Laying a Modern Data Foundation to Fight Financial Crimes
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Over the years, there has been a significant increase in regulations, specifically in the financial services industry, to curb the illicit activities that aid corruption, money laundering, and sanctions-busting. These regulations have particularly increased in the aftermath of the 2008 financial crisis, causing banks to hire additional compliance staff. At one of the major U.S. banks, the compliance staff has increased from 4% of the workforce in 2008 to 15% of the workforce in 2019.

Despite increasing efforts on the parts of financial institutions to maintain compliance with regulations and curb illicit behavior, major entities have been caught on the wrong side of these regulations and have been fined – be it for banking Mexican drug money or breaches of Russian sanctions, causing financial institutions to seek to be rescued by technology. The financial institutions that adopt innovative new technologies and techniques to address regulatory compliance demands will be industry leaders for years to come.

Data Aggregation and Management Deficiencies

Non-compliance, on the part of financial institutions, is not solely due to the global consolidation of financial markets, the consolidation of financial entities, the increasing number of regulations, or the expanded use of economic sanctions. Financial institutions also need the right set of technologies and processes to counter the threat of financial crimes.

The technological infrastructure, particularly in data and analytics, needs to be reassessed and renovated. Think about the basic know-your-customer (KYC) data collection and maintenance. Many banks and other financial institutions still use costly customer calls to update the information that is outdated or missing in the databases, leading to poor data quality. The nonstandard data structures and fragmented sources make data aggregation difficult, which limits the organization’s ability to automate transaction monitoring and perform due diligence. Banks in all markets struggle with the quality of data they keep on their customers, creating a significant obstacle to maintaining accurate customer views. The challenge can be especially daunting in some countries like the United States or the United Kingdom, which have only partial nationwide identification systems, and it can be challenging for banks that operate across borders but are limited by sovereignty laws not to share data across borders.

The Data Foundation for Fighting Financial Crime

Inundated by the lack of integrated data and the poor quality of the available data, financial entities are turning to new tools to aggregate and manage data. Many of these technologies can aggregate data in real time from internal and external data sources for sanctions screening and enriching the KYC process, helping to proactively identify both risks and opportunities.

Take, for example, SpareBank 1 Forsikring, a Norwegian pension product company. To comply with the new anti-money-laundering (AML) legal requirements, SpareBank 1 launched “extended customer approach1,” which entailed differentiated approaches to risk assessment for each customer. This involved scoring every new customer registration on the risk of money laundering and terrorist financing and accordingly, deciding on the countermeasures. The score calculation relied on data that had to be gathered from a variety of data sources, such as whitewash registers, politically exposed persons (PEP) databases, and sanctions lists — essentially a significant amount of data being sourced from external data providers. However, the traditional data warehouse at SpareBank 1 Forsikring, with a 3-to-4-layered architecture, was not agile enough to support these requirements and the new business use cases that the bank envisioned. 

The New Platform at SpareBank 1 Forsikring

SpareBank 1 designed a new data platform called the Information Platform of Pension (IPP). The Denodo Platform, with its data virtualization technology, makes the core of the IPP and gathers and consolidates data from all kinds of external and internal sources systems and makes the integrated data available for reporting and analytical purposes to tools like Tableau and Power BI.

The IPP uses Denodo APIs to connect with public registers, PEP and sanctions lists, address washing, real rights holders, etc., to gather relevant data and calculate the risk score for each individual customer. SpareBank 1 is also using the Denodo Platform catalog to make it easier for users to access the relevant data for themselves without having to go through the data integration teams.

The Denodo Platform has enabled fast, cost-effective data delivery while enabling data analysts to add any number of data sources for ad-hoc analysis and to easily build new insurance products. With the help of the Denodo Platform, the new AML use case, enabling SpareBank 1 to perform real-time verification of new customer registrants, was implemented in a record time of 3 months, compared with traditional data integration platforms, which could have taken up to 12 months to implement similar use cases. Finally, a broader and faster data reach has enabled SpareBank 1 Forsaking to more effectively prepare for Solvency II and IFRS reporting.

To learn more about SpareBank 1 Forsikring and the bank’s new AML capabilities, see the case study.

Sutender Mehta