AI may not have saved her, but it would have helped

She was a single mother in Sydney. Working two jobs, paying what she could, when she could. 

On paper, she looked like every other 60-plus DPD account, but she wasn’t. Her missed payments weren’t about avoidance; they were about survival. 

She didn’t need five reminder calls. What she needed was a sustainable plan. Early, before the spiral began. 

The lender had data. Plenty of it, including transaction histories, contact logs, partial payments, product relationships, digital activity, behavioural flags and internal hardship notes. Enough to paint a complete picture, if anyone had been looking. 

But it was all fragmented. 

Collections saw arrears, risk saw scores, customer service saw complaints. The problem was no one had the tools or the mandate to join it together. 

There was no decisioning engine to flag her change in behaviour, no signal when regular payments shifted to staggered partials. There was no escalation when contact fatigue increased or hardship triggers repeated. 

No treatment pathways that flexed when a customer fell into multiple vulnerable segments. 

Instead, she got routed into the standard arrears sequence. Same contact cadence. Same messaging, same “please call us” script. 

A smart system would have spotted the pattern weeks earlier and seen low engagement across channels and widening gaps between payments. All clear signs of strain. 

But without a unified engine, everything stayed siloed. And by the time someone manually escalated the case, the damage was already done, to her and to the account. 

This isn’t an AI problem; it's an execution problem. 

AI isn’t a strategy. It doesn’t fix broken processes. But it can expose how many of your current treatments are built on blunt assumptions. 

Segmenting customers by DPD band is no longer good enough. Neither is relying on a treatment path written five years ago (pre covid) by a team that has since moved on. 

Modern solutions, like the one built by C&R Software, don’t begin with product features. They begin with hard operational questions. 

• Where are you wasting effort? 

• Who shouldn’t be getting a call? 

• Which strategies are quietly failing? 

• Where is your team firefighting because the system can’t adapt? 

• How many manual work arounds do you have? How many do you have that you don’t even know about? 

If you don’t have answers, you don’t have a decisioning engine. You have a default engine. 

Not every AI tool belongs in a bank. 

There’s a new AI app every week. Some of them are genuinely impressive, others are built in someone’s garage using another AI to write the code. You can generate a cat mowing the lawn video in six seconds. You can plan your UK holiday in four clicks. 

But that’s not collections. And it’s not banking. 

In this industry, hallucinations aren’t harmless. Bad recommendations lead to broken trust, and missteps hit vulnerable customers. Misfires trigger breaches. 

This isn’t a playground, it’s a regulated environment where risk, conduct, and control still matter. This doesn't mean we wait for AI to become perfect, it means we need an orchestrator. A system that connects, governs, and executes, not one that guesses. 

C&R Software isn’t competing with every shiny new point solution. It is not chasing novelty for the sake of it. Its strength lies in stitching real-time collection intelligence across systems, safeguards, and strategies. 

It doesn’t need to be flashy. It needs to be right, repeatable and safe. This is what scales and what works.  

Stop waiting for clean data and the perfect business case. 

There is no clean data. There is no perfect case study. There’s only risk in waiting. 

The longer you wait to embed AI into everyday collections decisions, the harder it becomes to recover. While you’re still building your next quarterly strategy, your competitors have already tested three variations of theirs in real time. 

C&R’s platform design allows teams to test fast, learn faster, and pivot without needing to rip out the entire stack. They do not require transformation before progress. They just need a commitment to move. 

This is your wake-up call. 

AI in collections isn’t about the future. It’s about the gap between those who are acting and those who are still preparing. 

The lenders who are acting don’t talk about AI anymore. They talk about the cost to collect, agent headcount, and resolution times. And they already have the data to back it up. 

If your collections strategy doesn’t include real-time decisioning, dynamic segmentation, and strategy optimisation built for actual execution, you’re not preparing for disruption. 

You’re already in it and you’re unarmed. 

Asia-Pacific doesn’t need imported hype. It needs partners who understand complexity, regulation, and scale. It needs people who aren’t afraid to challenge outdated ways of working. 

C&R Software isn’t here to take over your tech stack. They ‘re here to make it smarter, because the next customer like her deserves better.