How to design an app that unstresses debt collection agents by 50%?
Insurance companies, banks, and telecoms have a lot of customers with outstanding payments. To collect them, a single consultant makes 100 repetitive calls a day and takes notes of each of them.
The problem with manual debt collection is that it takes time and is burdened with huge employee rotation, caused by high stress levels and lack of work variety. As a result, it contributes to the significant cost of ongoing recruitment and training for companies.
Lekta, a startup that builds NLP-based solutions for enterprises, used semi-automatic voice bots to boost the process of debt collection. The next step was to move towards full automation via a new SaaS platform Lekta clients would use to collect debts and report results automatically, saving 30-50% of call centre costs.
To address the challenges, we started with a product design service to transform a general product vision into a development roadmap. Then, our development team took over and built the MVP in only 4 months.
What was the challenge?
Product design sets the foundation for innovative SaaS products.
To address the challenges, we started with a product design service to transform a general product vision into a development roadmap. Then, our development team took over and built the MVP in only 4 months.
To lay a solid foundation for the solution, we started with a product design workshop that comprised several strategic meetings about the vision and the assumptions of the project. A key player in the game was a Lekta representative who knew how the app would be used.
After presenting the roadmap to Lekta’s technical board, we received a green light to move to the software development phase.
For the next several weeks, we created a project roadmap (strategic plan with milestones and goals for the next 6 months), followed by a set of user stories, and an architecture scheme.
Iterative work kept Lekta informed due to fortnightly demonstrations of our work.
The application’s MVP was ready after 4 months of work.
To lay a solid foundation for the solution, we started with a product design workshop that comprised several strategic meetings about the vision and the assumptions of the project. A key player in the game was a Lekta representative who knew how the app would be used.
For the next several weeks, we created a project roadmap (strategic plan with milestones and goals for the next 6 months), followed by a set of user stories, and an architecture scheme.
After presenting the roadmap to Lekta’s technical board, we received a green light to move to the software development phase.
Iterative work kept Lekta informed due to fortnightly demonstrations of our work.
The application’s MVP was ready after 4 months of work.
Every client can use the platform after onboarding and setting up the debt collection strategy.
Once the debtor’s data is uploaded, clients can start a debt collection campaign.
The system records and analyses all conversations, providing management with clear reports.
Fully automated debt collection process every company can set up on their own.
cost reduction
availability
of data collected and analysed
stress reduction among consultants
cost reduction
of data collected and analysed
stress reduction among consultants
availability
Technology stack
This was something! The number of integrations was impressive, which impacted the architecture a lot. To me, it was also a great chance to see how AI models can be used to foster innovation and cut down the cost and operations time in business.
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