Sayint Review

Use Case 1: PCI Redaction

Problem: It is very important for contact centers to protect the sensitive and confidential information like debit and credit card information, keeping customer privacy and compliance rules in mind. The power of redacting PCI-protected information from call center recordings and their transcripts helps organizations protect sensitive information. However, there are many organizations which fail to do so.

Solution: Sayint’s conversational analytics helps organizations to exercise better control over the call recordings by automatically redacting sensitive information based on company policies and compliance requirements.

Example: Any business that deals with credit card information over the phone have to follow PCI rules to avoid making customer credit card information readily available to employees. Sayint conversational analytics solution will redact sensitive information. This allows businesses to do away with the need to store this kind of sensitive information on their enterprise networks. At the end of the day, it’s a safeguard against potential litigation.

Use Case 2: Improved Agent Efficiency

Problem: Large-scale banking contact centers typically address multiple challenges and try to resolve them through a measurable improvement process. These are the most common areas seeking continuous improvement across:

• Reducing call times,
• Improving agent efficiency,
• Enhancing customer satisfaction level,
• Resolving customer issues on the first call/Improving first call resolution rate, and
• Improving sales performance and driving down costs.

Solution: In order to improve the operations of contact centers, organizations can start with categorizing calls and filtering them based on which they can develop standardized training programs.

Example: Sayint’s conversational analytics ranks agent performance. If you replace the bottom-performing 10 percent of your agents every three months and hire better performers, you can make major improvements in your contact center in a short span of time.

Use Case 3: Reduce Fraud

Problem: Fraud is one of the biggest risks that businesses are facing these days. With stringent steps being taken on cybersecurity front, fraudsters are changing their mode of fraud from online to telephone. As per Pindrop lab’s 2017 Call Centre Fraud Report, 1 in every 937 calls are of fraudulent nature which is an alarming number.

Solution: With the help of Sayint’s Conversational Analytics tool, you can detect fraud by setting rules to spot fraudulent behavior, conversations, and also identify if a caller is lying. This will help you take the correct risk mitigation steps.

Example: You can identify fraud callers with the help of keywords. You can examine the data and trends to decide which keywords and phrases you can use to create alerts for. You can also create a system to flag the caller who has called you more than the number of times he/she should have in a defined number of days.