Unlock the potential of AI with quality data

The power of artificial intelligence (AI) is proving transformative in the public sector, from enhancing data-driven insight and productivity, to improving fraud detection and the user experience.

However, there are issues when inaccurate user data is fed into AI tools. It could result in gibberish, or worse, biased and inaccurate outcomes. This is commonly called AI induced ‘hallucinations’, which delivers poor results.

Data degrades rapidly

Quickly deteriorating data quality is a significant issue, with user contact data lacking regular intervention degrading at 25 per cent a year as people move home, die and get divorced. Then there are errors at data entry, with 20 per cent of addresses entered online containing errors; these include spelling mistakes, wrong house numbers, and incorrect postcodes.

The best way to avoid this, and maximise your AI efforts, is to have data verification processes in place at the point of data capture, and when cleaning held data in batch. All that’s required is simple and cost-effective changes to the data quality process.

Obtain address lookup technology

Address lookup or autocomplete services are valuable pieces of technology to use at the user onboarding stage. They provide accurate address data in real-time when onboarding by delivering a properly formatted, correct address when the user starts inputting theirs. Utilising such tools reduces the number of keystrokes required, by up to 81 per cent, when typing an address. As a result, the entire onboarding process is speeded up, reducing the probability of the user not completing an application to access a service, for example. This approach to first point of contact verification can also be extended to email and phone, so verification of these important contact data channels can take place real-time.

Undertake data deduplication

Deduplicating databases is important with many having duplicate rates of 10 to 30 per cent. It’s a big issue and often occurs when two departments merge their data and errors in contact data collection take place at different touchpoints. Whilst potentially confusing an AI application, duplication also adds cost in terms of time and money, particularly with printed communications. Furthermore, it negatively impacts on the sender’s reputation. Obtaining an advanced fuzzy matching tool to deduplicate data can help. By employing such a service, it’s possible to merge and purge the most challenging records and create a ‘single user record’ which delivers an optimum single citizen or customer view (SCV) that AI can make learnings from.

Commence data cleansing

Carry out data cleansing to highlight people who have moved or are no longer at the address on file. It’s a vital element of the data cleaning process, and therefore in supporting efforts with AI. As well as removing incorrect addresses, these services can include deceased flagging to prevent the distribution of mail and other communications to those who have passed away, which can cause distress to their friends and relatives. By utilising suppression strategies those in the public sector can save money, protect their reputations, avoid fraud and aid their AI activity.

Data cleaning SaaS platform

It has never been easier or more cost-effective to deliver data quality in real-time to support AI and wider organisational efficiencies. It’s possible to obtain a scalable data cleaning software-as-a-service (SaaS) platform that doesn’t require any coding, integration, or training. Such technology cleanses and corrects names, addresses, email addresses, and telephone numbers worldwide. It matches records in real-time, ensuring no duplication, and offers data profiling to help source issues for further action. A single, intuitive interface provides the opportunity for data standardisation, validation, and enrichment, resulting in high-quality contact information across multiple databases. This activity can take place with held data in batch and as new data is being collected, and can also be accessed via cloud API or on-premise, if preferred.

Unlocking the potential of AI to add value, deliver efficiencies and insight, is reliant on the quality of data fed into AI tools. Inaccurate data leads to AI ‘hallucinations’ with unreliable predictions and bad outcomes. Undertaking best practice data quality procedures solves this issue and helps to maximise the success of your AI efforts.

Central Government Programme activities

The techUK Central Government Programme provides a forum for government to engage with tech suppliers. We advocate for the govtech sector, evangelise tech as a solution to public sector challenges, facilitate market engagement, and help make the public sector an easier market to operate in. Visit the programme page here.