The financial services industry is under an enormous amount of pressure from regulators at the moment and is finding itself getting fined on a regular basis for not having the correct Anti-Money Laundering (AML) controls in place. These fines not only damage a firm’s reputation but also mean that the FSA is going to be keeping a close eye on them in the future.

AML is really in the spotlight for regulators at the moment, and almost every large financial organisation has been fined for an AML failure. Many financial services IT departments face a similar issue - legacy systems that have been developed and expanded organically (often in-house) can often lead to data becoming siloed and disconnected. As one of the top 10 concerns for banks looking to achieve compliance and avoid fines, what exactly should banks be doing to overcome this challenge? For me, the answer lies in Business Intelligence.

Man and Machine

A couple of large banks that I know of employ around 1500 analysts to carry out AML investigations. Even with this enormous number of skilled analysts banks are still getting fined. Whilst some automated systems do exist to help, financial institutions have a way to go before they can say that they are intelligently using all of the data in the business to help solve this huge problem of being AML compliant. Carrying out manual investigations into suspicious transactions is obviously not very efficient. ‘Googling’ a person becomes difficult when you start to think about the potential variations in spelling of that person’s name or address for example.

Guilty by Association

Social media is an excellent and often untapped resource that can and should be used to help in AML investigations, but without the correct business intelligence strategy in place, this too would take too much time and could become more of a hindrance than a help. However by employing the correct data infrastructure and technology, 80-90% of false positive suspicious activity alerts could be eliminated automatically, leaving the analysts to investigate the real criminal activity.

What banks should look to do is employ the technology to match structured and unstructured data both internally and externally to the enterprise to build a picture of an account holder who has been flagged as suspicious. This means linking a person’s bank account with their job or their recent activity for example, have they just won the lottery? If so, that would explain the huge deposit just made into their account.

It really comes down to ensuring that you have a single customer view. If you could immediately see all of the accounts that person holds you would know that a large, unusual transaction is the result of a mortgage being paid off by a savings account for example.

The right business intelligence strategy would allow data from sources that aren’t usually linked to be automatically scanned at the same time, and integrated with the bank’s existing database. For this to work master data management is vital. The correct data warehouse with information stored in a meaningful way is essential, and being able to link individual transactions back to this will mean that banks really will have a single customer view, that can be shared across the organisation, and leave them less vulnerable to AML compliance fines.

A Catalyst for Change

So why aren’t banks doing this? As it stands the investment that banks are making in the regulations space tend to be carried out on a tactical basis. FATCA and Basel 3 for example will all have been dealt with separately, as and when it’s been absolutely essential.

However if the financial services began to think more strategically it would become clear that a common factor in all these regulations are the skills and data sets all of these regulations require the same skills and data sets – if businesses integrated their data across the entire organisation once and for all, it would mean that they could increase their agility and become much more reactive in their response to the unrelenting barrage of regulations. This often boils down to a shift in outlook for businesses who have traditionally seen investment in technology as an expensive outlay rather than an opportunity to transform the business with better decision-making processes.

Effectively managed quality data is the lifeblood of successful AML implementation and ensures the effective integration of risk considerations into the decision-making that underpins it. The extent to which financial services companies are able to capitalise on their investment in data infrastructure will depend on their commitment to invest time in understanding and harnessing the data for business intelligence and competitive advantage.

Arriving quickly on the horizon for financial services IT departments is FINREP COREP which comes into play next year as banks will need to be sharing all of their data on a monthly basis – AML compliance is a requirement; using it as a springboard for better business intelligence is a smart business decision.