The Indian market now has a dozen vendors selling something called a debt collection platform, and their demos look surprisingly similar. Dashboards, WhatsApp integration, a field app, the word "AI" somewhere on every slide. The differences that matter show up three months after go-live, which is a bad time to discover them.

These are the seven questions we'd ask any vendor, including us.

1. Does it predict, or only record?

Most collections software is a system of record: it tells you what happened. A platform worth paying for tells you what's about to happen. Ask the vendor to show you a default probability score on a live account and explain what data feeds it. If the honest answer is "DPD status and not much else," you're looking at a workflow tool, not intelligence. The pre-due and SMA-0 window is where recovery probability is highest and intervention is cheapest; software that can't see into that window has already conceded the most valuable ground.

2. Who decides where each account goes?

In a genuine platform, routing is automatic. Risk tier, ticket size, channel response history and timing all feed a decision about whether this account gets a WhatsApp nudge, an agent call or a field visit. In weaker products, a collections manager still allocates accounts manually from a queue, which means the software has digitised the spreadsheet without removing the bottleneck. Ask to see the routing rules and, more importantly, ask what happens when the manager is on leave.

3. Is RBI compliance enforced by the system or by training?

The RBI's August 2022 circular on recovery agents, the Digital Lending Directions and the February 2026 draft directions on loan recovery all point the same way: the lender is accountable for every borrower interaction, including outsourced ones, and needs the records to prove conduct was clean. A platform should make violations mechanically difficult - calls outside permitted hours blocked, escalation sequences enforced, every touch logged.

If compliance depends on agents remembering their training, the platform hasn't reduced your regulatory exposure at all.

4. How long is integration, honestly?

Get the vendor to commit to a timeline against your actual LMS, not a generic estimate. On FrenzoFinserv the typical range is 2–4 weeks for the integration itself and 4–6 weeks to full go-live, and the main variable is the API maturity of the lender's existing stack. Anything quoted in quarters rather than weeks means you'll be carrying PAR exposure while the project drags - overdue accounts age into deeper buckets whether or not your IT project is on schedule.

5. Does the reporting run in real time?

Batch-updated dashboards are fine for board decks and useless for operations. Roll-forward prevention only works if you can see an account slipping today. Ask whether PAR 1, PAR 30 and PAR 90 update live, whether you can drill down by product, vintage and geography, and whether the system alerts you before an account rolls rather than reporting it after.

6. What happens to the models over time?

A static model decays. Borrower behaviour shifts, products change, and last year's scoring logic quietly gets worse. Ask who retrains the models, how often, and on what data. On a CaaS arrangement the vendor maintains and improves the models as part of the subscription; if you're expected to staff that yourself, price the ML engineers into your comparison.

7. What does it cost, all in?

Compare the subscription not against zero but against your current cost of collections: agency commissions, agent salaries, field visit costs, and the write-offs from accounts that rolled to NPA because nobody reached them in time. A build-it-yourself alternative typically runs ₹50 lakh to ₹2 crore up front, takes 6–12 months, and pays back in 18–24 months if it works. A subscription platform starts returning improved recovery from roughly week five. Run both numbers on your own portfolio before deciding.

Where FrenzoFinserv sits

FrenzoFinserv is built as an answer to all seven questions: predictive scoring on every account, automated routing across six channels, RBI guardrails enforced at the infrastructure level, 4–6 week deployment against your existing LMS, real-time PAR analytics, and models we maintain ourselves. Lenders on the platform average around 35% higher recovery rates and roughly 30% lower collections cost.

The honest caveat: no platform fixes a broken product or reckless underwriting. What it fixes is the gap between the recovery your portfolio could produce and the recovery your current tooling lets you reach. If you'd like to see the gap quantified on your own DPD data, talk to our team - the first conversation is a portfolio walkthrough, not a sales pitch.