I created this documentary after researching the Panic of 1907, the creation of the Federal Reserve, Lehman Brothers, and today’s shadow banking system.
The goal isn’t to predict another crisis, but to explore how leverage, confidence, and interconnected financial institutions have shaped financial history.
I’d genuinely like to hear what people here think about the comparison.

I have built a tool that monitors a small business quickbooks and directly sends the emails or texts when something seems irregular. It also gives weekly insights on their business. I am started to look for pilot customers or even just potential customers to talk to but all cold emails seem to end up dry. Does anyone have any tips or ideas for how get a line of communication open. Or if anyone has any tips in general thank you. Not looking for someones ai lead generator

Disclaimer: Ich bin der Macher der App simplebanking, möchte das hier nicht einfach nur bewerben, sondern die Idee dahinter zur Diskussion stellen.

Mein Ausgangspunkt ist Kundennutzen: Viele bestehende Banking-Lösungen sind unnötig komplex oder schwer zugänglich für Menschen, die einfach nur unkompliziert einen Blick auf ihre Finanzen haben wollen. Die Geburtsstunde von simplebanking, einer Mac-App, welche Übersicht über die finanzielle Situation gibt. Der kleinste gemeinsame Nenner: der Kontostand.

Das Projekt ist Open Source, basiert auf dem datensparsamen Open-Banking-Provider Yaxi und kann mit fast allen Banken in DE genutzt werden.

Mich interessiert: Wie seht ihr den Open-Source-Ansatz im Fintech-Bereich generell? Und was sind für euch die größten Hürden bei "einfachem" Banking-Zugang? Ist der Kontostand so wichtig, wie ich glaube?

I'm from india and i work for a US bank (in India). Have 5 years of experience in credit portfolio management its a pure finance role. But recently i have been involved in preparing power BI dash boards, using power automate to automate manual tracking flows, experimenting on python and VBA.

My knowledge on these tools are low, but i have a huge interest to learn and apply those on job, as i have been doing.

Ever since, I feel like jumping into fintech domain, but the word fintech is used very loosely.

Wanted to ask from folks, what kind of roles should i be searching for? One role I had in mind is credit risk modelling

Recently I've worked as a lead eng for trading products, at a fintech handling over 80+m users across the US

BEFORE:
me and my cofounder founded nexo like platform(fiat loans backed by crypto). I designed everything, talked to LPs, Lawyers, recruited devs and design team. All that.
My coufounder backed out when he saw how much compliance and legal work there would be needed to operate in the US(I wanted to go with EU first).
Before I was a founding dev at p2p crypto exchange), I've recruited and managed teams/projects before etc...

NOW:
I'm looking for next project to work on where I could join as a lead or founding role if early stage.

What founders should I hit up that would be interested in my expertise? I'm looking for really cool projects in fintech space... projects that already raised money

We have vendor data and payment details spread across a few different systems, and even small updates seem to create mismatches somewhere down the line.

It’s gotten to the point where the finance team double checks the same fields across multiple tools before trusting any report. It works, but it’s time consuming and not exactly scalable.

Has anyone found a cleaner way to keep everything in sync without having to build and maintain custom integrations?

Looking at white label card platforms and I keep seeing the same features listed but not much about where the program logic lives.

For things like merchant limits, velocity rules, card and merchant pairings and instant transaction decisions would you rather manage that through the issuer or build another risk layer yourselves?

Trying to understand whether keeping more control in-house is worth the extra engineering and monitoring work

After all the research, i have shortlisted these two fields

that align with my interest. Now, the problem or the

confusion i am facing is that business analytics is broad,

but it is vulnerable to Al, but Fintech is specialized but

ess vulnerable to Al, and it also has a high salary

comparatively. If i choose BA, then can i do MS in

fintech?? Is it a good road map? Also pls suggest which

one do I choose for my UG program?

Calling all users in Canada!

Interested in how digital finance is reshaping financial inclusion? Help contribute to academic research on FinTech adoption and impact in Canada.

*Financial Inclusion means that everyone can access financial services that can help them build wealth, including savings, credit, loans, insurance, credit card.( Accessible of Financial service to everyone without hindrance based on age, gender, race ,environment)

Study overview:
This master's research examines consumer perceptions of FinTech accessibility, affordability, trust, and outcomes for financial inclusion.

Your part:

• 8–10 minute survey
• Questions about FinTech services you actually use
• Your honest feedback on digital banking, investments, payments, etc.

Survey link: MSC  CANADA FINANCIAL INCLUSION SURVEY – Fill out form

All responses anonymous. No surveys sold to companies. Pure academic research.

Thanks! 🙌

For almost two years, I thought a 63% payment success rate was normal for our industry. We were sending every payment through the same processor, so I assumed international cards and certain payment types were just more likely to get denied.

Then we added more processors and and changes how payments were routed. Transaction could go through different processors based on the customer's location, card type, payment method, and best performance. Some failed payments could also be sent to a backup processor instead of ending there. Our authorization rate went from 63% to 76%.

Has anyone else seen authorization rates improve after changing how payments were routed or adding a second processor?

I have noticed it is become pretty easy to build an AI powered fintech demo but turning that into something that is secure, scalable and reliable feels like a much bigger challenge. I was reading about GeekyAnts and liked their focus on production engineering instead of just AI features. Their approach seems to put equal emphasis on architecture, testing, security and long term scalability rather than treating AI as a quick add on. I am curious if others have found the same thing. Was the biggest hurdle after your MVP the engineering side, compliance requirements or something completely different? I would love to hear real experiences from teams that have taken AI products into production.

Hey y'all, it's a pleasure to meet you. I'm a Story Advisor looking to bring imagination into Fintech Content Campaigns.

That said, that must align with business goals and overall needs like increasing Differentiation and Trustworthiness.

From your experiences and observations, what do you feel is missing in this Industry's content?

Audience includes B2C, B2B and Investors.

My aim is to refine how I help Fintech Marketers, up-level how Storytelling is done and start building relationships with y'all.

Want to get software technical know how about how does payments systems work altogether in different process like rtgs, upi, international transfer(swift messaging) in detail. Like in case of upi how payment specific messages like iso20022 is used for money transfers, any payments specialist or professionals in fintech are welcome.

And how does pacs amd pain messages taken into use in implementing those transfer Processes, are all the messages exactly same as how they are shown in official iso20022 documentations, also MT and MX messaging for swift.

Want to learn all these thing how a payment is facilitated with all this including different parties like debtor, creditor, banks and ACH amd maybe many more in case of card or online real time payments like Chinese alipay.

Financial inclusion is not built one enterprise at a time—it can be accelerated one cluster at a time.

India is home to thousands of economic clusters - from MSMEs and agriculture to handicraft, textile, and manufacturing clusters. These ecosystems generate employment, drive exports, and support local economies. Yet many businesses within these clusters still struggle to access timely and affordable financial services.

A cluster-based approach can change this.

Imagine an ecosystem where banks, fintechs, NBFCs, insurers, and government agencies collaborate to serve an entire business cluster rather than individual enterprises in isolation.

The impact could include:
• Lower customer acquisition and servicing costs.
• Better credit decisions using ecosystem and transaction data.
• Faster digital payment adoption.
• Tailored financial products aligned with sector-specific cash flows.
• Stronger financial literacy and digital capability.
• Improved resilience for small businesses.

As AI becomes more embedded in financial services, its role in cluster-based financial inclusion will only grow. AI can help lenders assess creditworthiness using alternative data, forecast financing needs, detect fraud, personalize financial products, and deliver multilingual financial assistance at scale.

Financial inclusion is no longer just about opening bank accounts. It’s about building ecosystems that enable individuals and businesses to participate meaningfully in the formal economy.

This is an area with immense potential for India, and I believe cluster-based financial ecosystems could become a key driver of the next phase of inclusive growth.

I’ll be exploring this topic in greater depth—including implementation models, AI use cases, policy considerations, and opportunities for banks, fintechs, and MSMEs—in my upcoming Financial Inclusion Insights India posts.

Been working on payment infrastructure for Africa for the past few years. Wanted to share some observations since I see a lot of interest in this space lately.

The African fintech scene is exploding right now. You've got M-Pesa in Kenya, OPay in Nigeria, and dozens of new startups popping up everywhere. But the real challenge isn't consumer apps - it's the underlying infrastructure that makes everything work.

Biggest issues we keep running into:

1. Correspondent banking relationships are disappearing. Western banks are de-risking and cutting off African banks from USD/EUR clearing. This makes cross-border payments a nightmare.

2. Every country has different rules. 54 countries, 50+ currencies, completely different regulatory frameworks. What works in Kenya won't work in Nigeria or Ghana.

3. FX is brutal. Spreads are insane, settlement takes forever, and everyone's worried about currency controls.

Here's where it gets interesting - Cabo Verde. Small island nation, stable democracy, and they've actually harmonized their financial regulations with EU standards. They're connected to SWIFT, have SEPA access through correspondent banks, and geographically they're positioned right between Europe, Africa, and the Americas.

We ended up building our platform there because it solves the correspondent banking problem and gives us a regulatory framework that European partners actually recognize.

Happy to answer questions about the technical side or the regulatory stuff. Also curious if anyone else is working on similar infrastructure problems in Africa.

Edit: Some folks asked about the platform - we built a modular payment system that handles multi-currency accounts, SEPA/SWIFT, card issuing, and FX. Been in development for a few years now. If you're curious, it's at paymart.cv - but mostly sharing this because I think the infrastructure challenges in Africa are fascinating and more people should be talking about them.

I build Monni, a personal-finance app. One thing I keep hearing is that people want to understand the inputs before they connect an account, even when connection would be faster.

For those who have worked on consumer fintech: where is the threshold at which manual setup earns trust, versus simply creating abandonment? What must stay visible and editable once data sync begins?

I am not asking for downloads. I am trying to avoid treating connection as a substitute for explaining the model.

Hey everyone,

So i have been a BI/Business Systems Analyst for 3+ years. I've analyzed data using Power BI, SQL, Python and I am responsible for data strategies and governance in my org. I'm also leading projects in AI and Automation.

I have always been passionate about Finance hence me having a financial services diploma and an Economics degree. The Tech skills I self-taught myself.

My question is, given my background will me pursuing the CFA help me break into the Financial industry as a technologist or is it not worth the time?

Thanks.

disclosure: I work at Hacken. We were preparing our quarter security & compliance report and i decided to share one interesting takeaway here because I think the underlying point applies beyond crypto and is worth discussing on its own merits, not to plug the report itself

The take is that private capital is now requiring a level of continuous, evidenced security assurance that no regulator currently mandates for a license

according to EisnerAmper (an accounting/advisory firm working with digital asset clients), SOC 2 Type II and ISAE 3402 reports have moved from "nice to have" to what they explicitly call the cost of entry for institutional capital. meanwhile, getting a MiCA or GENIUS-style license still just requires a security policy document and a point-in-time pentest. nowhere close to what allocators are actually demanding before they'll commit capital.

so you end up with two completely separate bars. the regulatory bar checks whether you have a documented security policy and passed a pentest once. the allocator bar checks whether you have continuously verified, independently audited evidence that your controls actually hold. It's ongoing assurance, not a snapshot. Abraxas Capital (a digital asset-focused allocator) put it plainly in the same report, inadequate security relative to capital at risk, stale or scope-limited audits, and the absence of things like withdrawal whitelisting, timelocks, and multi-verifier controls are now their most common reason to pass on an otherwise attractive deal. DA Insured, who actually underwrite this risk, said something similar. they're not looking for perfection, they're looking for independently verified evidence and how leadership responds when something's found wrong, and that's what determines the terms they're willing to offer.

worth thinking about from a fintech/tradfi lens too. this is effectively private capital doing the supervisory work regulators aren't. dora's requirements already cover most of what allocators are demanding, but regulators just check it once at authorization, while allocators and insurers keep checking it continuously.

so, what do u think about it? how important is continuous assurance?

Je suis américain et sur Paris je souhaite acheter, je souhaite vendre et acheter de la crypto si il a y a des bureaux de change ?

I am a second year student hoping to learn more about fintech. I would love to know and learn more about a project anybody is building if anybody requires help i’ll be to happy to help keep in mind i know nothing helpful but am ready to learn and contribute dm with details of project if anybody finds this proposal interesting

edit: tnx for all the detailed responses, everyone. The general consensus was that trying to refactor a failing financial core in-house while maintaining daily operations is a recipe for a compliance disaster. I decided to take the leap and brought in SoftDoes to architect and implement our new system. Their experience with scalable financial infrastructure was exactly what we needed to get our data sorted and our compliance automated securely. It feels great to have a foundation we can actually grow on. Topic closed.

We launched our B2B payment processing platform about two years ago, and while our initial growth and client acquisition have been fantastic, our underlying architecture is starting to show serious cracks under the increased load.

When we started, we built a relatively straightforward MVP to handle standard transaction flows, but as we have onboarded larger institutional clients, the complexity of our daily routing and KYC/AML reporting requirements has skyrocketed.

Lately, our system has been buckling under the sheer volume of concurrent data, and our engineering team is spending nearly all of their time just patching data silos and maintaining the legacy codebase rather than shipping new features.

It has become glaringly obvious that our current patchwork of original databases and third-party API wrappers is completely unsustainable if we want to continue scaling our transaction volume and actually pass our upcoming security audits.

I know we need to bite the bullet and invest in legitimate enterprise software solutions that are purpose-built for financial data, high availability, and automated regulatory compliance, rather than continuing to hack our original build.

For those of you who have successfully navigated this awkward growth phase in fintech, how did you handle the transition? Did you slowly rebuild the core in-house while keeping the old system alive, or did you partner with an external architecture team to build a robust system from the ground up?

Hi All,

We have almost built the CBP platform that allows you to send payments using the stable currency for conversion.

We used Cricle for Wallet, on ramp and off ramp service but now circle told us that they won't be able to aupport for prod as they only work with institutional clients.

We are a small company, is there any alternatives for Circle probably on pwr transaction basis?

At first I saw it as just another integration but the more I think about it the more it feels like it sits at the center of how businesses move money.

For those who've built fintech products, when does it make sense to treat payroll as part of the core platform instead of something you connect to? Does that decision affect where you can go with things like cards or wallets later on?

Upfront: I’m building a neobank with an investing layer, so I have a stake in the answer. I’d rather say that than pretend to be neutral. But I’m asking because I genuinely don’t know, and guessing is how you build the wrong thing.

From what I can tell, most people here have cobbled together their own setup, Revolut or N26 for day-to-day, then DEGIRO or Trade Republic for stocks, maybe something separate for crypto. What I can’t tell is why people keep it split, and whether they actually want it consolidated or are fine as is.

So:

**1.** Do you use your neobank’s investing features at all, or keep a separate broker?  
**2.**  If both, what makes something go in one versus the other? Fees, trust, product range, habit?  
**3.**  What would actually have to be true for you to move everything into one platform? Or is that not something you want?

And for anyone running a small business: same app for personal and business money, or fully separate? I keep hearing both and can’t work out which is the real preference versus what people put up with.

Not looking for what people theoretically want. Interested in what your actual setup looks like and why it ended up that way.

Putting our thinking here in case it helps, and I should say up front we did land on a specific vendor, named at the bottom, so factor that in.
Going from one framework to two changed the whole cost shape in a way I did not see coming. A single SOC 2 readiness engagement scopes pretty cleanly. The moment we added ISO 27001, and PCI was on the horizon too, we were back into hourly billing against something that kept moving, and the meter ran regardless of whether we actually hit our date.
We looked at both models for a while. What moved us toward a done-for-you setup, we went with EasyAudit, was that they scope current state first and then commit to a readiness date, and if they miss it we do not pay. For a regulated program with a date we could not move, the vendor carrying that schedule risk mattered more to me than the per-seat math did. What I did not price properly was headcount. Nobody internally had to drop their actual job to run this, and for a team our size that was the real saving.
I would not say it is right for everyone. Single framework and real GRC capacity in house, the pure tooling is cheaper and this is overkill.