1. Capture customer tax data the first time, every time
Customer onboarding is pivotal when it comes to both accurate tax reporting and creating positive customer experiences. If organizations can get it right at this critical juncture, a firm foundation can be laid for future success.
Often, the process is imperfect because institutions repeat the same questions for the purpose of complying with a number of overlapping tax and regulatory obligations.
“Historically, tax information requests have often been regarded as a nuisance by the customer,” says Abi Jeffreys, Director, Financial Services, Ernst & Young LLP. “They don’t necessarily appreciate why institutions need this data. It can feel like an ancillary request, and even an intrusion — so asking the same questions multiple times can really annoy the customer.”
“The solution is to only ask for information needed to achieve compliance, only ask the question once, explain why this information is needed, and outline the customer benefits of providing it.”
Language is another major factor that can complicate the gathering of tax information. US-based Internal Revenue Service (IRS) forms, such as the W-8 in particular, are couched in technical legalese, which clients may not immediately understand – and this is compounded if the customer is not a native speaker.
Jeffreys advises that organizations looking to simplify the onboarding process will need to tailor the questions to make them as straightforward as possible for the majority of their customer base – and make additional queries when cases are more complex.
The risk of not capturing the required information the first time, every time, is that businesses may need to engage in a protracted remediation process to fix issues further down the road.
“From a client perspective, that is not an optimal customer journey,” Jeffreys says. “It often involves contacting the customer multiple times to clarify information and ask for additional data, which should have been captured accurately upfront.”
The ultimate risk is that an institution may report the wrong details to a tax authority. David Jensen, Principal, Financial Services, Ernst & Young LLP, says, “This may trigger an unnecessary audit or an unwarranted request for tax. Tax reporting errors and omissions can seriously damage customer experience, but if the root causes are systemic rather than one-off, they can also cause significant reputational damage for a financial institution.”
2. Harness the right technology to automate and improve your customer onboarding processes
Large financial institutions often onboard and gather tax details from thousands of clients every single day. Faced with a data challenge of this scale and magnitude, technology has a clear role to play.
There is already a steady growth of digital onboarding channels within the financial services sector, and all the signs suggest that this trend could be replicated for tax information gathering. In fact, there’s a strong case for integrating tax data capture within existing digital Know Your Customer (KYC) and anti-money laundering (AML) data capture systems.
For the time being, at least, many institutions still require customers to complete paper Foreign Account Tax Compliance Act (FATCA) and Common Reporting Standard (CRS) forms. These are manually reviewed some days later by a back-office individual who must contact and remediate any issues with the customer.
There are many risks inherent in this process: the relevant forms may not be collected or completed; the wrong information may be submitted by the customer; the reviewer may type the information into their system incorrectly, and the subsequent manual review process may also be carried out incorrectly.
With digital onboarding, however, systems exist that offer customers a set list of compliant answers, which can be validated by the system in real time and any issues flagged up and resolved immediately. This proscriptive approach significantly drives up accuracy rates and completeness of information.
Real-time checks enable the customer to access their financial product quicker. They also unlock significant efficiencies for the institution, which no longer has to devote precious resources to a potentially lengthy data remediation cycle. So both sides benefit.
Organizations might think that moving to digital is complex, but the existence of third-party digital onboarding solutions are leading an increasing number of clients to choose outsourcing. One of the key benefits being that they can be fully branded and seamlessly integrated with institutions’ existing customer-facing systems — such as internet banking websites and apps.
Organizations that achieve points one and two are well on the way to being fully compliant. But what differentiates an adequate process from a “gold standard” one? Two additional steps allow businesses to optimize the data they collect.
3. Use data analytics to engender high levels of data trust
Low-trust data, especially in risk-averse organizations, can often lead to a culture of over-reporting. Low-trust data occurs when institutions can’t sufficiently validate information, are unsure of provenance or don’t know the extent to which data has been manipulated by other systems or processes. This can lead to institutions unnecessarily reporting their clients to tax authorities, and audits that aren’t actually needed, which can significantly erode customer trust.
The solution, according to Anish Benara, Partner, Financial Services, Ernst & Young Tax Services Limited, is to interrogate data at strategic points throughout the data collection and analysis process in order to prove accuracy.
Benara says that by inserting data analytic “tollgates” throughout the process, institutions can isolate and stress test data — slicing and dicing information, analyzing and filtering it to prove its veracity. The last check, says Benara, should be to subject customer tax data to the same tests that tax authorities employ and only when it passes this stage should tax data be submitted.
4. Begin building a tax data pipeline capable of tracking the full customer life cycle
The most effective way to balance customer experience and customer tax reporting is to ensure a single record of customer data follows them as they engage with multiple departments, purchase various products across numerous jurisdictions, and do so over an extended time period.
This data continuum ensures customers need only share their details once (unless they have a change of circumstances). It also reduces the risk of capturing incorrect or contradictory information and the need for a resource-hungry remediation cycle.
Building such a tax data pipeline may be relatively straightforward for digital disruptors. Incumbent financial institutions, however — especially those that have grown due to merger and acquisition activity — are likely to find this approach complex and potentially prohibitively expensive. That’s because data is likely to be stored in multiple, siloed and disconnected legacy systems, which are unable to exchange data quickly or easily.
The conventional way to overcome the legacy system challenge is to build a central data repository. Only when this is complete is it possible to achieve a single view of customers’ tax information.
Emerging architectures, such as data fabric and the semantic consumption of data, however, aim to overcome this challenge of siloed systems, giving institutions a single real-time view of the truth without needing to replicate, lift and shift huge amounts of customer information to a custom-made data lake or warehouse.
Data fabric can also be used alongside AI-driven data auto-discovery, which is increasingly capable of automatically identifying the most reliable sources of customer tax data, wherever it may be within an institution.
When institutions achieve a single view of customer data they can then use the same information for a wide range of purposes, from tax reporting, regulatory and financial reporting to auditing and data analytics.
“This is a challenge that many banks are working on right now,” says Benara. “There are many large global banks that historically have issues with data quality. Individual business lines find and fix issues with AML, KYC, FATCA and CRS data independently — teams are working in silos. Until institutions begin to create a data continuum, these issues and inefficiencies will continue.”