NSDS Associates Pvt Ltd

Project 06 · Sri Lanka · LECO

Loan Consumer Tracking & Risk Analytics

Machine learning decision support for single-installment loans

Loan RiskRepayment risk analytics
Customer
LECO
Industry
FinTech, credit risk, analytics
Project type
Decision-support application
Approach
Custom ML models
5

Behavioural signals used to score risk

1

Consolidated view of every loan customer

100%

Decisions kept with staff, supported by AI

ML

Models trained on historical payments

01The business problem

LECO already held years of data on customer payments, transactions, outstanding balances and loan settlement behaviour. Historical records alone, however, do not tell decision-makers how likely a customer is to repay in the future.

02What we delivered

We built a standalone application that adds an analytical layer on top of this transactional data. It consolidates each customer's payment information, analyses repayment behaviour, identifies behavioural patterns, tracks customers receiving loan facilities and estimates repayment risk. Custom models use signals such as payment behaviour, settlement history, outstanding amounts, payment consistency and transaction patterns. The goal is not to replace human judgement but to give staff stronger evidence for their decisions.

Let's build together

Modernizing mission-critical systems while building the next generation of AI-native applications.

Our portfolio spans international SaaS, enterprise utilities, payments, predictive analytics, generative AI, multi-agent systems, private AI, social media, education and competitive intelligence. We would welcome the opportunity to apply this experience to your organization.