Math Labs collaborates closely with our partners and clients in creating high impact, repeatable solutions to critical problems in the financial services domain.
Advanced Risk platform
Enhanced Risk Profiling
Math Labs adds deep insights from world data and AI to classical risk models to bring them closer to ground realities - enabling Risk/Pricing teams at banks and insurance firms to accurately assess a range of risk-types.
Detection and Causal analysis of Risk Patterns
The Math Labs' Concept Engine enables detecting' periods of unnatural movements, and automatically explaining them via human-understandable concepts without human intervention.
‘Define your own Thematic Risk’ and see the impact of your custom risk – on your portfolio.
An advanced AI based approach to automated hypothesis testing of analysts’ own risk-sources of interest converting ideas into concrete, quantitative impacts - e.g. creation of an ESG Risk Engine.
Market Explorer origination and diligence
An intelligent engine thats begins with custom sector creation and a long list of targets - to progressively hand-hold an investment team through the origination funnel.
AI Powered Target Discovery
A mathematically-driven market scanning and screening to find 'hidden gems' acquisition/partnership targets in the difficult domains.
Algorithmic diligence assistance via peer group formation, comparative techno-functional diligence across peers, custom-specialty based capability-scoring and adverse events tracking.
ESG Intelligence platform
Understand the market-driven "greeks" for specific ESG themes for your portfolio companies as well as your overall portfolio.
Do a comparative analysis of the degree of ESG alignment of each company in your portfolio, based on what the companies actually do - a fundamentals based approach.
ESG Portfolio Designer
Design the right ESG portfolio for your fund, balancing the various ESG components and financial components (e.g. risk, return and covariances) as per your custom preferences, powered by Quantum mathematics.
Transaction-Anomaly Investigation platform
At the heart of retail, corporate and investment banks is a transaction - a trade, a payment transfer or an account withdrawal, among others. Banks look to monitor both its transactions, as well as the relevant principals - for anomalous events or event-patterns.
Math Labs defines a unique data space combining client data with valuable signals from external world data - on which it applies its own patterns detection and root-cause framework to identify-review suspicious transactions & principals post detection, algorithmically - helping banks reduce expensive false-positives, at scale.