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Case Study: Creditas cuts compliance risk 93% and lifts efficiency 27% with Deepgram

Creditas Case StudySourced & dated by Case Study Desk
Key facts · TL;DR
Company
Creditas
Industry
Financial Services
Challenge
Manual QA monitored under 10% of collections calls
Headline result
Creditas rebuilt Indian debt collections on Deepgram speech-to-text, reporting a 93% compliance-risk reduction and a 27% operational-efficiency lift.

Key results

93%
Compliance risk reduction
27%
Operational efficiency lift
2-3×
Higher engagement rates
post-Deepgram
10%
Revenue uplift
AI payment-intent prediction

The challenge

Creditas, an Indian digital debt-collections platform, relied on manual, scripted calls and QA processes that monitored less than 10% of interactions, leaving compliance and quality gaps in a heavily regulated market. Agents' code-mixed Hindi-English conversations were missed entirely by traditional QA.

The solution

Creditas deployed Deepgram's Nova speech-to-text models tuned for finance, phone calls, and multilingual Hindi-English collections through a self-hosted, in-region AWS deployment to meet accuracy, privacy, and compliance requirements.

The results, in context

Creditas reports 100% call-audit automation with every call transcribed and quality-audited in real time. It documents a 93% compliance-risk reduction, a 27% operational-efficiency lift, 2-3x higher engagement rates, and a 10% revenue uplift from AI payment-intent prediction.

Products used

Deepgram Deepgram NovaDeepgram Speech-to-Text API