How The Law Society of BC Uses Dataiku for Risk Ranking and Anomaly Detection
Customer Company Size
Large Corporate
Region
- America
Country
- Canada
Product
- Dataiku
Tech Stack
- Predictive Analytics
- Machine Learning
- Data Visualization
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Cost Savings
Technology Category
- Analytics & Modeling - Predictive Analytics
- Analytics & Modeling - Machine Learning
Applicable Industries
- Professional Service
Applicable Functions
- Business Operation
Use Cases
- Predictive Quality Analytics
- Regulatory Compliance Monitoring
Services
- Data Science Services
About The Customer
The Law Society of British Columbia is a non-for-profit organization that regulates lawyers in British Columbia with the mandate to protect the public interest in the administration of law and to ensure independence and competence of lawyers. They also bring a voice to issues affecting the justice system and the delivery of legal services. The Law Society of BC regulates 13,000 practicing lawyers and 3,800 law firms. They cover the end to end law lifecycle, from regulation initiatives to access to justice.
The Challenge
The Law Society of British Columbia, a non-profit organization that regulates lawyers in British Columbia, was looking to increase the efficacy of their trust assurance audit program. The organization regulates 3,800 law firms and audits approximately 550 firms per year, which means that each firm is audited at least every four to six years. The Law Society has three decades of historical data, which enables them to categorize law firms according to their risk level: low, neutral, or high risk. The organization made the decision to focus on risk factors and, from there, work to adjust the audit schedule based on the risk category of each firm. The senior management team at The Law Society of BC firmly believes that AI and machine learning will play an important role in their responsibilities in the near future. They knew it was time to take advantage of their collected data and leverage technology to identify patterns and behaviors and increase effectiveness and efficiencies within Law Society programs.
The Solution
The Law Society of BC evaluated a myriad of data science and machine learning platforms and ultimately chose Dataiku. The Law Society uses Dataiku to support proactive regulation of law firms. The trust audit program has the overall goal of being an effective and efficient program that helps ensure lawyers handle trust funds appropriately, and Dataiku helps identify risk factors for law firms. The Law Society uses predictive analytics in Dataiku to understand which factors contribute to a firm being a risk, such as years in business, the lawyers’ average years of practice, the number of complaints and hearings, the last trust audit score, and so on. Using Dataiku, they predict the probability of a firm’s risk from a compliance perspective, identifying the firms with high, low, and neutral risk factors according to their background and history. Upon identifying firms that fall under the high risk category, the Law Society then asks the firm for books and records to detect and analyze anomalies further using audit procedures and algorithms.
Operational Impact
Quantitative Benefit
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