The financial services industry is getting only part of the risk management and anti-money laundering point. And modern business models in banking and insurance militate against effective know-your- customer procedures says Nigel Morris-Cotterill of The Anti Money Laundering Network.

World-wide, regulators are including in the requirements they place on affected businesses demands that they build a profile of their customers.

This "know your customer" approach is vital in the attempts to detect and deter money laundering and terrorist financing.

Historically, many financial institutions have taken a narrow view of "know your customer." The basis for this is that, historically, banks in particular have wanted to know enough information to enable them to enforce their contract terms in cases of default or fraud. And so, whilst not going as far as "We know where your children go to school," "we know where you live" was generally seen as good enough.

And banks, and their regulators, used to take the view that this approach was good enough for countering money laundering, too. After all, the basic principles of Basle II are not new - they are restating good business practice: they can be summarised as "don’t think about how much you might make, worry about how much you might lose," or "always watch the downside."

That was then, and this is now.

Now under a raft of buzzwords (e.g. enhanced due diligence) and legislation driven panic and uncertainty, financial services businesses are driven to implement ever more complex and costly risk management systems.

From checking lists of names for blocked and politically exposed persons to installing neural networks to monitor all transactions happening world-wide in large and complex financial services businesses the issue of compliance comes down to one thing: the state is pushing the burden of policing onto the financial sector and with it the massive costs associated with detection and prevention.

The Regulators often miss the most salient point: the demands that they are placing on regulated businesses is diametrically opposed to the business model that banks and insurance companies, in particular, are developing.

The new business model is to put distance between those conducting financial services operations and those to whom the services are provided.

Internet banking and telephone banking are the more obvious examples but the most insidious, and the most dangerous, is that of centralised call centres which handle the calls for a number of branches. There is no personal relationship between a bank officer and the customer. Centralised payment processing services add to the remoteness of services provided.

The cost savings created by these measures are now being largely offset by the need to create, implement and maintain compliance and risk management systems that were built into old fashioned banking: the bank manager did, actually, know his customers.

He knew where they came from; he socialised with them if they had much money and saw daily exception reports if they didn’t. Those with routinely small credit balances and average regular salaries simply flew under the radar: they were not marketing prospects, nor were they risks to the branch’s balance sheet.

In short, the bank manager used to run a business: in effect, he was a salaried franchisee and to make his franchise work, he needed to understand his own business, his potential constituency and his customers.

Now, to a degree as a result of the work in marketing which uses KYC to more efficiently target sales efforts, and the use of computer analysis of a wide range of lifestyle data, the concept of KYC for risk management is largely entrusted, at least at a preliminary level, to technology.

That technology focuses on the transaction history and predicted transactional activity of an account.

The mixing of the need for financial risk profile and for marketing information has led to a strange marriage - one where the two sides are in bed but there is a big gap between them. The bank collects two different sorts of data about the same people but has no way of linking them.

Marketing people are able to tell with some degree of accuracy what a customer wants for himself and financial transaction analysis programmes can tell if he is under-or over achieving against the bank’s expectations for that account. But these two sets of data are not tied together.

But they can be: Pat Dade of Risk Values has developed a system for bridging the gap between the two types of data. And in doing so, has developed a software tool that collects information that relates to the customer’s attitude to the institution to provide a view as to the likelihood that the person displays a propensity to commit financial crime such as fraud, money laundering or using accounts for terrorist financing.

But there is one thing existing technology cannot do: it cannot develop a "gut reaction." But Risk Values does precisely that.

Using the customer’s own view of himself and how he relates to the institution, and setting that off against psychological norms and background data collected over a period of some 30 years, Risk Values assesses those applying to do business with a financial institution and displays, on a scale of one to five, the risk associated with that customer.

The principles of enhanced KYC mean that simply knowing the customer’s name and address are not enough. Financial institutions are having to build models based on the sort of customer they expect to attract, the sort of activity that would be normal for those customers and then to assess whether account activity - or non-activity - fits within those norms. This is both time consuming and expensive. And it fails to address the issues relating to new customers and to low activity accounts.

Certain types of business, such as money services businesses, rarely conduct more than occasional transactions with customers. They do not build up a transaction history and, in any case, the software and hardware necessary to do such is far outside their budget. This is also the case with, for example, community banks and thrifts.

These businesses need to resort to manual monitoring of accounts and that, too, is expensive. The use of profiling for propensity to financial crime would mean that the manual monitoring could be focused on the higher risk accounts: around 70% of account holders are regarded as unlikely ever to abuse the relationship with the financial institution but banks find it difficult to know which 30% of their customers should receive greater monitoring. And under 1% of the population are "the really bad guys."

It follows that banks are wasting huge resources by monitoring everything that passes through their hands.

The cost of monitoring is not just the cost of the technology: it is to a large extent the cost of dealing with the reports that the technology produces. Where monitoring criteria are set too wide, then cases will slip through, exposing the institution to risk of fraud or being involved in money laundering or terrorist financing.

Where monitoring criteria are set too narrowly, then there will be too many "false positives," that is reports which, on analysis, prove to be merely out of the ordinary. It is these false positives that cause cost to the organisation: each has to be investigated and reasons displayed as to why there are not, in fact, suspicious circumstances.

By integrating the collection of the data for assessing the Risk Value into the customer acquisition process or future CRM surveys, the cost of collection of that data may be, in percentage terms, insignificant.

By applying the Risk Value as a criteria within the monitoring system, the number of false positives may be significantly reduced - and therefore the cost of monitoring much reduced.

Moreover, for those businesses which are performing manual monitoring of all transactions, the additional "gut reaction" provided by an assessment of the customer’s attitude to the account will provide the bank with a way of prioritising the accounts it monitors, and of prioritising the handling of exception reports. This will lead to greater efficiency and, again, a cost reduction.

Simply watching the customer’s financial profile is not enough - as the focus enhanced due diligence shows. It is not enough to know the customer’s financial position - banks and an increasing number of businesses to be brought within the scope of money laundering legislation also need to know the customer. There is no doubt that this means more than just his name and address.

Nigel Morris-Cotterill is a counter-money laundering strategist with Silkscreen Consulting, part of The Anti Money Laundering Network. www.countermoneylaundering.com

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