Data-Driven Impact in Finance: Overcoming Challenges, Maximising Value

Leveraging data drives financial organisations’ decisions, efficiency, and innovation. We can provide guidance on how to improve data quality and governance, develop data-driven solutions, and create a common language for your organisation.

Contact us to discuss the possibilities and start your journey towards maximising the impact of data science in the financial industry.

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Data services we provide for the financial sector

With our expert guidance and support, you can leverage the full potential of data to drive growth and improve performance. We provide a range of services to help organisations in finance harness the power of data:

Data Strategy for Finance

We help you leverage data for organisational value. Our strategy aligns data initiatives with business goals, optimising data usage for informed decisions and efficiency.

Data Engineering for Finance

We handle the technical aspects of becoming data-driven, including designing and building the necessary infrastructure to store, process and analyse data.

Advanced Analytics for Finance

Our team develops advanced algorithms to turn data into actionable insights and knowledge.

Data Visualisation and User Experience

We ensure that our insights are easy to understand and use, through clear and effective data visualisation and user-friendly interfaces.

Financial Risk Modelling

Financial institutions need to continuously adapt their credit risk models and processes to stay compliant with changing regulations or face penalties and reputational damage. Our financial risk models provide a comprehensive and accurate assessment of creditworthiness through data analysis, helping institutions make better decisions about lending, risk management, and compliance. At ADC, we develop, calibrate, validate, and monitor credit risk models with the necessary expertise to support your risk management needs. We also provide stress testing and generate reports to meet regulatory requirements.

Financial Risk Modelling

working on financial risk modelling

Fraud detection and Anti-Money Laundering (AML)

Fraud detection and Anti-Money Laundering (AML) are essential for stopping illegal activities like money laundering and terrorism financing. However, identifying fraudulent clients is costly and time-consuming, leaving companies at risk of fines and reputational damage. ADC offers data science solutions that quickly and accurately identify fraudulent activities using flexible algorithms. We help financial institutions stay ahead of money laundering threats, minimise the risk of penalties and fines, and focus on business growth with confidence. Our approach, which includes ethical AI, optimises your AML processes and ensures compliance with (EU and local) regulations, saving you time and resources.

Fraud Detection and Anti-Money Laundering (AML)


ESG Banking

Environmental, Social, and Governance (ESG) factors can have a significant impact on the long-term performance and stability of companies and households, creating pressure on financial institutions to integrate them into risk management and decision-making. However, traditional risk models do not account for sustainability factors, leading to incomplete and potentially inaccurate assessments of risk. Our solutions integrate sustainability and ethical considerations into risk management processes to accurately assess environmental financial risks and promote responsible business practices. By incorporating ESG data into risk models, ADC helps financial institutions meet regulatory requirements, enhance their reputations, and make better decisions, leading to improved financial performance while responding to the growing demand for responsible and impactful banking.

ESG in Banking


Business Intelligence in Finance

Poor data quality is a common problem for financial institutions due to the challenge of managing vast amounts of data from multiple sources. This can negatively impact business intelligence and decision-making. Common data issues like inconsistent definitions, missing data, and inaccurate entries can make data analysis ineffective and unreliable. To address this, data transformation, cleaning, and synchronisation are necessary, as well as customised (automated) data quality controls. Our experienced team can help create comprehensive solutions that improve your organisation’s data quality, enabling better decision-making, operational efficiency, and accurate risk management and reporting. With our extensive financial industry experience, we can provide scalable and flexible solutions tailored to your specific needs.

Business Intelligence in Finance


“It’s really impressive what the team from Amsterdam Data Collective has been able to achieve in terms of impact in only a matter of months. Thanks to their combination of senior marketing experience with state-of-the-art technical knowledge they are the perfect partner to translate our commercial data into value for the bank.”


-Richard Leijnse – Managing Director NIBC Retail Banking


Scott Bush

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Camilla Huus

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Govert van Koningsveld

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