Market Risk & Front Office Treasury System
Valuation using FIMMDA methodology. Advanced VaR, CVA, and real-time deal capture engineered for demanding institutional trading desks.
Core Capabilities
Valuation using FIMMDA methodology for fixed income
Market data API connectivity with Refinitiv
Value at Risk (VaR — historical, parametric, Monte Carlo)
Credit Valuation Adjustment (CVA) & CEM
Full front-office deal capture
Built for Banks
Market Risk Capital Charge (MRCC) compliance integrated directly into the trading workflow. Live pricing simulation and stress testing scenarios are standard, providing immediate feedback on portfolio shocks.
Market Risk Capital Charge Engine
The MRCC engine computes regulatory capital for the trading book directly from live positions — no separate end-of-day extract required. It covers the four standard risk classes recognised under RBI's capital adequacy framework for market risk, and is built to migrate alongside the standard as the sensitivities-based FRTB methodology is phased in.
Interest Rate Risk
General + specific risk on the bond and swap book
Equity Risk
General + specific risk on trading book equity positions
Foreign Exchange Risk
Net open position across all currency pairs
Commodity Risk
Directional and basis risk on commodity exposures
Value at Risk Suite
All three industry-standard methodologies run side by side every day, so desks and risk managers can see where they diverge — a strong signal of optionality or tail risk the simpler methods miss. Every VaR number is backtested daily against actual P&L using exception counts at the 99% and 95% confidence levels, in line with regulatory backtesting expectations.
Historical Simulation
Re-prices today's portfolio against actual historical market moves (typically 250–500 days), making no distributional assumption and naturally capturing fat tails and correlation breakdowns observed in the past.
Parametric (Variance-Covariance)
Assumes returns are normally distributed and derives VaR analytically from the portfolio's volatility and correlation matrix — fast to compute and well suited to linear, delta-one books.
Monte Carlo Simulation
Generates thousands of simulated market paths from a calibrated stochastic model, capturing non-linear payoffs (options, structured products) that the other two methods understate.
Desk-Wise Limit Module
Limits are configured hierarchically — entity, desk, book, and trader — with each layer rolling up into the one above it. A breach at any level triggers a real-time alert to the desk head and the independent risk function simultaneously, with a configurable escalation path and audit trail for every override.
VaR limits at desk, book and trader level, with daily utilisation tracking
PV01 / DV01 and duration limits for rates books
Greek limits (delta, gamma, vega) for options and structured desks
Notional and gross/net exposure limits by instrument and counterparty
Stop-loss and management action triggers tied to cumulative P&L
Concentration limits by issuer, sector, tenor bucket and currency
CEM, CVA & SA-CCR
The Current Exposure Method (CEM) is still supported for legacy reporting lines, but new counterparty exposure is measured under SA-CCR — the Basel III replacement that is risk-sensitive to netting and collateral in a way CEM's flat add-on factors never were. In parallel, a Credit Valuation Adjustment is computed for every counterparty to capture the market value of counterparty default risk for both capital and fair value accounting purposes.
Replacement Cost (RC)
The loss that would occur today if a counterparty defaulted, based on current mark-to-market and any collateral held under the netting set.
Potential Future Exposure (PFE)
An add-on reflecting possible future increases in exposure, computed using supervisory factors per asset class and a maturity-adjusted, correlation-aware aggregation across the netting set.
Exposure at Default
EAD = 1.4 × (RC + PFE), feeding directly into the risk-weighted asset calculation for counterparty credit risk.
CVA Computation
CVA is built from the counterparty's expected positive exposure profile, simulated forward at each future time step, combined with the counterparty's marginal probability of default (derived from CDS spreads where liquid, or an internal credit curve otherwise), loss given default, and the relevant discount factor. The same exposure profiles feed DVA, FVA and other XVA adjustments where a desk requires the full valuation adjustment suite rather than CVA alone.
FRTB
FRTB redraws the boundary between the trading and banking book and replaces VaR-based capital with a sharper, more conservative measurement framework. Both prescribed approaches are supported so desks can run under the Standardised Approach from day one and graduate individual desks to internal models as they earn approval.
Standardised Approach (SA)
A sensitivities-based method: delta, vega and curvature risk are computed per risk class (GIRR, credit spread, equity, FX, commodity) and aggregated using prescribed risk weights and correlations — available to every desk regardless of internal model approval.
Internal Models Approach (IMA)
Replaces VaR with Expected Shortfall at a 97.5% confidence level across varying liquidity horizons, subject to a daily Profit & Loss Attribution (PLA) test and a separate capital add-on for Non-Modellable Risk Factors (NMRFs) that fail real-price observability tests.
One Valuation Engine, Every Instrument
Every instrument on the book — cash, derivative, or structured — is priced off the same curve and volatility surface infrastructure, so risk computed for a swap and risk computed for the bond hedging it are built from internally consistent market data rather than two disconnected systems.
Government securities, SDLs & corporate bonds — curve-built and priced off FIMMDA-published par yield curves
Interest Rate Swaps, OIS & FRAs — multi-curve framework with separate discounting and forwarding curves
FX forwards, swaps & vanilla/exotic options — priced off interpolated forward points and volatility surfaces
Cross-currency swaps & MIFOR/MOIS-linked structures — basis-aware valuation across legs in different currencies
Swaptions & interest rate options — modelled using market-standard volatility cubes (strike × tenor × expiry)
Credit derivatives & structured notes — decomposed into vanilla building blocks for consistent risk aggregation
P&L Simulation — PV01 & Greeks
Alongside full revaluation P&L, the engine produces a sensitivity-based ("risk") P&L for every book each day — built entirely from PV01 and the option Greeks rather than re-pricing the full portfolio. Comparing the two is the basis of the FRTB Profit & Loss Attribution test, and the gap between them is itself a risk signal: a widening gap usually means the book has taken on convexity the sensitivity ladder isn't capturing.
PV01
P&L per 1bp parallel shift, rates & credit books
Delta
P&L per unit move in the underlying
Gamma
Change in delta, second-order curvature risk
Vega
P&L per 1 vol point move in implied volatility
Theta
P&L from the passage of time alone
Macro & Micro Economic Dashboards
Position-level risk numbers mean more with sentiment context alongside them. The dashboard layer pulls two of RBI's household sentiment surveys directly into the desk view, sitting next to — not instead of — the bottom-up VaR and Greek dashboards desks already use.
Urban Consumer Confidence Survey (UCCS)
RBI's bi-monthly survey of urban households across major cities, tracking sentiment on the economy, employment, prices, income and spending. The Current Situation Index and Future Expectations Index from each round are pulled in to flag shifts in urban demand sentiment relevant to consumer-facing credit and rate exposures.
Rural Consumer Confidence Survey (RCCS)
The rural counterpart to the UCCS, covering states and union territories across the country. Reading it alongside the urban survey surfaces the urban–rural sentiment divergence that pure market data never shows — a leading indicator the macro overlay on the risk book is built to react to.
The macro layer (UCCS, RCCS, and the broader RBI DBIE series) sits above the micro layer — desk-level VaR, PV01, Greeks and limit utilisation — so a risk manager can move from "what is sentiment doing this round" straight down to "which desk's exposure is most sensitive to it" without switching systems.