Production-grade ALM intelligence platform for non-banking financial companies. Identifies maturity mismatches, quantifies liquidity gaps, and generates automated risk reports from raw transaction data.
Non-banking financial companies (NBFCs) in India and sub-Saharan Africa are required under RBI guidelines to maintain adequate liquidity buffers and report asset-liability maturity profiles. Manual ALM reporting from spreadsheets is error-prone, time-consuming, and produces static outputs. TreasuryIQ replaces this with an automated, data-driven intelligence pipeline.
A 10,000-row synthetic NBFC dataset containing loan disbursement records, repayment schedules, fixed deposit liability maturities, and working capital lines across 5 maturity buckets: 0-30 days, 31-90 days, 91-180 days, 181-365 days, and over 365 days.
A severe negative ALM gap was identified in the 31-90 day bucket: total asset maturities of NGN 320M versus liability maturities of NGN 890M, producing a net gap of negative NGN 570M. This represents a liquidity stress point requiring immediate management attention.
Automated ingestion, type validation, missing value imputation, currency normalisation, and maturity bucket assignment for 10,000 NBFC loan and liability records. Outputs a cleaned, analysis-ready DataFrame with 100% completeness.
Comprehensive exploratory analysis and ALM gap analysis. Maturity profiles constructed for 5 asset types and 5 liability types. Net gap computed per bucket. Cumulative gap waterfall chart generated. Critical negative gap identified in the 31-90 day bucket.
Machine learning model to predict liquidity stress events 30 days in advance based on rolling GAP ratios, deposit withdrawal velocity, and seasonal repayment patterns.