Ten years ago, automated transcription was relatively uncommon in financial services. Limited accuracy would mean that it was difficult to derive efficiency gains or rely on the end transcript for anything meaningful.
Typically, the words that wouldn’t be documented accurately would be the key industry-specific terminology you needed the most, which limited the value of the transcript.
Times have changed considerably since then. AI-driven transcription tools now offer comparable levels of accuracy to a human but with the added speed and consistency of a machine. This new wave of technology is providing unprecedented opportunities to the financial services sector that go much further than the efficiency gains first envisaged.
How it works
Automated transcription is the process of converting audio into a written format using voice and speech recognition technology. These tools use a specific branch of AI called natural language processing that is designed to deal with interactions between computers and the human natural language. This goes further than simply matching a word to the corresponding sound from an extensive dictionary of words: the technology also understands the context of each word within the sentence and wider conversation to increase the level of accuracy.
Modern transcription tools read, decipher and understand the language being used to make sense of human languages in a similar way to how the human brain makes sense of them. When machine learning software is fed more datasets, it gains more experience and builds a stronger, more multi-faceted algorithm, leading to an increased level of accuracy. So, the more it is used, the smarter it gets.
Key use cases
1. Driving efficiencies
Automatically transcribing a conversation is obviously much less labour intensive than recording the information manually, but many of the efficiency gains actually come further downstream. Having the information to hand makes conducting follow up activities much swifter, even from simple sounding things like having all the data you need at your fingertips, the ability to search for a keyword without needing to go through a stack of notes or being able to copy and paste key parts of the dialogue instead of typing them out manually.
2. Improving compliance
3. Boosting customer experience
4. Increasing transparency
5. The foundation for future analytics
Transcribing conversations through AI leverages data in a format that other analytics and automation tools can utilise. These become a source of valuable data for more advanced analytical insights and business process improvements including both historic data in past business reviews or daily business-as-usual activities.
Considerations
Accuracy – Automated transcriptions are only beneficial if they are accurate, otherwise, additional time is spent rectifying the mistakes. It is integral to use an industry-specific tool that is trained on the specific language used within your sector. Our Capture solution is built to work with compliance and financial services, tackling highly specialised languages and the specific nuances used in the industry. To increase accuracy further, the software has also been trained on various dialects and accents. This is why our knowledge model with six years’ worth of data from real-life conversations in financial services is so important in the work we do.
Security – When dealing with such sensitive information that is discussed in client meetings you need to be sure the transcriptions and any records are being stored securely. Recordings made on our software is encrypted at every part of the process, from the device to our cloud-based secure storage. If cloud-based is not an option, we also offer military-grade storage in our data centres.
If you would like to gain further understanding of how we help firms record, store, transcribe and review customer interactions then get in touch.
