AI for Collections Intelligence Management in BFSI

AI for Collections Intelligence

How a leading private sector bank replaced blanket collections campaigns with AI driven next best-action and improved recovery rates by 8-15% on targeted segments.

01 PROBLEM STATEMENT

Chasing Every Borrower the Same Way is Losing Money

A leading private sector bank with a growing retail loan portfolio was running collections the same way for every overdue account: bulk SMS blasts, uniform IVR calls, and agent outreach with no prioritisation. High intent payers were being over contacted and switching banks. Low-intent accounts were being under-engaged and sliding into NPA. The collections team had no visibility into which accounts to call first, which channel worked best for each borrower, or what message drove repayment. Recovery rates were stagnating and NPA provisioning requirements were rising.

02 current challenges

Key Operational Challenges Bank was Facing

Blanket

Outreach strategy

Every overdue account
received the same call,
message, and timing
regardless of repayment
probability.

No Score

Account prioritisation

Collections agents had no data
on which accounts were most
likely to pay, leading to wasted
effort on low-intent cases.

Rising

NPA provisioning

Without early intervention on
the right accounts, more loans
crossed the 90-day threshold
and required higher
provisioning.

Unmeasured

Campaign ROI

No way to measure which
channel, message, or timing
variant drove actual
repayments across cohorts.

03 SOLUTION OVERVIEW

STAR’s Approach – AINE Collections Intelligence

STAR Systems deployed AINE Collections Intelligence on-premises within the bank’s infrastructure. The platform scores every overdue account daily by probability to pay, recommends the next-best action for each borrower which channel, which message, which timing and triggers outreach automatically via WhatsApp, IVR, or agent queue. Collections managers review AI recommendations daily and approve outreach triggers above DPD-90. STAR provides a weekly campaign performance dashboard.

AI PATTERN

Predictive Scoring + Next Best Action +
Omnichannel Outreach

04 WORKFLOW PROCESS

Step-By-Step: How the Collections Intelligence Agent Works

Step 1 – Delinquency Data Feed: CBS delinquency data ingested daily via batch or real-time CDC. Every overdue account scored.

Step 2 – Propensity Scoring: AI model scores each account by probability to pay, segment, DPD bucket, and past behaviour.

Step 3 – Next-Best Action: Platform recommends optimal channel (WhatsApp, IVR, agent), message variant, and contact timing per account.

Step 4 – Manager Approval: Collections manager reviews daily AI recommendations. Triggers above DPD-90 require explicit approval.

Step 5 – Omnichannel Outreach: Approved outreach triggered automatically via WhatsApp Business API, IVR auto-dialler, or CRM agent queue.

Step 6 – Track and Optimise: Repayment outcomes tracked per cohort, channel, and message. Weekly dashboard shared with collections manager.

05 KEY FEATURES

What the Platform Does

Propensity to Pay Scoring:

Every overdue account scored daily on probability to pay based on DPD bucket, product type, payment history, and behavioural signals from the CBS feed.

Next Best Action Engine:

Recommends the right channel, message variant, and contact time for each borrower. No more blanket campaigns – every outreach is individually optimised.

Omnichannel Outreach Triggers:

Approved actions trigger automatically via WhatsApp Business API (Twilio or direct BSP), IVR auto-dialler, or agent queue in Salesforce or Leadsquared.

Manager in the Loop Controls:

Collections managers review AI recommendations daily. Outreach above DPD-90 requires explicit approval, keeping human judgement in high-stakes decisions.

Direct Pay Link in Outreach:

Payment gateway integrated into WhatsApp and SMS messages. Borrowers can pay directly from the message – reducing friction between intent and action.

Campaign Performance Dashboard:

Weekly dashboard from STAR tracks recovery rates, contact rates, and campaign ROI per cohort, channel, and message variant. Fully measurable.

06 BUSINESS OUTCOMES

What Changes After Go Live

8-15%

Recovery rate improvement

High-Value

Collections team focus

Measurable

Campaign ROI per cohort

Reduced

NPA provisioning requirements

CFO

Recovery rate improvement of 8-15% on targeted segments.
Cost per rupee collected reduced through right-channel, right-time outreach

CEO

NPA provisioning requirements potentially reduced.
Regulatory relationship improved through documented, non-discriminatory outreach.

Operations Head

Collections team focuses on high-value accounts and exceptions only.
Campaign ROI measurable per cohort, channel, and message variant.

Risk / Compliance

Every outreach decision logged and auditable.
Non Discriminatory contact policies enforced by the AI model, not individual agent judgment.

07 REAL-WORLD SCENARIO

A Day in the Life Before and After

Before	After
Collections team sends bulk SMS to all DPD-30 accounts at 10 AM. High-intent payers feel harassed. Low-intent accounts ignore the message.	AI scores each DPD-30 account overnight. High-propensity accounts get a WhatsApp with a direct-pay link. Low-propensity accounts get a softer IVR nudge.
Agent team calls 400 accounts per day with no prioritisation. Half the list has already paid or has no intent to pay this week.	Agent queue shows only the 80 accounts where agent contact is the recommended action. Recovery per agent-hour increases significantly.
Account crosses DPD-90 because the right message was never sent at the right time. Bank raises NPA provisioning for the account.	Early intervention with right-channel outreach at DPD-30 and DPD-60 keeps more accounts from crossing the 90-day threshold.
Monthly review asks which campaign worked best. No data available all cohorts received the same treatment.	Weekly dashboard shows recovery rate, contact rate, and ROI by channel and message variant. Next campaign optimised from real data.

08 ROI AND VALUE JUSTIFICATION

Why this Numbers Work

Value Driver	Indicative Impact	How It Is Realised
Recovery rate improvement	8-15% uplift on targeted segments	Right channel and message at right time converts more borderline payers before DPD-90.
Cost per rupee collected	Reduced through channel optimisation	WhatsApp and IVR outreach costs a fraction of agent calls; model routes agent effort to only high-value accounts.
NPA provisioning	Potentially reduced	Early AI-driven intervention keeps more accounts below the 90-day threshold, lowering provisioning obligations.
Positive ROI timeline	Within 6 months of go-live	Recovery uplift on even a small loan book segment exceeds platform and managed service costs within one quarter.

09 NEXT STEPS

Discovery Call

Call 30-min call to map your collections workflow, CBS setup, and DPD distribution.

Pilot Scoping

We identify 2-3 DPD cohorts from your book for a 4-week pilot campaign.

Pilot Delivery

AI scoring and outreach run on your data before any commercial commitment.

Business Case

Recovery uplift, cost savings, and ROI measured from actual pilot results.

Schedule a Free Consultation

AI for Collections intelligence management

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