The challenges of a midsize insurer

Combatting money laundering and terrorist financing

The midsized Benelux insurer ERGO Insurance nv faces the challenge of meeting ever-growing international and national regulations while keeping related costs within acceptable limits. One example is meeting the EU and national legal obligations concerning money laundering and the prevention of terrorist financing. ERGO Insurance decided to automate its related business processes using SAS®. “We save precious time and money every day ever since we implemented the SAS solution.”

Thanks to Fuzzy logic and fine-tuning of scenarios, we are able to reduce false positives to a level manageable for our investigator team.

Steven Verlinden
Business Analyst, ERGO Insurance

While the ERGO Insurance Group is one of the largest insurance groups in Europe, the Benelux subsidiary is only a midsize player, employing approximately 350 people. That brings extra challenges when it comes to meeting stringent European and national directives, given the limited resources available compared to large financial institutions.

A complicated and tedious task

Legal obligations include the requirement to ensure that ERGO Insurance policies are not being used as channels to finance criminal activities such as money laundering and terrorist financing. “We specialize in life insurance products for individuals and the self-employed. We must meticulously check every contract against extensive black lists of suspicious individuals and organizations,” says ERGO Business Analyst Steven Verlinden. “That is a complicated and tedious task, given the enormous amount of data involved and the fact that both the black lists and the insurance policies are subject to frequent changes. For example, contracts must be re-checked upon all contractual modifications such as the assignment of a new beneficiary. We must validate and document each modification.”

Dealing with uncertainties

ERGO Insurance launched a project to automate as much as possible the processes related to checking contracts against the black lists. “We were convinced that improving our efficiency would save us a substantial amount of money and time,” explains Verlinden. “However we were abundantly aware of the risks and pitfalls of total automation. For example, there is the issue of precisely matching our contractors with the suspicious individuals and organizations listed in the Dow Jones files we purchase. To give just one example: a given name can be spelled in a variety of ways, or with the addition of abbreviations, middle names and nicknames. We needed a powerful tool that is able to deal with these kinds of uncertainties.”

Matching big data for precise identification of suspects

SAS provided the required functionality. “We selected SAS for two primary reasons,” confirms Verlinden. “Firstly, it contains very powerful fuzzy logic and parameterization capabilities. Fuzzy logic enables the system to report matches between non-identical but textually, phonetically or numerically similar data records, including an assessment of the probability or quality of the match. The parameterization capabilities enable us to precisely define the criteria that are required to generate an alert. This is essential if we are to successfully expose all suspicious records while avoiding false alerts as much as possible. Secondly, SAS is able to process enormous quantities of data in a short time. That was important, given the need to perform a daily check of our entire database covering more than 800.000 customers against the huge amount of proven and suspected ‘bad guys’ in the Dow Jones files.”

Tailored to the needs of insurance companies

The SAS solution lived up to its promises, thanks in part to the implementation efforts performed by everyone involved at ERGO Insurance and SAS. There was an important additional challenge to this implementation,” notes Verlinden. “Consider the fact that this was the first time the system was implemented at an insurance company. Previous implementations were in the banking sector, which involves monitoring financial transactions rather than complex contracts. But with the help of SAS consultants we managed to tailor the system to our exact needs. The solution now processes our entire database every day, verifying, validating and documenting every single modification within 24 hours. That is an impressive feat as well as being quite reassuring.”

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Challenge

Meeting legal obligations in the battle against money laundering and terrorist financing

Solution

SAS® Anti-Money Laundering

Benefits

  • Exposing all suspicious records while avoiding false alerts
  • Automated routine to verify, validate, document all changes.
  • The entire database is being checked every 24 hours

Lessons Learned

  • Meticulously define both business and technical requirements, based on hard data such as the number of records to be processed. This enables you to determine the soft- and hardware required to guarantee smooth performance.
  • Continuous communication between analysts and developers from the SAS side and the people managing the backend systems providing the source data. Data quality and consistency aspects such as formats, rules, and extraction times are extremely important for the different systems to communicate in a safe and stable way.
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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