In the ever-changing field of corporate artificial intelligence, CourtCorrect is harnessing a game-changing tool known as case-based reasoning. It is a technology that not only learns from historical data but also possesses the ability to apply that knowledge to tackle new challenges effectively. It’s the AI assistance to case handlers we’ve all been waiting for, poised to reshape how businesses adapt, problem-solve, and make crucial decisions.

Unveiling Case-Based Reasoning

The case-based reasoning that CourtCorrect has created utilises a large language model to review existing cases and precedents, and “reasons” about how they impact new cases. This allows AI to predict how cases should be decided based on past precedent rather than just telling us what has been decided.

Why does it matter?

Operations

For businesses inundated with complaints, where the onslaught of issues can feel relentless, case-based reasoning provides a beacon of hope. This AI-driven approach empowers CourtCorrect users to spot patterns and anticipate the likely outcome of the cases they're facing. It does this by drawing upon both internal and external data, even data from relevant authorities. It's not just about putting out fires; it's about using the wisdom of the past to bring systemic improvements to your complaint-handling process. Say goodbye to the days of reactive firefighting and hello to a proactive, consumer-centric strategy.

Consumer Satisfaction

But case-based reasoning goes beyond streamlining operations. It has the potential to significantly enhance customer satisfaction. When clients witness their grievances addressed promptly and accurately, they're more likely to stay loyal to your brand. In fact, effective complaint resolution can turn disgruntled customers into fervent advocates. Case-based reasoning isn't just a tool; it's a game-changer for nurturing stronger customer relationships and building a reputation for exceptional service. In an era where customer experience is the ultimate competitive edge, CourtCorrect can help you leverage it to your advantage.

How is CourtCorrect utilising case-based reasoning

Insights Tab

The CourtCorrect Insights tab boasts AI-powered predictions that offer invaluable guidance for resolving customer complaints effectively. One standout feature allows case handlers to access a repository of similar cases, helping them spot common threads and patterns. This capability is invaluable in quickly finding solutions, enabling case handlers to dive deep into the specifics of similar cases. By leveraging AI-driven predictions and exploring analogous cases, this tool not only streamlines the resolution process but also equips customer service teams with the knowledge and tools they need to provide efficient and personalised support, ultimately boosting overall customer satisfaction.

The new CourtCorrect Workflow

Let's take a peek at a snippet from an AI generated sample legal memo that a case handler would receive analysing a financial services complaint in light of precedents in this area. It reviews existing cases, compares them, and recommends compensation based on prior cases.

The sample memo analyses the case of Ms Napoli against the similar cases of Ms P and Mr S.

Features of the AI generated sample memo

Similarity between fact patterns

“This is similar to Ms P's case where the delay in transferring her holdings caused her to lose out on potential gains.”

This AI generated insight stems from an analysis of past decisions, with the AI system drawing from hundreds of cases sharing similar fact patterns. This wealth of historical data serves as a crucial resource for complaints case handlers. By tapping into this reservoir of precedent, handlers gain invaluable insights into how previous cases were resolved. It allows them to navigate current cases with a profound understanding of what has worked in the past, facilitating more accurate analyses and informed decisions, such as relying on cases similar to Mrs. P or Mr. S.

Similarity between outcomes

“The relevant authority upheld Ms P's complaint and ordered the company to compensate her for the financial loss and distress caused by the delay.”

The AI system not only informs case handlers about past case outcomes but also uses data and precedent to help them make predictions and arrive at a clear verdict regarding the likely resolution of the case.

“Based on these decisions, it is clear that the relevant authority considers delays in the transfer of ISA accounts, especially those caused by administrative errors, as a valid ground for upholding a complaint.”

Here, the case-based reasoning tool extracts key factors such as "delay" causing stress and worry as critical elements in previous rulings. It advises the complaints handler to uphold Ms. Napoli's case, as a similar case would likely be lost if escalated.

Compensation Recommendation

“In conclusion, the complaint should be upheld and Ms Napoli should be offered a total compensation of £6,219.32 plus 8% interest for her financial loss and £250 for the distress and inconvenience caused by the delay.”

This tool meticulously analyses similar cases based on their outcomes, ensuring that customers receive fair resolutions. By delivering fair outcomes based on solid precedent, it dramatically reduces the likelihood of complaints escalating to the ombudsman. This not only improves complaints efficiency but also enhances the firm's handling of the new Consumer Duty, where the number of cases referred to the ombudsman plays a pivotal role in the assessment.

In the ever-evolving landscape of AI complaints management, CourtCorrect's case-based reasoning is the transformative force businesses need to streamline operations, boost customer satisfaction, and navigate the complex world of complaint resolution with confidence.

Interested in experiencing the power of AI in your complaint handling process?

Try our platform for yourself! Request a trial here