Use cases

A Scandinavian lending company succeeds
after use of our services

Use cases

A Scandinavian lending company succeeds after use of our services

When one of the largest Scandinavian lending companies sought to expand its market share without incurring additional risk, they turned to our sophisticated data science models. Our collaborative endeavor began with an overhaul of their credit scoring system, utilizing bespoke analytics that tapped into a wellspring of historical and transactional data. The results were nothing short of transformative. The precision of our scoring models unearthed creditworthy individuals who had previously been overlooked, leading to an 8% surge in loan approval rates. This uptick was not just a quantitative triumph but also a qualitative success story of data science’s predictive power enhancing financial inclusivity.

The adoption of our Credit risk Models by this companymarked a turning point in their risk management strategy. By integrating these models, which applied advanced machine learning techniques to identify and predict customer behavior, theysaw a significant reduction in its non-performing loan (NPL) level, dropping by an impressive 15%. This decrease not only protected the bottom line but also instilled a newfound confidence among their clientele, further solidifying their position in the competitive lending market.

Furthermore, the implementation of our Tailored Limit Assignment Models played a crucial role in optimizing their revenue streams. By balancing risk and creditworthiness, these models assigned limits that were both appropriate for customers and profitable for the company. This data-driven approach to credit limit allocation contributed to an 8% revenue increase, a testament to the nuanced understanding of customer profiles that our data science models provided.

In the grand tapestry of this Swedish company’s success, each thread was interwoven with the intricate patterns of our data science methodologies. From leveraging Bank Statement Transactional Data Risk Models to enhance underwriting precision to employing Continuous Credit Portfolio Monitoring for agile responses to market dynamics, the data science models proved indispensable. They functioned not merely as tools but as the very engines of growth, driving our client towards a future where data intelligence and financial acumen converged to redefine what it meant to be a leader in the lending space.

Better decisioning in
Central Europe market

Better decisioning in Central Europe market

In the dynamic financial landscape of Poland, a local fast-growing consumer lending companyembarked on a strategic initiative to enhance their credit decision-making process. Recognizing the potential of data science to revolutionize their operations, the companypartnered with a leading provider of analytics solutions to harness the power of real-time data processing and predictive modeling.

The crux of the initiative was the integration of an advanced decision-making platform powered by sophisticated data science models. These models were meticulously designed to analyze a multitude of borrower data points, from credit history to current financial behavior, delivering comprehensive risk assessments with unprecedented speed. The result? A remarkable 12% increase in credit issuance. This acceleration was made possible by the system’s ability to provide instant credit evaluations, allowing the company to approve loans with confidence and at a pace that matched the urgency of modern consumers.

Notably, while the speed of credit issuance often comes with the trade-off of increased risk, the Polish lender maintained their non-performing loan (NPL) levels at the status quo. This feat was achieved through the meticulous calibration of risk models that continuously learned and adapted to emerging financial patterns and trends. By leveraging real-time data, the institution avoided the pitfalls of rapid scaling by ensuring that every approved loan adhered to their stringent risk appetite and compliance standards.

The success of the this lending company became a case study in the judicious application of data science within the Polish financial sector. The institution’s ability to make swift, data-backed lending decisions without compromising on loan quality set a new benchmark for operational excellence. Customers, now enjoying quicker access to credit, empowered the company to solidify its market position, while competitors looked on with keen interest at the transformative impact of data science on traditional lending practices.

Through this collaboration, one of the leading lending companies in Poland not only accelerated its growth but also highlighted the strategic importance of data science in the financial industry. Their story underscores the reality that in the age of instantaneous digital transactions, the marriage of speed and accuracy in lending is not just desirable—it is essential for those who wish to lead in the competitive world of finance.

 Customer feedback

Collaborating with Lendiscore has enabled us to develop a successful business strategy, as they provide us with advanced customer analysis based on various factors, including region, credit history, income, financial habits, and more. As our business network spans clients in diverse areas, Lendiscore’s analysis facilitates an understanding of various customer behaviours.

Girts Rudzitis

CEO of GIVEN

Thanks to Lendiscore, we are able to assess our clients’ solvency, analyze the risk, and offer them the smallest possible initial instalment. We appreciate that by providing Lendiscore with anonymized information about our clients, we receive a detailed scoring overview within just a few seconds. Therefore, we can provide our clients with swift service, allowing them to seamlessly continue with their daily agenda afterward.

Liga Emma Gulbe

CEO of Grenardi

As the founder of a new fintech company in Spain, I was faced with the immense challenge of establishing a credible and effective operation in a highly competitive market. Consultations with Lendiscore team on how to best utilise data transformed our approach, enabling us to quickly develop a sophisticated transactional data model. This model has been pivotal in accurately assessing credit risk and tailoring our products to meet the unique needs of the market. The insights gained from this partnership have not only accelerated our business setup but also positioned us strongly for future growth, thanks to a more informed and data-driven strategy.

Felipe Sanhueza

Country manager of Luzo

 Customer feedback

Collaborating with Lendiscore has enabled us to develop a successful business strategy, as they provide us with advanced customer analysis based on various factors, including region, credit history, income, financial habits, and more. As our business network spans clients in diverse areas, Lendiscore’s analysis facilitates an understanding of various customer behaviours.

Girts Rudzitis

CEO of GIVEN

Thanks to Lendiscore, we are able to assess our clients’ solvency, analyze the risk, and offer them the smallest possible initial instalment. We appreciate that by providing Lendiscore with anonymized information about our clients, we receive a detailed scoring overview within just a few seconds. Therefore, we can provide our clients with swift service, allowing them to seamlessly continue with their daily agenda afterward.

Liga Emma Gulbe

CEO of Grenardi

As the founder of a new fintech company in Spain, I was faced with the immense challenge of establishing a credible and effective operation in a highly competitive market. Consultations with Lendiscore team on how to best utilise data transformed our approach, enabling us to quickly develop a sophisticated transactional data model. This model has been pivotal in accurately assessing credit risk and tailoring our products to meet the unique needs of the market. The insights gained from this partnership have not only accelerated our business setup but also positioned us strongly for future growth, thanks to a more informed and data-driven strategy.

Felipe Sanhueza

Country manager of Luzo

Request a custom quote

Furthermore, the implementation of our Tailored Limit Assignment Models played

Request a custom quote

Furthermore, the implementation of our Tailored Limit Assignment Models played