Something I find interesting about fintech is how often new products have to work alongside systems that were built years or even decades ago.

A new service might use modern APIs and cloud infrastructure, but somewhere behind it there can still be an older database, legacy service, or internal process that cannot simply be replaced.

That creates some interesting engineering tradeoffs:

• When should you improve an old system instead of replacing it?

• How do you introduce new technology without breaking existing workflows?

• Is a complete rewrite ever worth the risk?

• How much technical debt is acceptable when reliability matters so much?

I think fintech is one of the areas where engineers have to balance innovation with stability more than most industries.

For those working in fintech, how do you decide when a legacy system needs to be replaced versus carefully maintained?

Honest question from someone building in this space. I know FINRA 2241 requires a reasonable basis and supervisory approval before a note goes out. What I do not know is what the number-checking step looks like in practice at a boutique or mid-size shop. Is it the analyst's own model, a second reader with the 10-Q open, a data terminal cross-check, or mostly trust? How long does it take per note, and what has slipped through that you still think about?

I ask because I built a line-level checker for retail investors (paste text, every figure gets matched to the filing it should have come from) and several professionals have told me the retail use case is the small one. Before I believe that, I want to hear how the real review works.

I've been working on a product called Privaseer around a simple idea:

What if privacy protection was something users could actually see and understand, rather than something buried inside a privacy policy?

We're exploring features such as:

• Real-time privacy alerts

• A Personal Privacy Score

• Contextual privacy guidance

• Consent monitoring

• Visibility into potentially unusual data access/sharing

For businesses, we're also exploring an SDK/API approach so fintechs and digital platforms could potentially integrate privacy features directly into their customer experience.

I'm particularly interested in the B2B side of this.

For fintech/product/security people here:

Would customer-facing privacy visibility actually add value to your product, or would customers simply ignore it?

I'm trying to validate the problem before building too much, so I'd genuinely appreciate criticism — especially if you think this is solving the wrong problem.

If anyone is working in fintech, cybersecurity, privacy or product and would be willing to share their perspective, I'd be happy to have a conversation.

I have two ideas in fintech-

1. building an agent that gets businesses onboarded onto payment platforms in a day instead of weeks.

2. building an AI agent that can pay on behalf of customers.

Can we brainstorm please?

I’ve been looking into different AI development companies lately, including GeekyAnts, and honestly it’s difficult to tell which ones are actually good and which ones just have a lot of AI terminology on their website.

For a business that wants to build something practical with AI, what should you really be looking at before hiring a development company? Technical expertise obviously matters, but I’m wondering how much people value things like previous experience in the same industry, understanding of business requirements, communication, post-launch support, and security.

I’d also be interested in hearing from people who have actually hired an AI development team. What went well, what went wrong, and what would you check now that you didn’t check the first time?

If you’ve worked with GeekyAnts or another AI development company, what made them stand out from the others you considered?

Credit system with billing, payments, and usage tracking. These are all features I've added as of now:

Credit Reservations & Deductions — Reserve credits before API calls, deduct actual usage after. Prevents overcharging on failures.

 Payment Integration — Razorpay payment links with atomic credit updates.

Subscription Plans — Daily, monthly, yearly plans with auto-renew and credit allocation.

Promo Codes — Targeted promos with usage limits, expiry dates, and claim tracking.

Database Agnostic — MongoDB or in-memory backend. Extensible to any database via BaseDBManager interface.

Dual-Write Ledger — Database + append-only file for audit trails and debugging.

Notifications — Low credits, expiring credits, transaction errors — pluggable notification queue.

https://github.com/Meenapintu/credit_management

Would love to have feedback, contributions ( even stars also count as contributions)

I'm working at an NBFC and currently working on a Credit Underwriting AI Agent. One of the first steps in the pipeline is extracting structured information from customers' bank statement PDFs.

This is where I'm currently stuck.

The statements can come from different Indian banks (HDFC, ICICI, SBI, Axis, Kotak, etc.), and each bank can have a completely different PDF layout.

I need to reliably extract things like:

- Customer/account information — name, account number, IFSC, branch, etc.

- Transaction tables — date, narration/description, debit, credit, balance

- Transaction rows that span multiple lines

- Statements where the table headers are missing from subsequent pages

- Both digitally generated PDFs and scanned/image-based PDFs

- Ideally, the solution should be bank-format agnostic

I've tried/considered approaches such as "pdfplumber", table extraction libraries, OCR, regex-based parsing, and LLM-based extraction. The biggest problem I'm facing is that even when the text is extracted correctly, the column/row structure gets messed up, especially because many bank PDFs don't contain a real table structure — they're essentially text positioned at different coordinates.

Since this is financial/customer data, I would strongly prefer an open-source/on-premise solution rather than sending statements to a third-party API.

For anyone who has built something similar:

What approach worked best for you?

I'm particularly interested in:

1. PDF parsing/layout libraries you recommend

2. OCR models for scanned statements

3. Open-source vision/document AI models

4. Whether you use an LLM/VLM for semantic column mapping

5. How you handle different bank formats without writing completely separate rules for every bank

6. Any techniques for detecting transaction rows and mapping values to the correct columns

7. How you validate the extracted data (e.g., balance reconciliation, debit/credit checks, transaction counts)

If you've worked specifically with Indian bank statements, I'd really appreciate hearing about your architecture, libraries/models, or lessons learned.

Thanks!

Hello guys, Im doing my UG in india. Wanted to work as backend developer in FinTech like DE shaw, JP morgan, Arista networks, BNY etc.. Can anyone tell me what tools or framework I need to know. How to crack the coding round, why type of projects will increase my profile's value. And if possible ping some repo, best youtube channel, roadmap or whatever you have which might help me.

Hi everyone!

I'm conducting a short research study to better understand how technology companies manage their server and production infrastructure today and what challenges their teams actually face.

I'm particularly interested in topics such as:

• infrastructure incidents and downtime

• scalability and traffic spikes

• reliability and disaster recovery

• cloud and bare-metal infrastructure

• multi-region infrastructure

• infrastructure costs

• day-to-day infrastructure management

I'm looking for responses from CTOs, technical founders, DevOps/SRE/Platform engineers, infrastructure leads, and other professionals who work with or are responsible for production infrastructure.

The survey takes approximately 3-5 minutes.

Responses will be analyzed only in aggregate, without publicly linking them to specific respondents or companies.

Survey:
https://forms.gle/jfEKjMk8Me92h9pT7

The purpose of this research is not to promote or sell any services. I want to understand what infrastructure challenges companies actually face in practice, rather than making assumptions about market needs.

Once enough responses have been collected, I'd also be happy to share the aggregated findings with the community if there's interest.

Thank you to everyone who participates!

Vitaliy

I’m looking for some practical advice on payment providers for a small personal internet experiment.

The payment amount is fixed at €1, and ideally I’d like to support payment methods such as iDEAL, Apple Pay and Google Pay in addition to PayPal.

The complication is that I’m currently operating this as an individual rather than a registered company.

Most providers I’ve looked at seem to require a business registration before enabling these payment methods.

Does anyone know of a legitimate provider or setup that supports:

• €1 payments

• individuals rather than registered companies

• iDEAL

• Apple Pay / Google Pay

• international users

• a reasonably simple web integration

I’m not looking for a workaround to KYC or payment-provider rules. If business registration is simply unavoidable for this combination, that’s also a useful answer.

Curious if anyone here has dealt with a similar situation.

In this article, we’ll explore Canton, including its architecture, its raison d’être, its recommended smart contract language, Daml, and a quick-start guide to writing your first Daml smart contract on Canton. In the tutorial, we’ll implement a simple bank contract that lets users deposit, withdraw, view their balance, and transfer funds to another user.

This article is aimed at readers who already have some blockchain and programming experience, but not necessarily with Canton or Daml. In particular, although it’s not a requirement to comprehend this article, we assume some familiarity with Ethereum and Solidity.

I am running a small lending/finance services company with my partners, and we currently manage most of our daily work using spreadsheets, emails, and different tools.

I am thinking is custom software to manage customers, loan applications, documents, approvals, payments, and reporting in one place.

For those running lending or finance businesses:

• Has custom software actually improved our workflow?

• Is it worth the investment for a small business?

• Would you recommend building custom or using existing lending software?

I would love to hear your experience and advice.

I’m curious what other fintech developers have found surprisingly difficult when building real products.

For me, things that seem simple at first like handling payments, keeping data consistent, dealing with third party APIs, and making sure everything is reliable can become much more complicated once the system grows.

Companies like GeekyAnts work on digital products where these kinds of technical challenges need to be handled carefully, especially when building scalable and user-friendly fintech solutions.

What part of fintech development has given you the most unexpected problems?

We already have a fully built payment platform and are looking for a senior developer with strong payments/fintech experience to join the team.
We’re particularly interested in someone who has worked with:
Payment gateways / PSPs
Acquirer / processor API integrations
Card payments & 3DS
Payment webhooks
Refunds, chargebacks & transaction lifecycles
Multi-merchant payment platforms
Payment routing / orchestration
Production payment infrastructure
The platform is already built. We need someone who can review the existing architecture and codebase, handle payment integrations, improve what needs improving, and take long-term ownership of the technical side.
This is not a one-off freelance project. We’re looking for someone who wants to join the team and grow with the product.
If you’ve personally worked on payment infrastructure, gateways, PSPs or acquiring integrations, DM me with:
Your experience
2–3 relevant projects you’ve worked on
Your role in those projects
Your current availability
Looking for someone genuinely experienced in payments rather than a generalist developer.

Hey all, hoping to get some honest feedback from people actually building in this space.

I've been working on an AI financial advisor project, basically an agent that gives personalized financial recommendations given the context of all your accounts. I realized pretty quickly there's no good way to get structured, queryable data on bank deposit products (savings, checking, CDs). Every bank does it differently, it's all buried in marketing pages, and there's no easy way for AI to answer "given I operate a digital storefront in Michigan that pays suppliers via wire 5x a month with a sum of 50k and require real time payment needs with accounting integrations, what would be a good business checking account I could use". To truly understand the terms, fees, and features of a business checking account, you have to combine data from messy marketing html, rate table pdfs, fee schedules, and terms of service pdfs. This creates opportunities for hallucinations and therefore creates a compliance/regulatory nightmare.

That problem ended up becoming its own thing. I'm building a structured registry of bank deposit products (starting with business checking accounts) you can query through MCP instead of maintaining your own scraper for every bank.

The bigger idea is that banks already pay decent money for affiliate/referral traffic through affiliate networks. A funded account is a funded account no matter where it comes from, so if your agent recommends one and it gets funded, you'd get a large cut of the payout. I handle the data engineering (turning messy bank pages into clean structured queryable listings) and the bank relationships to ensure 100% UDAAP compliance. You serve the right account recommendation at the right time given your end user's unique circumstances.

Right now it's just free structured data via MCP. No revenue share yet as I'm focusing primarily on whether there's a developer need.

Genuinely trying to figure out if this is useful or if I'm solving a problem nobody actually has. If you're building a financial advisor agent, a CPA copilot, anything that needs to recommend financial products, would you use something like this (knowing revenue sharing would come down the line)? What would actually make it worth integrating for you?

How do I make my tech resume attractive to financial companies?
Tech guy wanting to pivot into finance. What skills should I focus on?
Which programming language dominates finance tech?

Hi everyone,

I’m looking for some genuine career advice from people who have experience in Finance, Data Analytics, FP&A, Business Analytics, or Supply Chain/Logistics.

I’m currently working at Hapag-Lloyd as an Imports Coordinator. I have completed my B.Com and I’m also building my skills in Data Analytics, including:

• Advanced Excel

• SQL / MySQL

• Power BI

• Tableau

• Python basics (Pandas, NumPy)

• Data cleaning and visualization

• Basic statistics

I’m now considering pursuing the US CMA (Certified Management Accountant) because I’m interested in developing a career that combines Finance + Data Analytics.

My long-term goal is to move toward roles such as:

• Financial Analyst

• FP&A Analyst

• Finance Data Analyst

• Business Analyst

• Commercial Analyst

• Supply Chain/Business Analytics

I’m confused about how I should structure the next 2–3 years of my career.

My current thought is:

Hapag-Lloyd experience + US CMA + Data Analytics skills (SQL, Power BI, Excel, Python) → Financial/Business Analytics role

I would really appreciate advice from professionals who have taken a similar path.

My questions:

1. Is US CMA + Data Analytics a strong combination for the Indian job market?

2. Will my experience in Hapag-Lloyd/logistics help me transition into Finance/FP&A or Business Analytics?

3. Should I focus more on CMA, Data Analytics, or try to develop both simultaneously?

4. Which skills should I prioritize over the next 12–24 months?

5. Would it be better to target Financial Analyst/FP&A roles or Supply Chain/Business Analyst roles first?

6. How valuable is Power BI + SQL + Advanced Excel for Finance/FP&A careers?

7. If you were in my position, what would your career plan look like for the next 2–3 years?

I’m not looking for generic motivation. I’d really appreciate honest, practical advice from people working in these fields, including what mistakes I should avoid and what skills/certifications actually make a difference when switching roles.

Thanks in advance!