v
Marrying Finance and Technology.
v
Availability of data from many sources.
i)
Data from Aadhaar
ii)
Data from Credit Bureau
iii)
Data from Fraud score card
iv)
Data from Algorithmic score card
v)
Duplication
v
Given this data, putting altogether, decision
taken.
v
This is an infrastructure.
v
Average of 10% of their loans was going
digitally, without seeing their clients.
v
Many new financial institutions, having no track
record history, has become significant.
v
Financial institutions, newly incepted have no
customers.
v
225 start-up companies in the lending business
for 2 years now.
v
This is alternative lending business.
v
Next 5 years, see a growth of 30-40% of their
loans going digitally.
v
Aadhaar, Jandhan will leave a digital foot print.
Origination → Data → Monitoring →
Delivery →
Maintenance.
v
GST will be the formalization of economy, i.e.
45 million micro enterprises, which have not paid tax, which have not
registered, will come into the formal economy or disappear. All of them require
funding.
v
CIBIL captures only credit card transactions.
v
Identifying credit profile of individuals –
Mobile phone data.
v
28 million credit cards, 800 million debit cards.
v
Biggest source of data – Mobile phone data.
v
Given access to an individual mobile phone data,
decisions can be made.
v
By opening up this access, from TRAI, credit
penetration in India will boost up.
v
Data privacy, given an individual’s email
address, a complete profile can be figured out.
v
UPI Vs Wallets
v
Future on Fintech revolution
i)
For last 20-30 years, lending happened to large
corporates.
ii)
SME financing and consumer financing pie was
very small
iii)
10% of India credit to SME
iv)
16% of India credit to Consumer
v)
74% of India credit to large corporates and
priority lending.
vi)
Now things changing drastically
vii)
RBI said, large corporates after 2020 can’t
borrow more than a $1 Billion from banks, after that go to Bond markets. So,
this will push more money to small borrowers.
viii) Next
3 years or so, the alternative channels other than conventional banks will show
a huge surprise.
ix)
Rs.110 Lakh crore deposits, 70 lakh crore going
to private sector and the rest goes to Government. (How much the Indian credit
will change) I.e. credit side of India (in total) – Rs.110 Lakh crore.
v
Need for collateral, with information will be
reduced.
v
620 million under age of 25, so 2 years not
sufficient but 5-7 years.
v
Regulatory challenges – Cyber security, KYC
v
The next big leap for UPI- 400 million
smartphone users. First, how to reach out to these 400 million smartphone
users. Large players like Amazon, Flipkart, etail players, social media
players, banks, wallet providers like PayTm, which is participating in the UPI
bandwagon.
v
Expanding the UPI user base.
1)
Allowing payments banks to give loans does not
work. (like Airtel)
2)
Micro Finance Institution (MFI)–Bank
partnership.
3)
Have seen behavioural change in MFI companies.
Need skill and scale for financial inclusion has to be truly economic
inclusion.
4)
43% mobile phones.
v
Fintech is basically start Ups using technology
to disrupt everything that a bank does today.
Disruptions like,
i)
From Payments- Mobikwik, Freecharge, PayTm,
RazorPay
ii)
Remittances – Oxigen, ItZ, PayWorld, novopay
iii)
POS – eZetap, PineLabs, Swipe
iv)
Consumer lending – BankBazaar, Faircent,
ZestFinance, Rinomina
v)
SME lending – Capital Float, LendingKart, indifi
vi)
Insurance – PolicyBazaar, Coverfox
vii)
Savings and wealth management – FundsIndia,
Moneyview, Scripbox
v
Why SME lending is ripe for disruption? –
Demand, Technology, Capital
v
Demand: 30 million SMEs in the country today,
contributing 20% of GDP, 40% of jobs, 40% of exports.
Total debt demand form SMEs in
India - $433 billion
Funded by banks and NBFCs – 27%
Ineligible for funding – 35%
Unmet demand – 38%, nearly
$200-300 billion
v
Technology: Electronic Clearances (ECS, NEFT,
NACH, IMPS, etc.) surpassed paper clearances (cheques)
Digital footprint like WhatsApp,
Facebook, LinkedIn
v
Algorithm – online Application form, typically
applications coming in between 1 and 3pm, 5 and 8pm have best chance of getting
a loan. But people applying between 11 and 4 pm has less chance. If he/she
enters the entire application form I caps, means literacy at the lower side. As
the app is in his phone, it can be able to fetch data about SMS, Bank
statements. Connected to credit bureau via API to see or pull what the other
loans he has and how he’s paying them off. He log into the app via Facebook, so
we get to know how many friends he’s got within the region, is he well
connected within the region, his comments negative or more positive, all these
add to his credit score. We also include a Psychometric test, which ask
questions such as if you won the lottery, how you gone spend the money, spend
on rent, education, for a party etc., this get to know about the integrity of
the borrower. Also, his e-commerce data, how much he travels on RedBus, MakeMyTrip,
put together, create a digital footprint. By which a loan within 10 minutes,
without paper work, without collateral.
v
Lending is set to grow 5 times in 10 years.
v
SME lending will have a significant pie.
v
Current market cap (FY’16)- Total - $170 Billion
Banks- $127 Billion, NBFC- $41 Billion,
Fintech- $2 Billion.
Estimated Market cap (FY 2026) -
Total - $600 Billion
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