How you can get on the front foot with correspondent banks
Over the years there’s been a decline in correspondent banking relationships – a decline that seems to have impacted smaller jurisdictions with poor compliance frameworks. According to the BATF's Respondent's Playbook for Obtaining and Maintaining a Correspondent Banking Relationship, the number of global correspondent banking relationships decreased by 15.5% between 2011 and 2017.
Why? A correspondent bank tends to have limited compliance data from a respondent bank, which makes them more at risk of being exposed to money laundering and other compliance risks.
What is correspondent banking?
Correspondent banking is when one bank (the correspondent bank) provides services to another bank (the respondent bank). Usually, the two financial institutions are in different countries to each other. The correspondent bank will provide services such as holding deposits, facilitating wire transfers, cash management and foreign exchange services.
So – as a respondent bank – you need to prove yourselves to the correspondent bank so that they can carry out services for you. How? By providing them with better compliance data, particularly financial crime risk and anti-money laundering data.
But, existing systems for this required risk assessment are data-poor.
In this article, we’ll show how you can gather reliable compliance data to inform your self-assessment of risk performance so that you can build a better correspondent banking relationship. But first, let’s look at five reasons why you need to do this.
1. Better compliance data means less risk
Less risk for the correspondent bank, meaning less risk for you – this increases the chance they’ll engage with you.
A correspondent bank is looking to build partnerships with as little risk attached as possible. So, if you can be rigorous in your provision of risk management data, they'll be more confident in engaging with you.
A correspondent bank will assess the respondent bank’s anti-money laundering framework, alongside other compliance functions. They’ll need information about your customers, your transactions and your financial crime risk management programmes. They’ll base their assessment on their own understanding of these factors. This understanding is of course highly impacted by the conversations they have with the respondent bank, and all the information sent to them. Any weaknesses they find will increase their exposure to risk.
You – the respondent bank – need to communicate all the potential high-risk factors of financial crime, and all the measures you’ve implemented to mitigate risk, particularly your anti-money laundering framework. Your data should show that your ‘superior knowledge of the local market’ could actually help in ‘lowering the correspondent’s overall risk in the market.’ (BATF’s Respondent Playbook).
2. Better compliance data means less cost
There are three broad factors that a correspondent bank will assess when deciding whether to engage with a respondent bank, one of which is cost.
Factors a correspondent bank will consider
- Potential profitability
- Expected costs (including financial crime compliance costs) of service delivery
- Creditworthiness of the respondent
(From the BATF’s Respondent Playbook: approx. two-thirds of the correspondent banks BAFT surveyed consider these three factors)
There is a cost for the correspondent bank in onboarding a respondent bank, a significant amount of which is based on their own AML and financial crime framework. So, efficient provision of all the information the correspondent bank needs will reduce this cost for them, which – again – will increase the chances that you can obtain a relationship with them.
3. Better compliance data means less time
Most due diligence processes are manual. They’re normally conducted every year and they can then take 6 months to complete. By this time the information is likely to be outdated.
As well as being more accurate and objective, automation of this process can be invaluable to securing a relationship with a correspondent bank. You can spend less time on data collection and more on growing your business and securing clients.
It’s one thing to obtain a correspondent bank relationship. But to maintain it, it’s important that you can update the correspondent bank regularly. Correspondent banks tend to review new partnerships every 6 months. Then they’ll review you every two years, but if you’re high-risk, they’re likely to do this every one year. Without automated due diligence processes, you’ll be on the back foot when it comes to their review.
4. Better compliance data means you’re more adaptable to change
The FATF Standards dictate mandatory requirements that countries must impose on their private sector. In a world of constantly changing requirements and regulations, it’s important to have data that keeps up. Without using technology to provide this constantly up-to-date data, you can see how easy it is to fall behind.
5. Better compliance data means less subjectivity
Correspondent banks want to see accurate information so they can fairly evaluate a respondent bank. They want to see critical self-evaluation against due diligence criteria and being able to show objective results for this will put you ahead of the competition. Automated and rich data will show the awareness and preparedness that correspondents want to see in respondent banks when considering a relationship.
How to obtain better compliance data
Respondent best practices
1. Engage in regular and open communication
2. Provide timely and complete responses to all inquiries
3. Proactively identify increasing risk and notify the correspondent
4. Maintain a strong compliance program and staff
5. Provide complete and accurate information on payment instructions
(according to the BAFT’s Respondents Playbook)
And this is where Elucidate's assessment for financial crime risk comes in. Powered by the Elucidate FinCrime Index (EFI), which employs data analysis and modelling, we’ve created the world’s first regulated risk scoring system for financial crime. It leverages data analysis and machine learning to generate nine scores across a range of risk themes, providing you with a comprehensive view of your own institution’s risk, as well as your peers. Read our case study on leveraging data to understand how the quantification of financial crime risk allows for better correspondent banking relationships.