ADJD leverages judicial insights to transform the justice delivery process

ADJD leads AI-driven government innovation with SAS Analytics Platform

Judicial systems worldwide are an epitome of an increasingly intricate data environment. The massive volume of structured and unstructured data collected through innumerable case types, spanning from civil to criminal case types along with thousands of digital touch points across various courts and channels, makes the judiciary a complex ecosystem.

Established in 2007, under the Chairmanship of His Highness Sheikh Mansour Bin Zayed Al Nahyan, ADJD is today a global trailblazer when it comes to data driven innovation within the justice system.

As part of their journey towards artificial intelligence (AI), ADJD has constantly been on the look out to unlock value from its trove of data assets. To this end, in a journey that commenced 4 years ago, ADJD, initiated a project that aimed at developing capabilities to deliver visibility and apply analytics to its extensive data reserve, in conjunction with SAS.

Setting the wheels in motion

The foundation was set in 2014, with a program titled “The Briefing Room” project. ADJD selected SAS Visual Analytics coupled with SAS Data Management, a solution that enabled ADJD to discover and explore all their data spread across over 40 data sources. With SAS, ADJD could uncovered new patterns in their business delivered through rich visuals. More importantly, they could gain insights using automated analysis.

SAS solutions were a tool to help the department augment its reporting process with rapid data discovery, explains Khawla Al Qubaisi, director, Information Technology, Abu Dhabi Judicial Department.


To sum it up, these solutions by SAS has helped us develop a world-class Judicial data platform that helps us identify our customers, cases and transactions and the relationships with a high degree of accuracy; and process the requests for insights and information in “timely manner” Khawla Al Qubaisi Director, Information Technology Abu Dhabi Judicial Department

While organizations struggle with applying first generation data analytics on structured data, ADJD’s multi-year program with SAS has past this stage and is today tackling the new frontier of unravelling value from its unstructured data.

Setting a benchmark with the success of this data analytics phase, ADJD and SAS set about implementing a unified data management platform around its complex data sources, an initiative that culminated in the implementation of SAS Master Data Management (MDM) solution, with an objective of having a unified and reliable data source.

Advancing on the Digital Transformation Roadmap

The cornerstone of a successful digital transformation journey is a strong and scalable data platform. Judicial Data stored in multiple databases is useless unless integrated and easily accessible for the decision-makers.

The challenge at the beginning of this engagement was that the ADJD data were in silos. All this massively valuable judicial data had to be extracted, standardized, transformed and loaded into a common unified repository that could lay the foundation for reporting or advanced analytics.

With SAS, ADJD built a data warehouse for all its core systems. This platform provided its business units with access to their specific data and enabled them to generate their operational reports, insights and visualizations on their data, and ultimately make more informed and data-driven decisions using SAS Visual Analytics. “Furthermore, the tools will be used by top management to visualize and discuss decisions based on reliable data and analysis,” explains Al Qubaisi.

With data amassing increasing importance globally, successful government-citizen engagement comes down to the availability of high-quality, well-integrated data and not only on digital touch points. Any AI-driven analytics project starts with data; having the right quality data is very important for a machine to be able to predict the probability of future events or scenarios, and building a scalable and extendible data ecosystem was a critical business need to help drive future data-driven innovations.

Reaping the benefits of AI 

AI is evolving from a trend to an actual enabler of seamless business transformation, however the foundations of this lie in developing a data management strategy, and spans the full analytics lifecycle. ADJD fully understood that analytics is not as project, but a multi-year transformation program that starts with developing a data management strategy.

Based on certain real business challenges faced by ADJD around case analysis & consistency of judgements, an AI & Machine Learning approach was presented to ADJD last year at a regional SAS summit and ADJD then invited the SAS team to undertake a pilot to prove the concept. “We were very happy with the trial results. All the data requirements to implement machine learning was already available in our data platform foundation developed by SAS, which made the implementation and production transition easier,” explains Al Qubaisi.

ADJD then got into working on cross-reference analysis where data from different systems will be correlated and analyzed; including ADJD operations, social and economic trends identified based on the department’s services, ultimately benefitting the Abu Dhabi government as a whole and not only ADJD, Al Qubaisi explains.

The department is also using the SAS-generated analytics across the business. “Our plan is to eventually implement SAS’s solutions across all the businesses and eventually replace all the older systems all in the future,” she adds.

We have been able to tap into the massive reserves of data about individuals that is collected by the judicial department, help them analyze that to be able to understand certain trends and insights into things like criminal behavior and civilian case behavior, a one of kind use case in the region Alaa Youssef Managing Director SAS Middle East

The journey with SAS

The SAS engagement over the past four years was phased out in three main phases: Phase one is based on creating visualizations, which involves viewing operational performance of the organization, gaining performance insights and ad-hoc analysis. Phase two involves the more complex data governance, which entails improving data quality, and producing a single customer data record or master data management – eventually, data synchronizations. The Third phase is the application of AI & Machine Learning models on real-world business challenges within the Judicial System starting with case analysis, involving case relationship discovery, case summarization and identifying and predicting certain case trends.

The solution is delivering on set objectives, says Al Qubaisi. “The main aim is to eventually integrate all the reporting processes and involve all the business departments so we can deploy SAS’s solutions across the organization; this will happen only when all the business departments are involved in the process,” she adds.

For SAS, a key value proposition is the leveraging of artificial intelligence for evidence-based government policy and decision making. With ADJD, the goal was to reduce their time to decision-making by leveraging the AI capabilities of SAS.

Alaa Youssef, Managing Director, SAS Middle East says SAS is proud of the work with ADJD which goes beyond business intelligence, to applying machine learning and AI models to help to augment and support the judicial leadership. “We have been able to tap into the massive reserves of data about individuals that is collected by the judicial department, help them analyze that to be able to understand certain trends and insights into things like criminal behavior and civilian case behavior, a one of kind use case in the region,” says Youssef.

“We are thus leveraging historical data using AI to detect the future,” he adds.
“Artificial intelligence has evolved from the hubris of big data strategy discussions, which failed to live to its billing. Big data however provided the stepping stone to AI, because it’s impossible to build AI capabilities without having the facility to process huge amounts of data”, Alaa Youssef observes.

One of the most important use cases for AI is augmenting the human effort. “The system will intelligently sort through these cases and automatically guide them to the respective channel. All this happens in the backend, which reduces a lot of effort within the ecosystem in terms of the number of people needed to process or manage a case,” Youssef adds.

“The ultimate success of the project will be when we succeed in producing a single complete view of the entire judicial ecosystem for our business units. We initially had to provide different reports on our customers, but now we can provide one solicited ‘golden’ dashboard which consists of all required information. To sum it up, these solutions by SAS has helped us develop a world-class Judicial data platform that helps us identify our customers, cases and transactions and the relationships with a high degree of accuracy; and process the requests for insights and information in “ timely manner”, Al Qubaisi adds.

The ADJD project was never a ‘tick-a-box’, kind of implementation, says Youssef. “The application of ML that we have applied has a direct reflection on the consistency and quality of judgments. This is the crux of what we are trying to do – to align any data initiatives to the strategy initiatives of the organization,” Youssef concludes.
 

Challenge

ADJD wanted to gain more insights on its judicial ecosystem spanning the entire breadth of civil to criminal cases, related data and enable more informed decision-making.

Solutions Deployed

SAS Data Management
SAS Visual Analytics
SAS Advanced Analytics

Benefits:

  • Ability to explore new patterns across 40 data sources through rich visuals to gain business insights
  • Ensure data quality & consistency
  • AI driven automated case analysis for optimizing judicial services
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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