Timeliness and Reliability in the Transmission of Regulatory Reports
Managing risk and regulatory compliance is an increasingly complex and costly endeavour. Regulatory change has increased 500% since the 2008 global financial crisis and boosted the regulatory costs in the process. Given the fines associated with non-compliance and SLA breaches (banks hit an all-time high in fines of $10 billion in 2019 for AML), processing...
4 Ways AI Can Future-proof Financial Services’ Risk and Compliance
The core function of a bank is to protect assets, identify risks and mitigate losses by protecting customers from fraud, money laundering and other financial crimes. In today’s interconnected and digital world, managing risk and regulatory compliance is an increasingly complex and costly endeavour. Regulatory change has increased 500% since the 2008 global financial crisis...
Identifying Financial Fraud With Geospatial Clustering
For most financial service institutions (FSI), fraud prevention often implies a complex ecosystem made of various components –- a mixture of traditional rules-based controls and artificial intelligence (AI) and a patchwork of on-premises systems, proprietary frameworks and open source cloud technologies. Combined with strict regulatory requirements (such as model explainability), high governance frameworks, low latency...
Leveraging ESG Data to Operationalize Sustainability
The benefits of Environmental, Social and Governance (ESG) are well understood across the financial services industry. In our previous blog post, we demonstrated how asset managers can leverage data and AI to better optimize their portfolios and identify organizations that not only look good from an ESG perspective, but also do good — companies that...
Building a Modern Risk Management Platform in Financial Services
This blog was collaboratively written with Databricks partner Avanade. A special thanks to Dael Williamson, Avanade CTO, for his contributions. Financial Institutions today are still struggling to keep up with the emerging risks and threats facing their business. Managing risk, especially within the banking sector, has increased in complexity over the past several years. First,...
A data-driven approach to Environmental, Social and Governance
The future of finance goes hand in hand with social responsibility, environmental stewardship and corporate ethics. In order to stay competitive, Financial Services Institutions (FSI) are increasingly disclosing more information about their environmental, social and governance (ESG) performance. By better understanding and quantifying the sustainability and societal impact of any investment in a company or...
Modernizing Risk Management Part 2: Aggregations, Backtesting at Scale and Introducing Alternative Data
Understanding and mitigating risk is at the forefront of any financial services institution. However, as previously discussed in the first blog of this two-part series, banks today are still struggling to keep up with the emerging risks and threats facing their business. Plagued by the limitations of on-premises infrastructure and legacy technologies, banks until recently...
Modernizing Risk Management Part 1: Streaming data-ingestion, rapid model development and Monte-Carlo Simulations at Scale
Managing risk within the financial services, especially within the banking sector, has increased in complexity over the past several years. First, new frameworks (such as FRTB) are being introduced that potentially require tremendous computing power and an ability to analyze years of historical data. At the same, regulators are demanding more transparency and explainability from...
