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'Open source data is our new approach to safeguarding children'

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If you follow the news today, it’s likely you will come across a story about a child safeguarding failure.

Whether it is an abuse scandal involving a sports club, or abuse of a child by a family member known to social services, incidents of this nature are sadly never far from the news.

Not only can they be devastating to those concerned, they can also be extremely damaging to local authorities. In part due to changing statutory responsibilities, councils are spending ever-increasing portions of their budgets on children’s safeguarding. With the ongoing squeeze on public spending, this is putting them under significant financial strain.

For a long time there has been a view that it’s impossible to predict where and when a safeguarding incident will occur. But that mindset could be about to change, as local authorities and other agencies develop a better understanding of how predictive analytics and artificial intelligence could be applied to safeguarding.

Artificial intelligence can make it easier for organisations to collate and analyse large datasets.

Zurich believes that by using AI to analyse and interpret large volumes of publicly available, open source safeguarding data – including reports from social services departments, Ofsted and other inspection bodies, as well as insurance claims data – it should be possible to build a clearer picture of safeguarding risks, and perhaps even to identify where claims are most likely to occur.

The greatest rewards of using AI and predictive analytics will be realised when insurers, councils and other safeguarding agencies work collaboratively – and when they truly understand the value of sharing certain types of data.

We are convinced of the potential benefits of using open source data to build a clearer understanding of safeguarding risks.

We have partnered with safeguarding experts Ineqe Group to develop a safeguarding dashboard, which incorporates several datasets – including rates of staff turnover within social services departments and the size of social worker caseloads – and uses this information to help local authorities understand how different factors could influence the likelihood of a safeguarding claim occurring.

Predicting when abuse will occur is a significant challenge. But we are keen to work with local authorities to explore how we can make this possible, for safeguarding issues of all kinds, which are both devastating to individuals and burdensome to local authorities already under a great deal of strain.

Andrew Jepp, managing director, Zurich Municipal

Column sponsored and supplied by Zurich Municipal

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