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Playbook — Step 2
Fintech AI

Stack Selection

Which decisions constrain which, how hard each is to undo, and the things teams consistently build too early. The goal early on is not the best stack — it is the stack that leaves the most doors open.

Verified May 2026Free · No signupOfficial sources only
BeginnerStart here. No prior knowledge assumed.

Decide in dependency order

Stack decisions are not independent. Each one narrows the next, and taking them out of order means revisiting earlier ones.

Stack decisions, in dependency order
DECIDE IN THIS ORDER. Each one constrains the next.

1. LICENCE POSITION            -> decides whether you can own a ledger
2. LEDGER                      -> buy / rent / build (Module 08)
3. DATA RESIDENCY              -> decides which AI APIs and clouds are usable
4. EVENT BACKBONE              -> the integration contract everything speaks
5. IDENTITY PROVIDER           -> indirect anyway; pick on liveness quality
6. RISK STACK                  -> credit / fraud / AML per your product
7. CUSTOMER OPS PLATFORM       -> last, because escalation design matters
                                  more than the platform

REVERSIBILITY, honestly assessed

  Easy to change      support platform, fraud vendor, analytics tooling
  Painful             KYC provider (re-verification), decisioning platform
  Very hard           ledger / core, event schema, data model
  Effectively never   licence structure, entity structure

  Spend your thinking time in inverse proportion to reversibility.

THE DEFERRAL LIST - things teams build too early
  - a data warehouse, before there is data worth warehousing
  - a feature store, before two models share features
  - microservices, before there is a team per service
  - a custom rules engine, before the rules stabilise
  - multi-region, before one region is reliable
Note

Optimise for reversibility first and efficiency later. At low volume, the per-unit differences between platforms are dwarfed by your salary bill. The decisions that matter early are the ones you cannot unwind.

The three questions that settle most of it

1. Do you hold a licence? If not, the partner’s core is the system of record and you are building a control layer. That removes most of the ledger debate.

2. What is your go-live date? Under six months means BaaS. Six to eighteen means a SaaS core or BaaS. Enterprise cores do not land inside eighteen months regardless of budget.

3. How many engineers can work on infrastructure rather than product? Under five means BaaS. Five to fifteen means a SaaS core will consume most of them. Fifteen or more makes an enterprise core operable.

Answer those three honestly and the shortlist is usually one or two options.

Data residency comes earlier than you think

Most teams treat residency as a deployment detail. It is a constraint on the whole stack.

It determines which AI APIs you may call, where backups and disaster recovery copies live, whether a vendor’s support team can access production from outside India, and what your observability pipeline ships offshore by default.

Watch out

Observability is the one that gets missed. Shipping application logs to a foreign-hosted monitoring service moves transaction data offshore continuously, and nobody notices because it was chosen as a platform tool rather than as a data decision.

IntermediateBuild it. Pipelines, tools and working code.

What to buy, build and defer

ComponentDecisionWhy
Ledger / coreBuy or rentBuild is ~3–5x cost and 24–36 months to basic function
Shadow ledgerBuild, from day oneCannot be retrofitted. History you did not capture does not exist.
KYC / identityBuyAadhaar is indirect regardless; buy on liveness quality for your device mix
Document extractionBuy initiallyEngine choice matters less than the quality gate and validation around it
Sanctions dataBuy enrichedThe Bank of Scotland case turned on list enrichment, not algorithm
Screening logicBuild or configure yourselfThresholds are your risk appetite, documented
Fraud rulesBuild first, buy laterVelocity counters in week one beat any vendor integration
Credit modelBuild on bought dataYour repayment history is the moat
ReconciliationBuild the matching, buy at volumeStart with exact-reference matching; most volume clears there
Support platformBuyEscalation design is yours; the helpdesk is not differentiating
Model registryAdopt an open toolAn inventory that stays current beats a bespoke one that does not

The integration contract

The one thing worth designing carefully before writing much code: what your internal events look like.

Vendor-neutral events are what make every other decision reversible. If your services publish and consume your own event schema rather than a provider’s payloads, swapping the provider is an adapter rather than a rewrite.

Event design rules worth fixing early
PUBLISH FACTS, NOT COMMANDS
  customer.onboarded          not  create_customer
  payment.settled             not  update_balance
  loan.disbursed              not  mark_disbursed

EVERY EVENT CARRIES
  event_id            unique, stable
  sequence            monotonic per aggregate
  occurred_at         business time  <- when it happened
  recorded_at         system time    <- when we learned
  idempotency_key     replay-safe
  schema_version      with backward compatibility enforced in CI
  actor               who or what caused it

NEVER
  - vendor payloads passed through unchanged
  - events that assume a specific provider's field names
  - mutable events (corrections are NEW events)

WHY THIS IS THE HIGHEST-LEVERAGE EARLY DECISION
  Your ledger vendor, KYC provider, fraud vendor and support platform
  will all change within five years. Your event schema should not.
AdvancedShip it. Failure modes, thresholds and evidence.

The deferral discipline

Building too early is as expensive as building too late, and less visible because it feels like progress.

Defer untilThing
Two models share a featureFeature store
Analytics queries are hurting productionWarehouse
You have a team per serviceMicroservices
Rules change weekly and a deploy is the bottleneckRules engine
One region is reliably reliableMulti-region
Manual review cost exceeds the build costAutomated matching at volume
Vendor API limits actually bindCaching layer

The counter-list — things to build early even though they feel premature — is short and worth taking seriously: shadow ledger, decision logging with model and policy versions, outcome capture, and the model inventory.

Testing reversibility before you commit

Before signing anything material, answer these. Most teams cannot, which is itself the finding.

  • Can you export full transaction history, not just balances? In what format, how often, at what cost?
  • Does the contract guarantee export on termination, within how many days?
  • Have you actually run a full export and restored it? Not read the docs — run it.
  • What is vendor-specific in your code? Product logic in a vendor DSL is the usual trap.
  • If this vendor had a four-day outage, what stops?
  • How many critical functions sit with this one provider?
Watch out

Run a full export quarterly and restore it into a scratch environment. If you cannot reconstruct balances from the export, you do not have an exit — you have a clause.

A prompt for your stack decision

Prompt — paste into any AI
You are a fintech CTO who has built and later migrated core
infrastructure in India.

My situation:
- Product: [describe]
- Licence position: [describe]
- Go-live target: [months]
- Total engineers, and how many can work on infrastructure rather
  than product: [numbers]
- Year 1 and year 3 volumes: [accounts, transactions]
- Data residency constraints: [describe]
- Funding runway: [months]

Give me:

1. A specific stack recommendation, component by component, tied to
   MY constraints rather than general best practice.
2. For each component: buy, build, or defer - and if defer, the
   trigger that says build it now.
3. My internal event schema - the core events and required fields.
4. Which three decisions here are hardest to reverse, and what to do
   now to keep them reversible.
5. What I am likely to build too early, given my team.
6. A realistic year 1 cost picture including implementation and my
   own engineering time, not just licence fees.

Be sceptical of anything that sounds like the industry default.
Where vendor pricing is undisclosed, say so rather than estimating.

Sources

Every figure, rule and date on this page, and where to check it. Entries are typed so you can see which are primary-sourced and which are industry reporting.

  1. officialRBI outsourcing and IT governance directions — the constraints on vendor choice for regulated entities. www.rbi.org.in
  2. industryVendor documentation — the capability comparisons. See the build sheets for priced, dated figures.

Checked September 2026. Regulation in this area is actively developing; the date is part of the claim.

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