Risqova — Liquidity Risk & Research

Liquidity Risk & Research

Behavioral Liquidity Intelligence for Banks and NBFCs

Risqova combines funding behavior, macroeconomic conditions, balance-sheet signals and research-led analytics to identify emerging liquidity pressure and strengthen risk decision-making.

Designed for liquidity risk, ALM, treasury and senior risk teams at banks and NBFCs.

Explore Our FrameworkContact Risqova

Liquidity risk is rarely visible through a single metric. Headline deposit growth, regulatory ratios and static ALM reports can mask important changes in funding behavior, pricing, refinancing pressure and balance-sheet structure. Risqova is building a regime-aware framework to understand those mechanisms before they become obvious.

What we are trying to solve

Beyond Static Liquidity Reporting

Common liquidity monitoring approaches often emphasize

  • Regulatory ratios
  • Contractual maturity ladders
  • Historical reporting
  • Static stress assumptions

Risqova focuses on

  • Behavioral funding patterns
  • Funding composition
  • Repricing
  • Rollover and refinancing pressure
  • Macro-to-liquidity transmission
  • System-wide funding conditions
  • Bank-specific deviations from system behavior
The question is not simply whether liquidity metrics are healthy today. It is whether the institution is having to work progressively harder to fund its balance sheet.

Benchmarking approach

System Benchmark → Institution-Specific Insight

  1. 01

    Public Data & Regulatory Evidence

  2. 02

    Macro-Financial Regime

  3. 03

    Behavioral Benchmark

  4. 04

    Institution-Specific Data

  5. 05

    Calibration

  6. 06

    Decision Support

Risqova builds an external behavioral benchmark using public data, historical regimes and regulatory evidence.

Institution-specific data is analyzed against this benchmark to identify deviations, vulnerabilities and institution-specific funding behavior.

The system benchmark provides context. The client data provides calibration.

Macro-economics layer

Macro-Economic Context

Liquidity risk does not evolve in isolation.

Funding conditions are shaped by the broader macroeconomic environment — including credit demand, household savings behavior, inflation, consumption, investment, market liquidity and monetary conditions.

Risqova connects these macro signals to funding behavior so that changes in deposits, borrowing conditions and refinancing pressure are interpreted in context rather than viewed as standalone metrics.

  1. 01

    Macro Conditions

  2. 02

    Funding Behavior

  3. 03

    Balance-Sheet Pressure

  4. 04

    Liquidity Risk Implication

Funding analysis

Funding & Liquidity Intelligence

Risqova studies how funding conditions evolve across deposits, wholesale markets, borrowing channels and other balance-sheet sources — and how those changes interact with macroeconomic conditions, liquidity buffers and institution-specific behavior.

Across funding sources. Across regimes. Across institutions.

Decision intelligence

From Research to Decision Support

Risqova is developing an AI-enabled decision-support layer designed to combine research, structured data, behavioral models and institutional evidence.

The capability is under development and is being designed as an evolving decision-support layer, not an operational product today.

The AI is not the risk model. The underlying logic remains structured, explainable and evidence-based; AI acts as the reasoning and interaction layer around that framework.

  • Research-grounded answers
  • Source citations
  • Structured data retrieval
  • Behavioral model logic
  • Benchmarking
  • Explainability
  • Auditability

Methodology

Research Before Model

Risqova does not begin with fixed thresholds and then search for supporting evidence. The data generates the questions. Relationships are challenged before they are allowed to become model assumptions.

Sequence

From Observation to Model Implication

  1. 01

    Observation

  2. 02

    Decomposition

  3. 03

    Hypothesis

  4. 04

    Mechanism

  5. 05

    Economic Theory

  6. 06

    RBI / BIS / Regulatory Evidence

  7. 07

    Academic Evidence

  8. 08

    Empirical Validation

  9. 09

    Confidence Assessment

  10. 10

    Model Implication

About Risqova

Built by Practitioners

Risqova is a research-driven fintech combining practitioner experience, empirical macro economics research, structured analytics and AI-enabled decision support to build defensible risk intelligence for banks and NBFCs.

Our work is designed to connect economic context, funding behavior, institution-specific evidence and explainable AI to practical risk decisions.

Who we work with

  • Heads of Liquidity Risk
  • ALM and Treasury leadership
  • Chief Risk Officers
  • Bank risk teams
  • NBFC treasury and funding teams
  • Senior risk practitioners

Contact

For research discussions, benchmarking questions or institution-specific liquidity work, write to us at contactus@risqova.in.

Office

SCO 47, M3M 113 Market
Sector 113, Dwarka Expressway
Gurugram, Haryana 122017