The behavioural intelligence layer for SME lending
Undercurrent transforms raw bank transactions into explainable behavioural intelligence for better underwriting, portfolio management and relationship decisions. Go beyond categorisation and generic feature engineering to understand how businesses behave, adapt and evolve.
The problem
Millions of transactions are reduced to balances, turnover, averages and a handful of engineered features. Yet experienced underwriters can often recognise important patterns in the same statements because they interpret behaviour—not just numbers. Today’s models rarely capture that knowledge consistently.
Cafe · POS driven
Money should arrive frequently. Broken settlement rhythm can be meaningful.
Ecommerce · Gateway paid
The signal must recognise gateway cycles before calling normal behaviour risky.
Tradie · Invoice driven
The real behaviour may be debtor timing, recovery and supplier-payment hierarchy.
The missing layer
We build the adaptive behavioural intelligence layer between bank transactions and every lending decision. It gives models, analysts and underwriters a shared representation of how a business actually operates.
Adaptive representation
Recurring payroll should not be analysed like seasonal revenue. Inventory purchasing should not be represented like customer receipts. Liquidity may require a different window from revenue stability. Undercurrent determines how each behavioural concept should be represented using available history, transaction density, business type, seasonality, lending context, prediction horizon and the pattern itself.
Start from the credit or portfolio question and the business concept that could explain it.
Test windows, rhythms, events, interactions and latent views appropriate to the signal.
Measure incremental contribution, stability, coverage, robustness and point-in-time integrity.
Deploy transparent metrics with lineage and retain the evidence for future decisions.
Most candidates fail. That is the evidence gate working.
The Business Behaviour Profile
Undercurrent represents each business through transparent behavioural concepts. Every concept is supported by traceable metrics derived directly from transaction history—not a black-box score.
Can this business generate enough cash to service debt?
How predictable and resilient are its operations?
Does it consistently demonstrate responsible payment behaviour?
Can it absorb an unexpected shock?
Is growth sustainable, cash-generative or fragile?
How effectively does the business manage its financial obligations?
Underwriters and strategy teams receive explainable behavioural evidence instead of manually interpreting hundreds of transactions.
Validated behavioural metrics arrive with lineage, temporal context, coverage and explainability as a reusable representation layer.
Commercial value
Signals are measured once and validated wherever they earn a role. This creates a consistent behavioural vocabulary across the customer lifecycle instead of rebuilding disconnected features for every model.
Give strategy analysts rapid, repeatable feedback for monitoring the book, testing approval and pricing thresholds, and responding to emerging conditions. This matters between model rebuilds: the signals that reveal a macroeconomic shift can change quickly—and can look very different across business models.
Target businesses more likely to become profitable, performing customers.
Approve more creditworthy SMEs without proportionally increasing loss.
Match economics more closely to observed risk and resilience.
Test score cut-offs and policy thresholds quickly, without waiting for a full model rebuild.
Recognise business-model-specific changes in resilience before arrears become the first signal.
Prioritise accounts and choose treatment using current behavioural evidence.
Recognise improving borrowers, protect good customers and manage declining ones.
Commercial value appears through additional performing-loan revenue, more accurate pricing, stronger renewal value, avoided credit losses and faster, lower-cost portfolio decisions.
Design-partner pilot
Start with one decision and one agreed outcome. Undercurrent works with your existing data and models, validates incremental contribution against pre-agreed thresholds and leaves you with the evidence either way.
Built by Parisa Milne, PhD, drawing on more than fifteen years of applied data science across healthcare, retail, technology and SME lending—and a career spent finding trustworthy signal in noisy real-world systems.