Financial Economic Crime

Financial Economic Crime

Leverage data and modeling expertise to prevent and detect Financial Economic Crime in a risk-based, compliant approach that meets all regulatory demands.

Financial Economic Crime modeling leverages advanced techniques and innovations, ensuring you're equipped to combat financial crime efficiently and effectively while maintaining full regulatory compliance.

An optimal mix of traditional and advanced models  

While rule-based models offer certain benefits, they face challenges with scalability and detecting complex crime schemes. Drawing from extensive experience, you'll receive optimal model landscaping that effectively integrates rule-based, machine learning, and (Gen)AI techniques for enhanced detection and performance.

Meeting regulatory demands using our advanced analytic techniques will ensure you remain compliant and ahead of the market at all times.

By utilizing advanced analytic techniques, you’ll not only meet regulatory demands but also stay compliant and ahead of the market at all times.


Various vendor solutions can help mitigate your Financial Economic Crime risk, often providing a strong alternative to in-house model development. With our extensive experience, we'll guide you through the vendor landscape and craft a buy-or-build strategy tailored to your company’s needs.

Our Financial Economic Crime Expertise

Expertise across all FEC domains

Models for Transaction Monitoring, CDD, Sanctions, and Fraud are just the beginning. With expertise extending from data and modeling to workflow optimization, we integrate both simple and advanced solutions, including Machine Learning and GenAI, to enhance every part of your process.

Risk-based, efficient, and effective

At Zanders, we tailor risk-based solutions to maximize your effectiveness and efficiency. In the FEC domain, where false positive rates can be high, we help you transition to next-generation models that provide high-quality alerts and minimize false positives.

Ensuring regulatory compliance

We create flexible models tailored to your country’s regulatory needs. Our services include a well-designed MRM framework to ensure compliance and effective management of model risks at all times.

Latest Insights

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Component VaR: Automating VaR Attribution

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Component VaR: Automating VaR Attribution

VaR has been one of the most widely used risk measures in banks for decades. However, due to the non-additive nature of VaR, explaining the causes of changes to VaR has always been

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The Ridge Backtest Metric: Backtesting Expected Shortfall

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The Ridge Backtest Metric: Backtesting Expected Shortfall

Challenges with backtesting Expected Shortfall Recent regulations are increasingly moving toward the use of Expected Shortfall (ES) as a measure to capture risk. Although ES fixes many

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FRTB: Harnessing Synergies Between Regulations

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FRTB: Harnessing Synergies Between Regulations

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Targeted Review of Internal Models (TRIM): Review of observations and findings for Traded Risk

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Targeted Review of Internal Models (TRIM): Review of observations and findings for Traded Risk

The EBA has recently published the findings and observations from their TRIM on-site inspections. A significant number of deficiencies were identified and are required to be remediated by

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FRTB: Profit and Loss Attribution (PLA) Analytics

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FRTB: Profit and Loss Attribution (PLA) Analytics

Under FRTB regulation, PLA requires banks to assess the similarity between Front Office (FO) and Risk P&L (HPL and RTPL) on a quarterly basis. Desks which do not pass PLA incur capital

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The usage of proxies under FRTB

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The usage of proxies under FRTB

Non-modellable risk factors (NMRFs) have been shown to be one of the largest contributors to capital charges under FRTB. The use of proxies is one of the methods that banks can employ to

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FRTB: Improving the Modellability of Risk Factors

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FRTB: Improving the Modellability of Risk Factors

Under the FRTB internal models approach (IMA), the capital calculation of risk factors is dependent on whether the risk factor is modellable. Insufficient data will result in more

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VaR Backtesting in Turbulent Market Conditions​: Enhancing the Historical Simulation Model with Volatility Scaling​

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VaR Backtesting in Turbulent Market Conditions​: Enhancing the Historical Simulation Model with Volatility Scaling​

Challenges with VaR models in a turbulent market​ With recent periods of market stress, including COVID-19 and the Russia-Ukraine conflict, banks are finding their VaR models under

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Regulatory exemptions during extreme market stresses: EBA publishes final RTS on extraordinary circumstances for continuing the use of internal models

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Regulatory exemptions during extreme market stresses: EBA publishes final RTS on extraordinary circumstances for continuing the use of internal models

The Covid-19 pandemic triggered unprecedented market volatility, causing widespread failures in banks' internal risk models. These backtesting failures threatened to increase capital

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Fintegral

is now part of Zanders

In a continued effort to ensure we offer our customers the very best in knowledge and skills, Zanders has acquired Fintegral.

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RiskQuest

is now part of Zanders

In a continued effort to ensure we offer our customers the very best in knowledge and skills, Zanders has acquired RiskQuest.

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Optimum Prime

is now part of Zanders

In a continued effort to ensure we offer our customers the very best in knowledge and skills, Zanders has acquired Optimum Prime.

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