Industry
Digital banking
Use Cases
Credit data
Automation
About
tbi bank is a mobile-first digital bank in South-East Europe and regional leader in alternative payment solutions. It focuses on helping merchants grow their business as well as providing consumers with financial products and services that make their lives easier. Currently operating in Romania, Bulgaria, Greece, Germany, and Lithuania. Through trusted partnerships with nearly 20,000 merchant locations, tbi has a customer base of 2 million clients and issued nearly 550,000 loans in 2022. Its business model and customer-focused approach resulted in becoming one of the most profitable and efficient banks in the region.
Before SEON
With SEON
The Challenge
In the banking and fintech industry, managing financial risk is a complex and multifaceted challenge. Among the most significant concerns are fraud risk and credit risk—two areas that can have profound implications for a bank’s profitability and customer trust. For tbi bank, a leading institution in its region, finding an effective way to predict and mitigate these risks was crucial to maintaining a competitive edge and ensuring sustainable growth.
They may seem like distinct and seperate risks, but there is a thin line between them. In fact, managing one risk can often have an impact on the other. In this context, understanding the difference betweem fraud risk amd credit risk, as well as the interplay between the,. is crucial for effective risk management in the financial industry.
Costin Mincovici
Chiefg Credit Officer at tbi
The Solution
To address these challenges, tbi bank turned to SEON’s advanced fraud prevention and risk management tools, focusing on digital footprinting technology. This technology scans a wide array of digital and social platforms, collecting data points that provide deeper insights into a customer’s digital presence, providing a strong signal for onbaording
With SEON’s assistance, tbi bank was able to simulate and model the performance and behavior of its customers more accurately. By using the data collected through SEON, particularly from digital and social sites, tbi bank enhanced its machine learning score models to better predict customer performance and manage credit risk.
Allow rapid decision making for a frictionless onboarding experience. Leaving your team more time to help your Neobank grow.
The Results
The impact of this enhanced modeling was substantial. By improving their machine learning models, tbi bank saw a 5 percent increase in customer approval rates. This significant improvement allowed the bank to onboard new customers more rapidly and efficiently.
This boost in approval rates didn’t just streamline the onboarding process; it also had a direct positive impact on tbi bank’s bottom line. With more accurate risk assessment and a smoother customer journey, the bank was able to expand its customer base and increase revenue streams while effectively managing credit risk.
Moreover, by focusing on alternative data sources, including digital and social footprints, tbi bank gained deeper insights into customer behavior and preferences without relying on potentially sensitive or biased demographic information. This approach not only improved the accuracy of credit risk assessments but also enhanced the overall customer experience, fostering greater trust and satisfaction among clients.
5%
Improved customer onboarding approval rates
Improved
The customer journey for good customers
Conclusion
By leveraging SEON’s advanced analytics and data-driven insights, including their digital footprinting technology, tbi bank successfully expanded its customer base while effectively managing credit risk. The result was a significant return on investment for the bank, showcasing the value of innovative risk management strategies in today’s competitive financial landscape.
For more information about tbi bank, visit www.tbibank.bg