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Having worked with multiple fintech platforms launching Fixed Deposit products — from neobanks to stock brokers to payments super-apps — we've seen patterns in what goes wrong. These aren't theoretical risks; they're actual mistakes that cost teams months and lakhs.
Here are the seven most common ones.
The temptation: "We need 8-10 banks on day one to offer competitive rate comparison."
The reality: Each bank integration takes 3-6 months. Starting with 8 banks means you're looking at 12-18 months before launch — by which time the competitive window may have closed.
What works better: Launch with 2-3 well-chosen issuers that cover the rate spectrum:
This gets you live in weeks, not months. Add more issuers incrementally based on user demand and rate gaps.
The platforms that launch fastest and iterate — adding issuers based on actual user preference data — consistently outperform those that try to launch with a complete issuer lineup.
The temptation: "We'll handle compliance in the last 2 weeks before launch."
The reality: RBI KYC Master Direction compliance, Aadhaar consent management, VKYC infrastructure, DICGC disclosure management, TDS handling, and Form 15H/15G support are each significant engineering and legal workstreams.
What compliance actually involves:
| Compliance Area | What's Required | Typical Effort | |----------------|----------------|----------------| | Aadhaar eKYC | UIDAI integration, consent capture, data handling | 4-6 weeks | | Video KYC | Scheduling, video infrastructure, 11-state machine | 6-8 weeks | | PAN verification | NSDL/UTIITSL integration, senior citizen detection | 2-3 weeks | | Consent management | Audit trails, consent text versioning, regulatory reporting | 3-4 weeks | | DICGC disclosures | Auto-display for banks, auto-suppress for NBFCs | 1-2 weeks | | TDS information | Threshold display, Form 15H/15G reminders | 1-2 weeks |
That's 4-6 months of compliance engineering — not 2 weeks.
And it's not a one-time cost. Every RBI circular, every KYC rule change, every new VKYC requirement needs to be implemented and tested. Compliance is an ongoing operational expense.
The temptation: "We need custom KYC flows to match our app's UX perfectly."
The reality: KYC for FD booking involves 4 distinct verification methods (Aadhaar eKYC, CKYC, VKYC, DigiLocker), each with its own API integration, consent requirements, and bank-specific variations.
Building a KYC engine that handles all four methods across multiple banks — with proper consent management and audit trails — is a multi-quarter project.
What works better: Use existing KYC infrastructure. Whether that's a standalone KYC provider or a full FD infrastructure platform with KYC built in, avoid building the verification layer from zero.
The KYC flow is a solved problem. Your engineering time is better spent on your core product — the user experience that differentiates your platform.
The temptation: "We'll integrate Razorpay and payments will just work."
The reality: FD payment processing has 20-30% first-attempt failure rates. This is normal for bank-focused transactions (higher than e-commerce) and requires robust handling:
And remember — different banks use different gateways. You're not integrating one payment system; you're integrating 5-7 and routing between them.
What works better: Budget 2-3 months specifically for payment infrastructure. Build retry logic, background status polling, and reconciliation from day one. Or use a platform that's already solved multi-gateway payment orchestration.
The temptation: "We'll add premature withdrawal later. For now, let's just handle booking."
The reality: Users will want to break their FDs. Life events — medical emergencies, job changes, large purchases — don't wait for your product roadmap.
If you launch without a premature withdrawal flow, your customer support team becomes the withdrawal interface — manually coordinating with banks for every closure request. This doesn't scale.
What premature withdrawal involves:
| Component | Complexity | |-----------|-----------| | Penalty calculation (varies by bank, tenure, elapsed time) | Medium | | Bank-specific closure APIs (different per issuer) | High | | Partial withdrawal (some banks allow, others don't) | Medium | | Refund processing back to user's account | Medium | | Tax implications (TDS on accrued interest) | Low |
What works better: Plan the withdrawal flow from day one — even if you don't build it for V1. At minimum, ensure your data model and bank integrations support closure queries. And communicate withdrawal terms clearly during booking to set expectations.
The temptation: "Let's build the FD vertical separately, with its own team and infrastructure."
The reality: FDs create the most value when they're deeply embedded in your existing product — not siloed as a separate section.
The highest-performing FD implementations we've seen are those where FDs are woven into the user's financial journey:
What works better: Integrate FDs into your existing product surfaces from day one. The FD booking flow can be a separate module, but discovery, portfolio, and re-engagement should be native to your app.
A platform that treats FDs as a tab in "More Products" will see 2-3% discovery rates. A platform that nudges FDs in high-intent moments sees 10-15%.
The temptation: "We'll negotiate the highest possible commission rate with issuers."
The reality: The pricing structure matters more than the rate. Two models exist:
The common mistake: Optimizing for per-booking fees when trail would generate more lifetime revenue. Or negotiating trail rates that are too thin to justify the integration effort.
What works better: Model both scenarios for your expected volumes:
| Volume | Per-Booking (Rs 150/booking) | Trail (15 bps) | |--------|----------------------------|----------------| | 100 bookings/month, Rs 50K avg | Rs 15,000/month | Rs 7,500/month (Year 1) | | 1,000 bookings/month, Rs 50K avg | Rs 1,50,000/month | Rs 75,000/month (Year 1) | | Same 1,000/month in Year 2 | Rs 1,50,000/month | Rs 1,50,000/month (cumulative AUM) |
Trail takes longer to catch up but generates more lifetime value — especially with renewals. For most platforms, a blended model (moderate per-booking + trail) provides the best balance of short-term and long-term revenue.
All seven mistakes share a common root: underestimating the complexity of financial product distribution.
FD distribution isn't a simple API integration. It's a multi-bank, multi-gateway, compliance-heavy system that requires ongoing operational management. Teams that treat it as a 2-month side project end up spending 12+ months and 5x their budget.
The teams that succeed are the ones that either:
Both paths work. The mistake is choosing something in between — underestimating the build, under-investing in the team, and ending up with a half-built system that doesn't convert.
Blostem has solved these challenges for platforms like Zerodha, Jio, MobiKwik, Jupiter, and Upstox. Talk to our team about launching FDs the right way.
Get in touch with our team to discuss how Blostem can power your platform.
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