BFSI
Lending & Credit Risk
A loan book's real risk profile lives at the branch, vintage, and channel level — not in the portfolio-wide NPA number that shows up in the monthly credit committee deck. By the time aggregate NPA moves, the specific cohort driving it has usually been deteriorating for weeks.
FireAI connects your LOS, LMS, core banking, and bureau data into a live risk intelligence layer. Credit risk teams see DPD bucket movement in real time, underwriting teams see exactly where sanction turnaround stalls, and the entire risk function can query portfolio quality in plain language instead of waiting for the next scheduled report.
Loan Book Quality & NPA Early-Warning
NPA is a lagging indicator by design — an account is only classified non-performing after 90 days past due. By then, three months of recovery opportunity is already gone. Most risk teams find out a segment is deteriorating from the same monthly report that tells everyone else.
FireAI ingests LOS/LMS disbursement and repayment data alongside bureau refresh feeds to surface DPD-30 and DPD-60 bucket movement in real time, broken down by branch, product, vintage, and origination channel — so the credit team sees a cohort turning before it becomes an NPA number.
Portfolio Quality Dashboard
Credit Underwriting Turnaround Time by Segment
A slow underwriting cycle isn't just an operating cost — it's a conversion leak. Applicants who wait too long for a sanction decision go to a competitor or drop off entirely, and the segments where this happens most are rarely the ones underwriting teams are watching.
FireAI connects LOS stage-level timestamps to show exactly where an application stalls — credit check, document verification, or approval queue — by product and branch, so underwriting bottlenecks get fixed before they show up as a conversion problem.
Ask FireAI about Underwriting TAT
See how your team can ask questions in plain language and get instant analytics answers.
Portfolio-at-Risk (PAR) by Product & Geography
PAR30 and PAR90 tell a very different story depending on which product and state you slice by, but most PAR reporting stops at the portfolio-wide number because the underlying data lives across separate product ledgers.
FireAI unifies PAR calculation across every product line and geography, refreshed daily, so risk committees can see exactly which combination is driving portfolio stress instead of debating whether it's a product issue or a regional one.
Disbursement vs Sanction Leakage Analysis
Not every sanctioned loan gets disbursed, and the gap between the two numbers is rarely investigated — it's treated as a normal drop-off rate rather than a signal. Some of that leakage is customer choice; some is an operational failure in the disbursement workflow.
FireAI tracks sanction-to-disbursement conversion by branch and channel, flagging where the drop-off rate is abnormal against the portfolio baseline, so operational leakage gets separated from genuine customer drop-off.