Quick answer: New to credit Indians are often treated as one lending segment, but they are not. A first salary borrower, a gig worker using multiple credit apps, and a small shopkeeper taking a first formal loan may all look similar on a dashboard, while their risk, credit behaviour, and future outcomes are completely different.
The first time you realise new to credit is not one segment at all is usually not in a risk pack.
It is in a stray conversation that does not fit the slides.
In one retail SteerCo I sat in, the unsecured head was presenting a neat update:
new to credit share of disbursals up from 18% to 27%,
early loss rates within plan,
score and rule based filters performing as expected.
One bar chart showed vintage curves for NTC vs non NTC.
The lines were close enough for everyone to relax.
The business pitch was simple:
“This is our future franchise.
Young, first time borrowers.
Controlled ticket sizes.
If we are careful at onboarding, risk is manageable.”
The discussion moved on to rate grids.
Later that week, I sat with a small group of field and collections staff for a different review.
We started talking about tough cases in the NTC pool.
One officer mentioned a 24 year old in a Tier 2 city who took a first PL to fund a training course, then lost his job when the company wound down.
“He thought missing one EMI would spoil his record with
our bank.
He had no idea it would follow him into every future loan discussion.”
Another described a platform worker in a metro:
“He has never had a formal loan before.
But there are four apps on his phone giving him short term credit.
In his head, these are just top ups.
On the bureau, it is the start of a pattern.”
On paper, all three were new to credit Indians.
In reality, they were three completely different lives carrying the same label.
Inside most institutions, the comfortable belief is still:
“New to credit is a growth engine with known, contained
risk.
If our entry filters are tight, we understand this segment well enough.”
The more you listen to actual stories, the less that sentence holds.
For lenders, NBFCs, and fintechs across India, from Mumbai, Pune, and Bengaluru to Indore, Jaipur, Lucknow, Patna, and smaller cities, this matters because first formal credit often shapes future risk, future trust, and future credit behaviour.
Because first time formal borrowers come from very different income realities, digital habits, work patterns, and financial histories.
A salaried graduate in Pune, a delivery worker in Mumbai, and a small shopkeeper in a Tier 3 town may all appear as thin file or first trade cases in a bureau. But their actual financial life, shock absorption capacity, and response to stress are very different.
That is why new to credit borrowers in India should not be treated as one standard pool.
If you listen across Indian banks, NBFCs, and consumer fintechs, the NTC narrative is reassuring and tidy:
“India’s formal credit penetration is still low.
The big opportunity is first time borrowers.
We’ll onboard them with small tickets, short tenors, and strict filters.
Over time, we’ll grow with them.”
It shows up everywhere.
In a product deck for a new NTC personal loan:
Slide title: “First Loan Strategy: Controlled Growth in Emerging India”
Bullets:
minimum bureau footprint or surrogate criteria,
low ticket size from ₹50,000 to ₹1 lakh,
12 to 24 month tenors,
strong employer or income checks where available.
Comfort line near the bottom:
“Loss rates expected to be slightly higher than core, but acceptable for franchise value.”
In a Board conversation:
“We cannot build a ten year book by only lending to
existing credit card customers.
We need new to credit youth.
Our models and rules will protect us.”
In a risk policy document, there is often:
a neat section called NTC with
slightly higher score or surrogate thresholds,
stricter DTI caps,
channel restrictions such as only certain partners or only digital journeys
with full KYC.
Underneath all of this sits a sentence you will hear in some form in many rooms:
“New to credit Indians are more volatile, but if we filter them well at entry, the rest behaves like any other retail pool.”
On the surface, it feels reasonable.
The uncomfortable truth is that for new to credit Indians:
we know far less than we think at onboarding, and
our first decisions shape their risk as much as they reveal it.
That is where the models and the stories diverge.
If you stay at the portfolio level, NTC often looks under control:
slightly higher early delinquency,
slightly steeper vintage curves,
losses within a band everyone agreed to in the business case.
The problems usually sit one layer down.
Three patterns repeat across lenders:
We treat wildly different NTC lives as one segment because the bureau is blank or thin.
We copy big pool behaviours, such as pricing, communication, and collections, onto people at their most fragile credit moment.
We underestimate how much our own early actions harden their future risk.
The reason it stays invisible early is simple:
Dashboards were never designed to show you which parts of your NTC book are learning and which parts are breaking.
The cost is not only charge offs.
It shows up as:
higher long term roll rates in cohorts that started
NTC,
reputational drag in communities where the first formal credit experience went
badly,
and a quieter loss of optionality, segments you no longer touch because of
scars created in their first few loans.
To see it clearly, it helps to get away from NTC pool language and look at a few real lives.
The first is the story risk teams like to tell when they speak about NTC.
A 23 year old engineer in Pune, first job in a mid size IT firm.
She opens a salary account with a large private bank.
Within months:
the app starts nudging, “You’re eligible for a credit
card”,
a pre approved personal loan limit quietly appears.
On the bureau:
there is almost nothing, one enquiry, maybe a small
consumer loan,
after six months, her first trade shows up.
Internally:
she is tagged as NTC for the first trade,
quickly graduates to early vintage, prime if she pays on time.
Her story matches the product decks:
small initial exposure,
clean behaviour,
gradual move into core franchise.
When management thinks new to credit Indians, this is often the composite picture in their heads.
It does exist.
It just is not the only story.
The second story lives mostly in collections notes and call logs, not in Board packs.
A 26 year old delivery partner in a metro.
On paper:
no prior formal loans,
no credit card,
thin or blank bureau.
In life:
four BNPL or small ticket apps on his phone,
advances from the platform,
one small personal loan from a fintech that paid out into his wallet.
He does not think of these as loans.
They are:
top ups,
settlements with the app,
early wages.
When one personal loan from a regulated NBFC goes bad:
he misses EMIs in a slow month,
the app and call centre scripts mention CIBIL,
he is not sure what that means, but he knows he is in trouble with this lender.
On the bureau, over the next 6 to 12 months:
trades from different apps and NBFCs start appearing,
short tenor products open and close,
one or two show persistent DPD.
Internally, in the first lender he ever touched:
he is just counted in the NTC pool for a digital
personal loan,
booked at a small ticket size,
written off as a contained loss if things end badly.
Five years later, when he applies for a modest home loan in a smaller city, no one remembers the app scripts or the platform income volatility.
They see:
a mid 600s score,
short tenor personal loans and BNPL trades with issues,
NTC risk done badly somewhere else.
He is still technically new to core products.
He is no longer new to bureau scars.
The third story rarely appears in NTC product decks, but you see it in PSU and NBFC books.
A 35 year old shopkeeper in a Tier 3 town.
He has run his business for a decade using:
wholesaler credit,
local moneylenders,
family contributions.
He takes his first formal business loan from a small NBFC:
term loan against shop cashflows,
ticket size around ₹3 lakh to ₹5 lakh,
basic documentation.
On the bureau, before this loan:
there may be a Kisan card,
an old gold loan,
or nothing at all.
He is NTC for the institution’s unsecured book.
For him, formal credit is a test:
Is this more reliable than the local financier?
Is the paperwork worth the hassle?
Does the lender behave predictably if things go off plan?
If the product is pushed aggressively and early stress is handled mechanically:
he may go through harsh collections for a relatively
small overdue,
lose face in his local market,
decide never again for formal lenders.
Six years later, when policymakers ask:
“Why are not more small businesses using formal credit?”
this first experience is rarely on the slide.
On risk dashboards, his case sits under:
NTC SME vintage 2019, 3 plus bucket or write off.
The story is richer than the cell.
Given these three very different lives, why does new to credit still look like one manageable segment in most institutions?
Because most artefacts were never designed to distinguish them.
A few typical blind spots follow.
In most policy documents, NTC means:
no prior bureau history, or
very short history below some vintage threshold.
That definition collapses:
a new salaried graduate in a metro,
a platform worker with heavy app based credit,
a mid 30s small business owner meeting formal bureaus for the first time.
They all look the same on the first NTC dashboard:
first trade or first 12 to 18 months of visible credit.
So when someone presents:
NTC performance vs non NTC,
NTC share of disbursals,
NTC GNPA vs plan,
they are averaging across stories that behave very differently when stress hits.
Most business cases for NTC products bake in:
a few percentage points higher expected loss,
in exchange for franchise value and future relationship.
So when actual losses come in slightly higher than core but within that bound, nobody looks deeper.
The early warning decks show:
NTC GNPA higher by 80 to 120 bps vs non NTC, within
tolerance,
some commentary on channel mix, partner performance, and vintage.
Very few decks:
cut NTC by age, income type, geography, and product
path,
or ask what share of later stressed core customers started with NTC episodes.
The extra loss is treated as the cost of growth.
The design flaws baked into some NTC journeys remain.
Most of what is interesting about NTC sits in:
branch manager anecdotes,
field collection notes,
complaint logs,
long emails from customers trying to understand why a small, early mistake
will not go away.
These rarely make it to SteerCo slides or Board packs.
What does:
neat charts of NTC disbursals by month,
tidy vintage curves,
high level partner names,
average scores after the first trade.
So the institution keeps asking:
“Is NTC on plan as a segment?”
instead of:
“Which kinds of new to credit Indians are we testing
our system on,
and what are we teaching them about formal credit in the first three years?”
That second question is where risk and franchise value meet.
It rarely gets airtime.
They do not avoid first time borrowers.
They get more specific about which new to credit lives they are dealing with, and what their own system does to those lives.
This is where new to credit lending strategy in India becomes less about one pool and more about segment design, early experience, and long term portfolio learning.
The institutions that seem calmer about NTC over a five to seven year horizon do not avoid first time borrowers.
They get more specific about which new to credit lives they are dealing with, and what their own system does to those lives.
A few practical patterns repeat.
Instead of one NTC block, they explicitly create sub views, for example:
salaried below 30, urban, first job or early career,
gig or platform workers with high app activity,
self employed or small business owners coming into formal credit late,
rural and semi urban salaried.
In internal MI, you then see pages like:
NTC performance, salaried early career vs gig vs SME,
subsequent personal loan or card vintages for customers who started NTC in
each sub segment.
This does two things:
stops people talking about NTC risk as if it were one
thing,
surfaces which early designs are building stable relationships vs storing
problems for later.
You do not need a fancy model for this.
You need to decide you care.
In some institutions, you can feel a tone in NTC discussions:
“We’ll give them a small chance, see how they behave.”
More mature teams flip the lens slightly:
“This is our first impression too.
If we design this badly, we are teaching them the wrong lesson.”
You see that in small design choices:
NTC products with clear, plain language communication about dues, dates, and consequences, rather than copied scripts from prime segments.
Slightly more forgiving operational flows for genuine first time confusion, while still protecting the book.
Better handover from collections so that one early mis step does not automatically poison every future interaction.
They are not soft on NTC.
They are deliberate about which messages the system sends in the first stress event.
Instead of just looking at NTC as a first product issue, they add a simple flag in data:
customer’s first formal loan or trade visible to us, or in bureau, was NTC with us.
Then, in personal loan and card decks, you see:
performance of current vintages, NTC origin vs non NTC
origin,
cut further by channel and early experience.
In more than one lender, this analysis quietly changed strategy:
For some NTC designs, later behaviour was similar to core once income stabilised.
For others, cohorts with a messy NTC start remained fragile in multiple products.
The response was not a grand statement about serving new India.
It was:
closing or redesigning specific NTC pathways,
tightening some partners,
adjusting early limit upgrades for certain origin types.
It is unglamorous, but it is how NTC becomes a real franchise, not a permanent experiment.
It is tempting to see clean early behaviour in NTC and quickly:
increase limits,
cross sell personal loans or cards,
treat the customer as graduated.
More cautious teams apply simple brakes:
minimum behavioural vintage before major upgrades,
additional checks for high volatility occupations and geographies,
slower graduation for customers whose NTC cleanliness sits on very thin income
or savings buffers.
They still reward good behaviour.
They just remember that:
a six month clean history in a first job is not the
same as five years of stability,
and a gig worker’s early good behaviour may be hiding more volatility than the
bureau can see.
It means first formal credit should be treated as a design moment, not just a filtering exercise.
For Indian lenders, especially those growing across salaried youth, gig workers, semi urban borrowers, and small business owners, NTC portfolio analysis, onboarding design, collections experience, and later vintage tracking need to work together.
The real question is not only whether NTC losses are within plan.
It is whether your first credit experience is building stable future borrowers or creating long term bureau scars that reappear in later books.
It is easy, sitting in a central office, to talk about:
NTC share of book,
NTC GNPA vs plan,
NTC as our growth engine for the next decade.
It is harder to sit with one new to credit Indian and trace what happens after something goes wrong the first time.
A missed EMI because a job ended suddenly.
A dispute with a lender they did not know how to escalate.
A small write off that sits on their file while life moves on.
On our side of the table, these episodes become:
one line in a bureau report,
one row in a write off MIS,
one dot in an NTC vintage chart.
On their side, it is often:
the moment formal credit goes from opportunity to dangerous and unpredictable.
If there is one uncomfortable question worth asking at the next NTC discussion, it might be this:
“Take ten of our stressed customers whose first trade
was with us.
If we replay their first three years in the system,
how much of their current risk was already inside them,
and how much did we harden by the way we designed and ran their first formal
loan?”
There is not a neat percentage answer.
There is usually a pause.
At Arth Data Solutions, when we look at NTC data in Indian books, that is the pause we care about.
Not because it changes PD calculations in a
spreadsheet,
but because it reminds everyone in the room that new to credit is not a
segment to exploit,
it is a set of lives whose stories our systems are helping to write, for
better or worse.
New to credit borrowers are people entering the formal credit system for the first time or with very limited visible bureau history. This can include salaried freshers, gig workers, small business owners, and first time formal borrowers in semi urban or rural markets.
Because borrowers grouped as NTC may have very different financial lives. A blank or thin bureau file does not show income volatility, use of short term credit apps, informal debt dependence, or how fragile the borrower’s financial cushion is.
Because most NTC dashboards are built around bureau status, vintage curves, and portfolio averages. They rarely separate different borrower life contexts or track how the first formal credit experience affects later behaviour.
Lenders should segment NTC borrowers by life context, design first loan journeys more carefully, track NTC origin in later portfolios, and avoid treating early clean behaviour as full maturity too quickly.
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