How HMRC is using data to reduce risk for the UK’s COVID-19 schemes

Profile picture for user ddpreez By Derek du Preez June 16, 2020
Summary:
The government announced its ambitious Job Retention Scheme in response to COVID-19. HMRC is responsible for the systems supporting it.

Image of a person at work wearing a face mask to protect against COVID-19
(Image by Engin Akyurt from Pixabay )

When the realities of COVID-19 finally took hold for the British government back in March, one of the first responses from the Treasury was to introduce a Job Retention Scheme - which effectively allows employers to furlough unproductive staff during the pandemic, paying up to 80% of their salaries (to a point). The hope is that when the economy begins to pick up again, those employees will be able to transition seamlessly back into the workforce, without having to face unemployment.

The scheme has already seen over 9 million people supported via furlough, costing the state over £20 billion.

One of the government departments that has been responsible for creating and implementing the Job Retention Scheme is HMRC - the UK's tax department. This week, as part of SAS' Global Forum digital event, CIO of HMRC's Customer Compliance Group, Tim East, shared some of how the department is using data to help reduce the risks associated with the scheme. He also shared some learnings on collaborative teamwork throughout the process.

East said that the longstanding agenda within the department and the group is to figure out how to work with customers to promote voluntary compliance, but when non-compliance does happen, to respond effectively. This is particularly true for the COVID-19 government-backed schemes, which had to be established in incredibly short timeframes.

Prior to COVID-19 hitting the UK, HMRC had been working on upgrading its ‘Connect' service, which was focused on updating its ageing graph database technologies to support compliance and risk assessment. East explained:

The idea of the original Connect service is that we used graph database technologies behind the scenes to build a social network to run models against. But it's quite old now. And there are lots of constraints. Non-functional requirements are no longer good enough. The volume of work that we do electronically. The user experience isn't great. The OS it's based on is quite old now.

So we took the decision that we needed to invest in modern technology - and that's why we are going down the SAS Investigation and Detection route - as part of the replacement platform. We have been working that through now for the last 18 months, through a process of building accelerators. And we had just got to the point that we had constructed our production environment in the cloud and we were beginning to ingest data ready for the construction of the replacement graph database. And starting to test the social network. And then COVID-19 happened…

A new reality

As noted above, the Job Retention Scheme focuses on using the Pay as You Earn (PAYE) network of employers to, instead of take money in, distribute money out to those that qualify. East said that the creation of the systems to support the scheme took three to four weeks, end to end.

When considering risk and compliance, East said:

Some of the key challenges for us were really around aligning the front end purpose of the system, making it an easy to use system for employers to claim, with the compliance need. Like any organisation that pays out money we do see our fair share of attacks, particularly from organised crime. What we wanted to make sure was that we did the best possible job in terms of making sure that we got money quickly to employers, whilst also making sure we protect ourselves against organised crime, fraud and other forms of high value fraud.

However, East added that those two things aren't necessarily compatible - stating that trying to work out where to interrupt the processes, how you orchestrate the IT to do that, is no small ask. For HMRC, data quality is also a huge challenge. He said:

Bear in mind that many employers weren't operating from their normal offices either. So the people who run the payroll would have been working at home, as well as all of our staff who built these schemes. That meant that we were much less strict than we would normally be about things such as data schemas. So we enabled quite a broad range of file formats for people to submit data to us - that brings its own challenges in terms of ingestion problems, compatibility problems. Those have been some of the biggest challenges we have faced.

And of course, time. Getting this through did require a huge collaborative process within business - to understand policy, understand processes, understand resourcing demands. And then folk in the IT community, folk in our own organisation, but also with our partners like SAS, working together to make it all work.

East explained that HMRC has also been able to use data that the department already holds on those looking to abuse the system to help reduce risk. He said:

As you would expect we already hold a fair amount of data about bad actors. We know what the indicators are of hijacked accounts, for example. We are also able to use known good data, particularly about bank accounts, to help us work out if we are paying a legitimate organisation or an illegitimate one. We also used some of the data we already held about the operation of PAYE to really help with the eligibility criteria, making sure that people were following the rules.

People, teams and collaboration

East said that despite the technical challenges, some of the key learnings have been about how teams work together, the roles of certain groups and the importance of having an established data profession in place to mobilise quickly. For instance, East said:

The most positive thing that we learned was the need to make sure that it is a fully collaborative effort and that we make sure that we have the right mix in the team - policy, design, IT - to make sure it works. We got a huge amount of value from our business analysts, in particular. Because they were the ones that sat down and really thought about what the policy intent was, how we wanted to implement it - and wrote it down in the form of user and system journeys. That synthesis between user journeys, system journeys, was really important to understand. I can't really emphasise enough how much value came from that approach because it did speed up the whole development and deployment lifecycle.

And on HMRC's data engineering and data science profession - something that the government has prioritised in recent years in building up - East said:

What I would draw out is that the establishment really has a data engineering and data science profession - we have probably got 400 people in HMRC that we would say are at the forefront of data science. We couldn't have done this job without them. Particularly in working through, how do we target these schemes to make sure that we have got the help to where it was most needed? We really needed that analytical skill set to work with our data up front, in the conception of the schemes.

Finally, in terms of what has been learnt throughout the process, East said that HMRC has found that distributed workforces using digital collaboration tools has actually resulted in teams being more productive. And it is something that will likely stay. He said:

What I think is interesting, what we've learnt is that with people largely working from home, we found that collaboration has become much more structured between people. The other thing that we've found is that [working virtually] has been a great leveller - it's actually meant that we've made everyone productive.