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Apr 2, 2017 · 21m · top-founders

EP 617: DataSigns Raises $5.4M, Gives Loans To Indian Credit Borrowers At 1/2 The Rate Money Sharks Do With CEO Monish Anand

Monish Anand · 9m spoken Nathan Latka · 9m spoken
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In this episode of The Top, host Nathan Latka interviews DataSigns Technologies founder Monish Anand to explore how his Bangalore-based FinTech startup leverages alternative mobile data, B2B MSME partnerships, and an asset-light banking model to provide fair institutional credit to underserved Indian borrowers.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Nathan holds 49.2% of the talking time here. How this is scored →

Nathan as informed peer 2.8 Guest teaching 2.6 Guest disagreement 0.4 Nathan pushing back 2.0
05100:0010:0020:001:32–6:05 · Nathan as informed peer 3/10 Introducing Monish Anand and the Indian Credit Gap Monish educates Nathan on the credit gap in India where 400M people apply for loans and traditional banks reject most of them. Nathan asks straightforward clarifying questions regarding Monish's driver anecdote and how smartphone digital footprints substitute for traditional credit scores.6:06–9:13 · Nathan as informed peer 4/10 MSME Partnerships, Financial Literacy, and Loan Traction Nathan presses Monish to distinguish between the 75,000 employees exposed to their HR partnership program versus the actual 10,000 app downloads. Monish explains their MSME factory onboarding strategy and initial loan volumes.9:13–15:17 · Nathan as informed peer 6/10 Financing Rounds, Asset-Light Banking Model, and Team Growth Nathan digs deep into the unit economics, asking detailed questions about upfront points, loan shark IRR, interest rate spreads (7-10%), and whether loans sit on DataSigns' balance sheet or are flipped to partner banks.15:19–18:13 · Nathan as informed peer 1/10 Mid-Roll Sponsor Break: Accounting Simplicity with FreshBooks Segment features a mid-roll FreshBooks advertisement followed by the standard Famous Five rapid-fire questions, during which Monish shares personal routines and preferences.18:14–21:44 · Nathan as informed peer 0/10 Episode Summary, Listener Reviews, and Partner Promotions Solo host outro covering episode recap, call for iTunes reviews, HostGator promo, and personal travel juice endorsement.1:32–6:05 · Guest teaching 5/10 Introducing Monish Anand and the Indian Credit Gap Monish educates Nathan on the credit gap in India where 400M people apply for loans and traditional banks reject most of them. Nathan asks straightforward clarifying questions regarding Monish's driver anecdote and how smartphone digital footprints substitute for traditional credit scores.6:06–9:13 · Guest teaching 4/10 MSME Partnerships, Financial Literacy, and Loan Traction Nathan presses Monish to distinguish between the 75,000 employees exposed to their HR partnership program versus the actual 10,000 app downloads. Monish explains their MSME factory onboarding strategy and initial loan volumes.9:13–15:17 · Guest teaching 4/10 Financing Rounds, Asset-Light Banking Model, and Team Growth Nathan digs deep into the unit economics, asking detailed questions about upfront points, loan shark IRR, interest rate spreads (7-10%), and whether loans sit on DataSigns' balance sheet or are flipped to partner banks.15:19–18:13 · Guest teaching 0/10 Mid-Roll Sponsor Break: Accounting Simplicity with FreshBooks Segment features a mid-roll FreshBooks advertisement followed by the standard Famous Five rapid-fire questions, during which Monish shares personal routines and preferences.18:14–21:44 · Guest teaching 0/10 Episode Summary, Listener Reviews, and Partner Promotions Solo host outro covering episode recap, call for iTunes reviews, HostGator promo, and personal travel juice endorsement.1:32–6:05 · Guest disagreement 0/10 Introducing Monish Anand and the Indian Credit Gap Monish educates Nathan on the credit gap in India where 400M people apply for loans and traditional banks reject most of them. Nathan asks straightforward clarifying questions regarding Monish's driver anecdote and how smartphone digital footprints substitute for traditional credit scores.6:06–9:13 · Guest disagreement 1/10 MSME Partnerships, Financial Literacy, and Loan Traction Nathan presses Monish to distinguish between the 75,000 employees exposed to their HR partnership program versus the actual 10,000 app downloads. Monish explains their MSME factory onboarding strategy and initial loan volumes.9:13–15:17 · Guest disagreement 1/10 Financing Rounds, Asset-Light Banking Model, and Team Growth Nathan digs deep into the unit economics, asking detailed questions about upfront points, loan shark IRR, interest rate spreads (7-10%), and whether loans sit on DataSigns' balance sheet or are flipped to partner banks.15:19–18:13 · Guest disagreement 0/10 Mid-Roll Sponsor Break: Accounting Simplicity with FreshBooks Segment features a mid-roll FreshBooks advertisement followed by the standard Famous Five rapid-fire questions, during which Monish shares personal routines and preferences.18:14–21:44 · Guest disagreement 0/10 Episode Summary, Listener Reviews, and Partner Promotions Solo host outro covering episode recap, call for iTunes reviews, HostGator promo, and personal travel juice endorsement.1:32–6:05 · Nathan pushing back 2/10 Introducing Monish Anand and the Indian Credit Gap Monish educates Nathan on the credit gap in India where 400M people apply for loans and traditional banks reject most of them. Nathan asks straightforward clarifying questions regarding Monish's driver anecdote and how smartphone digital footprints substitute for traditional credit scores.6:06–9:13 · Nathan pushing back 4/10 MSME Partnerships, Financial Literacy, and Loan Traction Nathan presses Monish to distinguish between the 75,000 employees exposed to their HR partnership program versus the actual 10,000 app downloads. Monish explains their MSME factory onboarding strategy and initial loan volumes.9:13–15:17 · Nathan pushing back 4/10 Financing Rounds, Asset-Light Banking Model, and Team Growth Nathan digs deep into the unit economics, asking detailed questions about upfront points, loan shark IRR, interest rate spreads (7-10%), and whether loans sit on DataSigns' balance sheet or are flipped to partner banks.15:19–18:13 · Nathan pushing back 0/10 Mid-Roll Sponsor Break: Accounting Simplicity with FreshBooks Segment features a mid-roll FreshBooks advertisement followed by the standard Famous Five rapid-fire questions, during which Monish shares personal routines and preferences.18:14–21:44 · Nathan pushing back 0/10 Episode Summary, Listener Reviews, and Partner Promotions Solo host outro covering episode recap, call for iTunes reviews, HostGator promo, and personal travel juice endorsement.

speaking balance: gold is Nathan, purple is the guest (3 minute bins)

0:00 · Nathan 74.6% · guest 25.4%0:00 · Nathan 74.6% · guest 25.4%3:00 · Nathan 13% · guest 87%3:00 · Nathan 13% · guest 87%6:00 · Nathan 15.9% · guest 84.1%6:00 · Nathan 15.9% · guest 84.1%9:00 · Nathan 40.3% · guest 59.7%9:00 · Nathan 40.3% · guest 59.7%12:00 · Nathan 39.7% · guest 60.3%12:00 · Nathan 39.7% · guest 60.3%15:00 · Nathan 54.8% · guest 45.2%15:00 · Nathan 54.8% · guest 45.2%18:00 · Nathan 91.6% · guest 8.4%18:00 · Nathan 91.6% · guest 8.4%21:00 · Nathan 100% · guest 0%21:00 · Nathan 100% · guest 0%
Sharpest disagreement ▶ 11:06 Reframing riskier cohort definition

Monish gently reframes Nathan's assertion that his borrowers are a 'riskier cohort', clarifying that they simply lack formal financial histories rather than being inherently bad credit risks.

 Hardest push from Nathan ▶ 7:31 Pressing on actual app downloads

Nathan refuses to accept the 75,000 corporate reach figure as active users, twice pressing Monish until he reveals the actual download count is 10,000.

 Biggest teaching moment ▶ 12:01 Mechanics of Indian loan shark IRR

Monish breaks down the predatory mathematics of local moneylenders, explaining how deducting 36 dollars upfront on a 100 dollar annual loan creates a >50% effective IRR.

 Nathan holds their own ▶ 13:34 Unpacking the banking spread and balance sheet risk

Nathan demonstrates financial acumen by mapping out DataSigns' cost of capital (12-15%), retail lending rate (22-26%), and verifying that they operate an asset-light origination model without balance sheet liability.
the scores for every segment, with the reasoning behind each
ChapterTopicNathan as informed peerGuest teachingGuest disagreementNathan pushing backWhy
Introducing Monish Anand and the Indian Credit Gap 3502 Monish educates Nathan on the credit gap in India where 400M people apply for loans and traditional banks reject most of them. Nathan asks straightforward clarifying questions regarding Monish's driver anecdote and how smartphone digital footprints substitute for traditional credit scores.
MSME Partnerships, Financial Literacy, and Loan Traction 4414 Nathan presses Monish to distinguish between the 75,000 employees exposed to their HR partnership program versus the actual 10,000 app downloads. Monish explains their MSME factory onboarding strategy and initial loan volumes.
Financing Rounds, Asset-Light Banking Model, and Team Growth 6414 Nathan digs deep into the unit economics, asking detailed questions about upfront points, loan shark IRR, interest rate spreads (7-10%), and whether loans sit on DataSigns' balance sheet or are flipped to partner banks.
Mid-Roll Sponsor Break: Accounting Simplicity with FreshBooks 1000 Segment features a mid-roll FreshBooks advertisement followed by the standard Famous Five rapid-fire questions, during which Monish shares personal routines and preferences.
Episode Summary, Listener Reviews, and Partner Promotions 0000 Solo host outro covering episode recap, call for iTunes reviews, HostGator promo, and personal travel juice endorsement.

Statements from this episode (11)

Assertion Partly supported
Over 400M Indians apply for loans annually; under 1 in 7 succeed
“In India, over four hundred million people every year apply for loans, and less than one or seven actually manage to get a loan from banks and banks in a non-banking company.”
Monish Anand Apr 2, 2017 ▶ 2:37
Insight
Traditional credit underwriting calculus fails to accurately predict loan repayment behavior
“Well, what we really believe is that the calculus, which is often used to determine credit worthiness is not good enough to predict whether a person will pay back a loan.”
Monish Anand Apr 2, 2017 ▶ 3:33
Assertion Partly supported
India has over 1B phone subscribers; smartphones make up 61% of sales
“India has over one billion phones subscribers. Out of which, today's, 61% of the phones which are getting sold are the smartphones.”
Monish Anand Apr 2, 2017 ▶ 5:23
Assertion Partly supported
150 million Indians currently work for micro, small, and medium enterprises
“There are about hundred and fifty million Indians working for these small and medium enterprises.”
Monish Anand Apr 2, 2017 ▶ 6:39
Disclosure
DataSigns has an addressable base of 75,000 employees across 60 partner companies
“Today our entire universe is close to about 75,000 employees working in about, in working about sixty-odd companies, yeah.”
Monish Anand Apr 2, 2017 ▶ 7:25
Disclosure
DataSigns has disbursed 600 loans averaging 25,000 rupees with 18-month tenures
“We have given close to about 600 loans at an average ticket size of 25,000 rupees with a 10 year of about 18 months.”
Monish Anand Apr 2, 2017 ▶ 8:08
Assertion Not checkable as stated
Indian loan sharks typically charge an effective annual IRR of 56%
“In India, a loan shark typically charges close to about 56% to IRR.”
Monish Anand Apr 2, 2017 ▶ 8:21
Disclosure
DataSigns issues loans at an IRR of less than 28%
“We lend at less than half, half of that, yeah.”
Monish Anand Apr 2, 2017 ▶ 8:40
Disclosure
DataSigns expects to close a $5M equity round within 45 days
“We are raising another five million, which we should be closing probably in next about 45 days.”
Monish Anand Apr 2, 2017 ▶ 9:39
Assertion Not checkable as stated
DataSigns claims sole mandate from Indian banks to originate proprietary credit scores
“So what we are the only company in the country today where multiple banks and NBFCs have given a mandate to acquire these customers, risk assess these customers. Also you know, these companies accept a credit score. And they lend to these customers based on ou…”
Monish Anand Apr 2, 2017 ▶ 11:26
Disclosure
DataSigns operates an asset-light model, originating loans for partner bank balance sheets
“No, it's, we are flipping to the other banks. So we are absolutely asset light model. We help banks build the books. So these, this is, these are on the balance sheet of the banks.”
Monish Anand Apr 2, 2017 ▶ 13:40
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