Models, Business Rule Engines and the end-to-end lending tech stack — accurate, explainable and compliance-ready, proven in production across 30+ NBFCs.
Most acquired leads never fund. Marketing spend is sprayed across cold, low-intent prospects.
Hand-cranked decisions are costly, inconsistent and impossible to scale at speed.
Effort is spread evenly instead of where risk sits, eroding margins and recovery.
New-to-credit and self-employed borrowers are underserved by bureau-only logic.
Each model plugs into a configurable Business Rule Engine, so policy, scoring and automation work as one system — from first click to final repayment.
Rank and target high-intent leads.
Score, approve, set the offer.
Consistent, policy-true decisions.
Prioritise effort by pay-probability.
Figures reflect outcomes on deployed NBFC portfolios.
Scores every incoming lead by its likelihood to convert, so acquisition spend concentrates on the prospects most likely to fund.
A BRE-driven decision engine that auto-approves the clear cases and routes only genuine edge cases to humans.
Predicts, for every account, the probability of paying before, on, or after the due date — so collection capacity is aimed where it changes the outcome.
Right effort, right account, right time — lower cost-to-collect, higher recovery and protected book quality.
Purpose-built for borrowers with little or no bureau history. Opens credit to the NTC population at controlled, small-ticket exposure — building repayment history while protecting the book.
A model and rule engine tuned to the irregular cash-flows of self-employed borrowers — reading income the way it actually arrives.
Reads repayment behaviour, utilisation and life-stage signals on your existing book to time the next offer — a top-up, a limit enhancement, a second product or a protection add-on — to the moment a customer is most likely to say yes.
Purpose-built models and rule engines for the asset classes NBFCs are scaling into — housing, property-backed and MSME — with collateral, cash-flow and policy logic encoded in the BRE.
Eligibility, risk and policy automation for housing finance — from sourcing to sanction. FOIR, income-multiple, co-applicant clubbing, property-type and builder-approval rules run as code, with the file routed to credit only when a rule genuinely needs a human.
Collateral-aware scoring and rules for property-backed lending — LTV caps by property class and geography, valuation and legal-report checks, end-use and repayment-capacity logic — so the offer is right-sized to the asset and the borrower at the same time.
Cash-flow and bureau-blended underwriting for micro, small and medium enterprises — and the Credit Assessment Memo written by the system, not the analyst.
Bank statements, GST returns, ITR, Udyam and KYB pulled and reconciled automatically. Circular transactions, bounces and related-party flows flagged before underwriting starts.
Turnover, margin and seasonality read from GST and banking; commercial bureau blended with proprietor consumer bureau; sector and vintage benchmarks applied to size the exposure.
Policy, deviation matrix and pricing grid run as rules. Clear cases approved straight-through; deviations routed to the right authority level with the reason attached.
The Credit Assessment Memo — financials, ratios, bureau summary, risk commentary, deviations and recommendation — drafted automatically from the decision trail, ready for committee sign-off.
Plus bespoke models and rule sets built to each lender's policy.
Every model runs on a single configurable BRE — so scoring, policy and automation behave as one auditable system that any lender can tune to its own rules.
Policy-as-code: thresholds, cut-offs and overrides changed without re-engineering.
Every decision carries its reason trail — built for review and compliance.
Low-latency decisions that drop into any LOS / LMS via clean endpoints.
Run, compare and promote model and policy versions safely in production.
Designed around RBI-aware, fair and transparent lending practice.
One engine across unsecured, secured and MSME asset classes.
We design, build and operate the entire technology and analytics backbone for lenders — from a production CRM / LOS to data pipelines, dashboards and integrations.
Origination-to-servicing CRM, configured to your product and workflow.
Cloud, APIs, data pipelines, deployment, monitoring and uptime.
Dashboards, reconciliation and portfolio, funnel and collections insight.
Bureau, KYC, bank-statement, payment and disbursal partners, wired in.
ASDatalab Technologies is a Gurugram-based AI and machine-learning firm focused exclusively on financial services. We bring 6+ years of hands-on lending, credit-risk and collections experience to design, build and deploy models and Business Rule Engines that are accurate, explainable and compliance-ready — across consumer, MSME and secured lending.
Six-plus years inside lending, risk and collections — not generic data science bolted onto finance.
Transparent, audit-ready models aligned to fair and RBI-aware lending practice.
Real APIs, monitoring, versioning and retraining — built to run, not to demo.
We optimise for metrics that move your P&L: conversion, approval rate and collections.
Map your funnel, policy and data.
Validate lift on your portfolio.
Train, calibrate and encode rules.
API integration into LOS / LMS.
Track, retrain and improve.
Deploy proven models into your stack.
Models, BRE, CRM and tech tailored to you.
We run, monitor and retrain for you.
Let's discuss how our models and BRE can move your numbers — on your data, on your portfolio.