u/Dizzy-Mine-5760

do we simply focus on % values?

Looking for recommendations on good notetaking ai tool.

i have been working with my brother who is a merchant and have helped him with small automations. he has been able to reduce costs of 1 teammember with these automations. I think there is scope to grow my services outside of family. How do i get first few paying customers?

i am looking for a card for zero forex markup. scapia feed back is ok. how is uni?

Hi everyone, I keep seeing few features here and there of Linkedin. I want to know if i can get a custom CTA on my profile under premium and if yes, what plan is it called? the plan it shows are so vague and talk quality over actual quantity. i am very confused.

I have worked for more than 12 years in the Indian fintech space and have been twice on the decision-making side when it came to picking a LOS system for my NBFC. I’m also seeing a fresh wave of NBFCs being set up across the country, so thought I’d share a few practical learnings.

When we first evaluated LOS platforms, we made the mistake most people do - comparing feature lists. In reality, most mature systems today offer similar “checkbox” capabilities (workflows, bureau integrations, rule engines, etc.). The real differences only show up post-implementation.

Here’s how I’d break down some of the commonly discussed LOS options in India:

1. Enterprise-heavy systems - Nucleus Software

• Strengths: Very robust, proven at scale, strong compliance alignment
• Weaknesses: Long implementation cycles, expensive, less flexibility once deployed
• Best for: Large NBFCs / banks with stable products and in-house tech teams

2. Configurable mid-market platforms - Finezza.in

• Strengths: Balance between configurability and structure, faster go-live vs enterprise systems
• Weaknesses: Still require vendor dependency for deeper changes, UI/UX can vary
• Best for: Growing NBFCs trying to digitize without building from scratch

3. API-first / newer-age platforms - TurnKey Lender, FinStack

• Strengths: Faster integration, modular approach, better suited for digital journeys
• Weaknesses: May need stitching together multiple components, maturity varies
• Best for: Fintech-first lenders with strong tech teams

What actually mattered more than the vendor (in hindsight):

• Configurability > Features Every lender thinks their process is unique — and they’re usually right. If your LOS can’t adapt quickly, you’ll feel stuck within months.
• Turnaround time on changes The real test is: how fast can you change a rule, journey, or product after go-live?
• Integration ecosystem Bureau, bank statement analysis, KYC, eSign; your LOS is only as good as how easily it plugs into these.
• Data ownership & reporting Extracting clean, usable data is often harder than expected. This becomes critical for credit models later.
• Implementation partner quality Honestly, this mattered as much as the product itself.

Two biggest mistake we made:

1. Optimizing for “current requirements” instead of how fast we’d need to evolve in 12–18 months.

2. Continued launching products after products with the same LOS instead of switching when we realized that our current LOS is not able to adapt as fast as we were.

One thing I always wondered - what if we had built in in-house? Do people regret after going in this direction or is it a better route than outsourcing the loan procession bit?

hi folks, i have often heard about context engineering. does that work only with the particular user or works in training the llm and entering a brand in its knowledge base?

hello, how do you track refunds and how often?

where can i migrate to?

one of the very interesting things happened recently, my blog got cited in chatgpt but my brand was not recommended. instead my comparison blog was used to recommend brands in a structured way! how do you go from here?

what is the one feature you have not found in the existing aeo products out there?

I have received more than 10 different emails which are more or less the same construct (written by AI) and i have not responded to any. One of them was actually useful but I eventually went through the website first and then put in my details there itself.

1. What kind of conversion are you seeing on lInkedin?

2. Do you calculate attribution to Linkedin outreach?

I have been using chatgpt for a lot of deep research. It does tremendous work of actually going deep into a topic instead of giving a tl;dr version but often the sources are dated. any prompt recommendations to solve it?

I am a wealth manager and i see this as a pattern in my clients bank statements. they all have a few transactions between their own accounts. I eventually catch it but it is not easy. I dont want to upload them to any AI since it contains personal data like address, account number. What tool would you recommend for this?

I am a wealth manager and i see this as a pattern in my clients bank statements. they all have a few transactions between their own accounts. I eventually catch it but it is not easy. I dont want to upload them to any AI since it contains personal data like address, account number. What tool would you recommend for this?