoters account/CA
or existing OD limit) with Banks or small
finance banks
Length of relationship with formal
financial system
Account opening/TL
loan availed date
MnR Account
statement/Sanction
letter
W12c1
Number of inward cheque/RTGS/NEFT
bounces
Instances of not holding
commitment
MnR,
BR
Account
statements
W13c2
Number of outward cheques/RTGS/NEFT
bounces
Instances of borrower’s
customer not delivering
on promises.
BR Account
statements
W14c3
Delay in payment of existing EMI if any Instances of delay and
number of days
MnR Account
statements
W15c4
OD account overdrawn Instances of delay and
number of days
BR,
MnR
Account
statements
W16c5
Penal charges Instances and reason MnR Account
statements
W17c6
Credit summation for last 12 months or
since inception
To verify sales routing
through the account.
BR Account
statements
W18c7
Credit/debit entries to be cross verified
with GST
Receivable/Payment
cycle
BR Account statement
and GST portal
W19c8
GST Portal
Customers profile Quality of customers BR GST Portal W20d1

5. Customer concentration % of sale from top 5
customers
BR GST Portal W21d2
Supplier profile Quality of suppliers BR GST Portal W22d3
Supplier concentration % of sale from top 5
customers
BR GST Portal W23d4
Trend in volume of business Month on month
Increase or decrease in
sales
BR GST Portal W24d5
Product line being catered Number of products
being sold and margin
trend
BR GST Portal W25d6
Geographic concentration of
customer/suppliers
Location wise
concentration of buyers
& suppliers
BR GST Portal W26d7
Payables due more than 3 months Delay in payment by
borrower may be
indication of business
facing liquidity crunch.
BR GST Portal W27d8
Receivables due more than 3 months Delay in receipt of
payment for more than
3 months may be
indication about quality
of product or buyers
insolvency
BR GST Portal W28d9
e-Way Bill Validate shipment of
goods especially for
trading firms
BR GST Portal W29d10
Financial Data
TOI Revenue obtained
during last three years.
FR Last3 year Financial
Statement,
Financial as on date
- ERP
W30e1
EBITDA/PAT Operating Profit ratio FR Last3 year Financial
Statement,
Financial as on date
- ERP
W31e2
TOL/ATNW Leverage Ratio FR Last3 year Financial
Statement,
Financial as on date
- ERP
W32e3
ROCE Return of capital
employed
FR, IR Last3 year Financial
Statement,
Financial as on date
– ERP
W33e4
DSCR Debt service coverage
ratio
FR Last3 year Financial
Statement,
W34e5

6. Financial as on date
– ERP
Current ratio Liquidity ratio FR, IR Last3 year Financial
Statement,
Financial as on date
– ERP
W35e6
Total Liabilities/Net cash accrual Ability to meet the
external obligations by
existing cash flow
generated by company
FR, BR Last3 year Financial
Statement,
Financial as on date
- ERP
W36e7
Inventory as % of Revenue Revenue held in form of
inventory
FR Last3 year Financial
Statement,
Financial as on date
– ERP
W37e8
Receivable as % of Revenue Revenue held in form of
Receivables
FR, BR,
IR
Last3 year Financial
Statement,
Financial as on date
– ERP
W38e9
Creditors as % of RM consumed Raw material consumed
taken on credit.
FR, BR,
IR
Last3 year Financial
Statement,
Financial as on date
- ERP
W39e10
Dedupe checks
CIBIL/Equifax score of promoters Credit score above 650
or credit score linked
pricing
MnR CIBIL Report based
on PAN detail
W40f1
Delay in payment in any of the loans by
promoters
CIBIL Report MnR CIBIL Report based
on PAN detail
W41f2
Commercial CIBIL of business entity if
present
Past data about
businesses entity loan
repayment
BR CIBIL Report based
on PAN detail
W42f3
ECGC Defaulter list Check for non-presence
of promoters/business
entity name
BR ECGC defaulter list W43f4
RBI Willful defaulter list Check for non-presence
of promoters/business
entity name
MnR Wilfull defaulter list
by RBI
W44f5
Anti-money laundering database Check for non-presence
of promoters/business
entity name
MnR List published by
Government
W45f6
Bills Payment
Electricity, water, Gas, Telecom, DTH Regularity in payment
of utility bills by
promoters
MnR Bharat Bills
Payment
W46g1

7. Insurance premium, mutual fund, school
fees, institutions fees, local taxes, invoice
payment by Promoter
Regularity in payment
of other bills by
promoter
MnR Bharat Bills
Payment
W47g2
Institutions fees, local taxes, invoice
payment by business
Regularity in payment
of other bills by
promoter
BR Bharat Bills
Payment
W48g3
Existing payment apps or payment banks Regular bills payment
by promoter & business
MnR,
BR
Payment bank/
mobile wallets
accounts
W49g4
e-Public distribution system (Micro loan
borrowers)
Latest data of ration having availed and
locality
Prevents possibility of
fraud by absconding
MnR Aadhar &
Household ration
card
W50h1
Insurance
Promoters life & health insurance data Insurance policy along
with premium paid
MnR Aadhar Number W51i1
General insurance products availed by
business
Indicative of business
risks to which company
is exposed and its
hedging policy. Can be a
factor in pricing
BR PAN number W52i2
Consent for assignment of policy papers in
case of default for endowment plans
Security in case of
default.
SR Borrower e-
authorization
W53i3
e-commerce sales
Number of e-commerce platform
registered onto
Risk diversification
across multiple e-
commerce platforms
BR e-commerce portal W54ji
YoY sales from ecommerce portal Sales trend from e-
commerce portal
BR e-commerce portal W55j2
e-commerce sales as percentage of total
sales for the year
Offline & online sales
data
BR e-commerce portal W56j3
Funding availed from e-commerce tie-ups
with financiers
Data with perspective
to avoid double
financing
BR e-commerce portal W57j4
Trade Invoice Discounting Platform
Invoice amount discounted at TrEDS
exchange
Data factored in to
avoid double financing
BR TrEDs exchanges W58k1
Income Tax data
Form 26AS -quarterly filing Data about sales in last
quarterly filing
BR Income Tax,
Brower
W59k2

8. Payroll data
Employee salary cost % of total cost Trends in hiring cost or
increase in overall
remuneration
BR W60l1
Telecon discussion/market feedback
Applicant Business Model, past
growth history, future
plan, clarifications
about any discrepancy
observed in data
Telecon- Applicants
contact details
W61m1
Applicant’s customer Feedback about
products, relationship
with applicant,
Telecon- Applicants
key customer’s
contact details
provided by
applicant
W62m2
Applicant’s supplier Feedback about
payment cycle,
relationship with
applicant
Telecon- Applicants
key supplier’s
contact details
provided by
applicant
W63m3
Applicant’s Chartered Accountant Details about company,
financial details and
statutory clarification,
general feedback
Telecon- CA’s
contact details
provided by
applicant
W64m4
Merchant POS sale: for retail sellers
Sales trend through merchant sales Historical trend of
merchant sales
BR, IR m-POS service
provider
W65n1
PoS Sales data validation at merchant end Data validation of
applicant’s sales m-POS
service provider
BR m-POS service
provider
W66n2
Merchant sales as % of Total sales Percentage of total
sales through digital
channel for retailers
BR m-POS service
provider and ERP
W67n3
Personal guarantee
Personal guarantee of minimum 70% of
promoters/shareholders
Promoters/shareholders
skin in the game.
MnR Promoters signing
of agreement
W68o1
Bank exposure as % of combined net
worth
Ratio not to be above
300 %
BR Self-declaration for
net worth
statement
W69o2
Mobile App retrieved Data
Bank transactions SMS alert Using financing entity’s
apps to track banks
MnR W70p1

9. II.Score card for secured micro loans upto ticket size of INR 200 lacs.
All the parameters mentioned in above score card for unsecured loans and below mentioned
additional details can be added on selective basis.
transaction sms to get
real time data
Red flag app installed eg- Gambling apps Track portfolio of Apps
installed on applicant’s
mobile to track red flag
apps
MnR W71p2
Online Web search about
business/promoters
Google search about
business, promoters
BR,
MnR
W72q1
External Factors
Industry outlook & competition Industry outlook for
future
IR Risk management
department of
Banks, CRISIL
industry outlook
report
W73r1
Economic growth outlook Economic growth
outlook for future
McR RBI quarterly
economic reviews
W74r2
Parameters/Information source Data point /Proxy
data
Type
of
Risk
Source to validate
the same
Weighted
Score
Collateral data- Physical property
Type of property Residential,
commercial,
industrial, open plot
SR Sale deed, Gift
deed
W75s1
Central registry of securitization asset
reconstruction security interest
(CERSAI Filing)
Charge filed data
about past
SR CERSAI Website W76s2
Ministry of corporate affairs charge filing
data
Charge filed data
about past
SR MCA API W77s3
Existing bank sanction letters Details mortgaged
to current lenders
FR,
SR
Applicant W78s4
Empaneled Advocate legal report online
upload
Title search report
and legal vetting of
property
SR Bank empaneled
advocate
W79s5
Empaneled valuers report Valuation of
property- land
building, machine,
vehicle, inventory
SR Bank empaneled
valuers
W80s6

10. Encumbrance certificate of property Details about
charge created in
name of property
SR Local municipal
authority
W81s7
Property tax paid receipt Indication of
ownership of
property
SR,
Legal
Risk
Applicant W82s8
Collateral covered under CGTMSE
Collateral charge paid in past Details about
existing collateral
coverage
SR CGTMSE W83t1
Collateral invocation for company in past Default in past by
company
MnR CGTMSE W84t2
Company/Site visit
Business model, Operations, Accounts First hand view of
business
BR Bank official W85u1
Employee/official meeting Interaction with
employee, direct
operations people
BR Bank official W86u2
Promoter meeting Get overall
perspective of
business, future
strategic plans
BR,
MnR
Bank official W87u3
Collateral visit Check for ground
situation with
respect to
marketability of
property should
situation arise.
SR Bank official W88u4
Payroll
ESI payment Month on month
data indicates the
hiring cost and
proxy about future
plan
BR Payroll ERP W89v1
Provident fund payment Month on month
data indicates the
hiring cost and
proxy about future
plan
BR Payroll ERP W90v2
Employee salary cost % of total cost Trends in hiring cost
or increase in
overall
remuneration
BR Payroll ERP W91v3

11. 5. Assessment of limits- Working capital & TL
Assessment of limits both for working capital and term loan can be carried out once all the relevant
financial details are available. In traditional banking setup, for working capital limits upto Rs 5 crore,
projected turnover method is used for cash credit or overdraft limits. In this, few assumptions are made
like turnover of last financial year is projected to increase by past trend, (in possibility of unusual growth
trend , promoters need to justify it) working capital cycle to be 90 days and margin amount to be 20%. On
overall calculations, working capital exposure is 20% of projected turnover.
In new data rich environment, working capital assessment needs to include latest invoice data, order
book, changed cash to cash cycle. Considering these new reality, below is the proposed structure for
working capital assessment
Note- Non fund based limits are not considered in current context as data availability is not seamless and
needs confirmation from multiple parties, however in cases where non fund based limits are availed, it
needs to considered as part of overall working capital exposure.
Data source
A Historical Monthly trend
Total Monthly sales in past three months*
(1+growth rate)
X GST, ERP
No. payment cycle of 90 days 1
Less : e-commerce tie up finance if any A e-commerce platform
Less : Supply chain finance if any B Corporate or their
supply chain finance
partner bank/NBFC
Less : Trade discount exchange factoring if
any
C Trade discounting
exchange
Gross working capital required X-(a+b+c)
Margin @20% -0.2(X-(a+b+c))
Net working capital finance 0.80*(X-(a+b+c))
OR
B Outstanding receivables on monthly basis X GST, ERP
Inventory (Raw Material+ WIP+ FG)
holding amount on monthly
Y ERP
Less: trade payables on monthly basis Z GST, ERP
Less : e-commerce tie up finance if any A e-commerce platform
Penalty paid on payroll compliance Noncompliance
data
BR Payroll ERP &
account statement
W92v4

12. Less : Supply chain finance if any B Corporate or their
supply chain finance
partner bank/NBFC
Less : Trade discount exchange factoring if
any
C Trade discounting
exchange
Gross working capital required =(X+Y+Z)-(a+b+c)
Margin @20%
Net working capital finance 0.8*((X+Y+Z)-(a+b+c))
Total working capital limits to be higher of the two.
Note-The time line for assessment can vary (yearly, quarterly or monthly) depending upon data analysis
and business cycle as observed about the industry, particular business entity. The data from GST, ERP ,
bank account statement will be vital source to calculate the receivables and payables.
Once the GST portal, supporting platforms stabilizes, the borrower’s track record of repayment is built
time period of loan can be decreased further to one week or a day.
Assessment for Term Loan -Debt service coverage ratio[DSCR]
Year1 Year2
Profit after Tax + depreciation
Interest on term Loans
Sum total [A]
Term loan repayment obligations
Interest on term Loans
Sum Total [B]
Gross Debt service coverage ratio[A/B]*
Minimum threshold DSCR varies bank to bank. In present case it should be minimum 1.5
Note- Term loan tenure can be variable and less than a year in few cases. In case of duration less than one
year, all the calculation to be carried out on pro-rata basis.

13. 6. Process -Flow based lending

14. 7. Asset monitoring
Post sanction cum disbursement, applicant turns into borrower and close monitoring of asset is
desired during the tenure of loan. Assets monitoring is followed at two level, a) Individual firm
level b) Portfolio level. Since loans are small ticket and high-volume analytics needs to play a big
role.
a. Firm level monitoring- Post sanction and disbursement of funds, end use of fund is
monitored, activity level co-relation with projections made during sanction, detect deviation
from terms of sanction, regular payment of installment & interest, regular routing of sales
through account, regular payment of insurance premium. Performance review of
operational parameters like turnover, profitability, margin, leverage.
Many early warning signals can be tracked for effective monitoring of assets as shown
below.
Early Warning Signal Data Source Frequency
Default in payment to statutory dues
and banks
Bank Account statement,
ERP, IT dept
IT dept data
monthly, bank
account statement
can be downloaded
anytime
Delayed GST bills payable, and invoice
payment
GST Portal, account
statement
Monthly or quarterly
Reduction in stake of promoters and
promoter non-responsive
ERP, account statement ERP data on running
basis. Financials on
quarterly interval
Account overdrawn for prolong
duration and increased frequency
Account statement On running basis
Sudden fall in account credit more
than 25% in a particular quarter.
Account statement On running basis
Default in insurance premium,
payment of utility bills by promoter
Insurance SMS alert Fortnightly basis.
Total liability amounts greater than
1.5 time last one-year turnover
ERP data Triggered by ERP
software.
Stock & inventory data from ERP
should reflect working capital limit
ERP data Fortnightly basis
Regular tracking of funding of working
capital to check for double financing.
GST, ERP, TreDs,
dealer/supplier account
Monthly
High value payment to unrelated party
or heavy cash withdrawal from
company account.
Account statement On running basis
Critical observation during
unit/stock/collateral inspection.
Site visit/stock
statement/gowdown
visit report
quarterly
Increase in unbilled revenue ERP, Account statement On running basis
Increase in related party transactions Account statement On running basis

15. Frequent change in business address Web search & submitted
documents
On running basis
Deviation between disclosed and real
data, or hiding of material
information. Discrepancy in data
obtained from different sources like
ERP data, MCA filed data, CA
feedback.
ERP, MCA, CA discussion Monthly
Sales return data to be tracked
carefully
ERP, Account statement,
GST
Monthly
Drastic change in financial parameters
like sudden fall in sale,
disproportionate change in inventory
position, receivable cycle lengthening
or shortening, increase in fixed assets
without corresponding increase in
sales.
ERP, Financial
statements
Monthly
b. At portfolio level following checks and balances are required to
Assets portfolio tracking needs to be carried out at regular interval so as to fine tune the
credit policy prevent further slippages of accounts. Important parameters to be tracked are
Diversified lending across services, Manufacturing and trading sector
Not more than 30 % of portfolio exposure to particular industry or geography or
depending upon Financial institutions business model
Term loans should align with well with liability tenure and not more than 30% above 1
year
Case by case portfolio review if stressed account increases more than 10% of assets.
Regulatory guideline specific to particular industry or geographic area
8. Recovery Policy
When a loan account is under stress, defaulting in its repayment schedule or early warning signs
of default are visible, rigorous flow up process to be initiated.
Restructuring:
If the business is viable in long term, promoters are honest, handholding should be explored.
The support can be in terms of additional incremental funding, concession in interest rate,
change in repayment duration, lowering of principal paid. Equal sacrifice to be ensured by
promoter by reduction in salary, commitment about non-withdrawal of dividend or retained
earning from business till turnaround.

16. In case of assets turning to NPA, normal recovery process to be initiated as per the credit policy
norms of banks/Financial Institutions. Process to be followed as that in case of existing SME
borrowers.