Meet Polli. The AI Policy Coach built for lenders.
For the first time, see how your policy performs across the industry in real time: where it wins deal volume, where it leaks it, and what to change.
Polli works alongside your policy, product and credit teams, inside Cynario Insights Pro.
An example conversation. Polli works from aggregate, de-identified data and never names or quotes another lender.
Self-employed scenarios were 14% of the market last quarter. Your policy was a clear yes (High Fit) for 29% of them. The typical lender managed 31%, the best quarter of lenders 52%. Most of the gap is the two-year ABN rule, and wording that brokers read as stricter than it is.
| Self-employed, ABN under 2 years | You | Typical lender | Best quarter |
|---|---|---|---|
| Clear yes (High Fit) | 29% | 31% | 52% |
Recommendation. Publish the 12-month ABN exception in the broker guide. Matching the best quarter of lenders is worth up to $1.37bn of scenarios a quarter across the market.
What brokers brought to lenders last quarter
Every scenario a broker researches on Cynario is checked against every lender's policy, and each lender gets a rating. High Fit is a clear yes, Moderate Fit a yes with conditions or wording open to interpretation, and Edge Fit only at the edge of policy.
of home loan scenarios brokers researched on Cynario in Q3, if each were a $1.2m loan.
of them met the typical lender's policy at Moderate or Edge Fit: deals at risk of going elsewhere.
of scenarios a quarter, if 2% more of them met your policy at High Fit.
Q3 2026. Aggregate and de-identified. The value of scenarios researched, not settled, committed or pipeline lending.
Built for the business case.
Every AI decision in lending comes down to three questions. Polli answers all three.
Grow deal volume
Polli prices every policy gap against the market, so you know which change wins the most scenarios and market share, before you make it.
Cut cost
Clearer policy means cleaner submissions. Credit Assessors spend less time on rework, SLAs come down, and the same team assesses more.
Put AI in every role
Credit, policy and BDM teams ask Polli in plain English. No implementation, no new system to learn, no data leaves your hands.
Your policy, read against the market every day.
Polli continually analyses your criteria against prevailing market sentiment, conditions and trends. Built into Cynario Insights Pro, it pairs a full analytics dashboard with a live chat your credit and policy teams can talk to directly.
- Policy optimisation strategies and recommendations
- The deal volume impact of ambiguous policy
- Policy gaps worth exploring
- Market opportunities and competitive visibility
| Category | Share | Typical | Best quarter | Volume a quarter |
|---|---|---|---|---|
| Self-employed, ABN under 2 years | 14.2% | 31% | 52% | $1.37bn |
| Temporary visa, non-resident | 6.1% | 18% | 44% | $731m |
| Debt consolidation | 11.8% | 47% | 58% | $598m |
| Construction | 5.2% | 35% | 49% | $336m |
How often each category gets a clear yes (High Fit) from the typical lender, and from the best quarter of lenders. Volume a quarter is what the typical lender would add by matching the best quarter, at a $1.2m loan.
Watch the market move, in your own dashboard.
Polli sits on top of the Cynario Insights dashboard: what the broker channel is asking, how often your policy is the answer, and how that moves week to week. Every figure is aggregate and de-identified, and refreshes as brokers work. The market moves every week, and so do the lenders watching it.
- Broker activity and scenario volume, week by week
- Where the market is asking, and which topics are rising
- Your visibility and policy performance against the market
- The policy lines that decided the outcome
| Topic | Share of scenarios | Move on Q2 |
|---|---|---|
| First home buyer | 18.4% | +0.6 |
| Self-employed | 14.2% | +1.1 |
| Debt consolidation | 11.8% | -0.9 |
| Investment | 10.9% | +0.3 |
| Construction | 5.2% | +2.1 |
Illustrative of the dashboard. Shares of all broker scenarios on Cynario; no counts, no lender named.
What clearer policy is worth to you.
Your numbers, not ours. The figures below are an example until you move the sliders to match your teams.
Credit assessment
Cleaner submissions, less rework.
- Saved a year, team
- $473,684 $39,474 an assessor
- Added capacity, each
- +861 deals 65% more, $947.0m of lending
BDM productivity
The busy BDM, made productive.
- Workshopping recovered, team
- $164,211 2,112 hours a year
- Volume lost to slow answers
- $193.6m 1 in 20 lost, a year
Deal volume
Small, steady moves that compound.
Clearer wording turns partial fits into a clear yes.
Scenarios you are not considered for today.
Segments your policy does not reach yet.
- Added deal volume a year
- $200.0m a 4.0% lift on $5.0bn
Example figures. 220 working days of 7.6 hours (1,672 hours) and 44 working weeks a year. Estimates to frame your business case, not a forecast or a promise of results.
We built Polli to help lenders move from reacting to the market to proactively leading it.
See how your policy performs.
Thirty minutes, your policy, live in Polli. See what the market already sees in it.