Turnaround time — the days from application receipt to funds in the borrower's account — is the single metric that determines whether the institution's credit process is a competitive advantage or a competitive liability. A borrower who applied for a home loan at two institutions simultaneously will disburse from whichever one reaches them first. An MSME borrower who needed working capital on Monday and disburses on Friday instead of Wednesday has had two days of business interrupted. TAT is not a process metric — it is a customer experience metric, a competitive positioning metric, and a collections risk metric, because borrowers who wait longer have more time to reconsider. The MIS & Reporting Agent AI tracks TAT at step level and branch level for every application, identifies where each branch's time is being lost, and produces a weekly TAT analysis that allows the Head of Ops to direct improvement efforts at the specific steps and branches where they will have the most impact.
Why total TAT is the wrong measurement unit — and what step-level TAT reveals
An institution that measures "average origination-to-disbursement TAT" and finds it is 8.2 days knows it is above the 7-day target. What it does not know is whether the 1.2-day excess is concentrated in the credit assessment step, the valuation step, the QC step, or the post-sanction documentation step — or whether it is distributed evenly across all steps. These are four different operational problems requiring four different interventions. A credit assessment bottleneck requires analyst reallocation or credit process acceleration. A valuation bottleneck requires panel expansion or reassignment. A QC bottleneck requires error reduction at origination (feeding into the QC feedback loop). A post-sanction documentation bottleneck requires ops process redesign.
The MIS & Reporting Agent AI tracks TAT at the step level for every application in every branch — maintaining a real-time clock on every step, updated from the LOS and CBS each morning. The weekly TAT report shows not just each branch's total average TAT but their step-wise contribution to that average, making the operational intervention obvious rather than investigative.
The weekly TAT analysis: all branches · Week ending November 14, 2025
The step-level TAT analysis: what each excess day costs and where the fix lies
| Step exceeding target | Avg excess time | Primary cause | Branches most affected | Intervention |
|---|---|---|---|---|
| QC review → credit assessment | +0.8 days | Credit analyst queue — 2 analysts on leave simultaneously; Hubli credit team carrying full institution volume | Hubli (2.1d average) · Bellary exacerbated by QC holds | Temporary analyst reallocation · Bellary QC hold reduction reduces volume entering credit queue |
| Legal review | +0.6 days | Hospet: complex ancestral property title chains · Legal team handling 2 contentious EC disputes simultaneously | Hospet (10.8d total) · Institution average marginally affected | Hospet: external legal counsel for EC disputes to free legal team capacity · Title chain complexity: additional legal resource |
| Property valuation | At target — 3.2d vs 3.0d · Raichur outlier | Raichur: 6 properties with single overloaded valuer · Girish (panel valuer) unreachable Nov 12–14 | Raichur specifically · Institution average within 0.2d of target | Raichur: reassign to adjacent panel valuer (implemented Nov 13) · Panel expansion for Raichur geography |
The Bengaluru HO's 5.8-day TAT is not luck — it is the result of each step performing at or near its target simultaneously. The step-level comparison shows every other branch exactly where its time is going.
When the Head of Ops reads the TAT report and sees that Hubli's credit assessment step averages 2.1 days against the 1-day target, they know the intervention is a staffing question, not a quality question. When they see that Hospet's legal review step averages 4.2 days against the 2-day target, they know it is a complexity question — the title chains in Hospet's geography are more complicated than the legal team's capacity was designed for. The step-level data converts a TAT problem — "Hospet is slow" — into an operational problem — "Hospet's legal review step needs additional capacity for complex title chains" — which is a problem with a specific, fixable solution. A head of operations who works from total TAT data generates generic exhortations to "move faster." One who works from step-level data generates specific operational interventions. The MIS & Reporting Agent AI produces the second kind of analysis, automatically, every week, for all 50 branches, without an analyst spending 3 hours in Excel.