One such innovative product is Sales Optimizer, which is helping banks overcome the Catch 22 of the lending business, namely, how to meet sales and profit targets while upholding risk appetite. The modularity and scalability of this cloud-native solution makes the onboarding process fast and efficient, allowing banks and their customers to benefit from the solution from day one.
It is simple economics; the higher the interest rate, the higher the potential profit margins. However, with that comes lower sales volumes as loanees choose competitors. The same applies to credit risk appetite. The stricter the credit policy, the smaller the credit losses but, at the same time, sales suffer due to low credit approval rates. In the language of mathematics, the bank faces a multidimensional optimization problem with several variables affecting each other. Yet another challenge is customer churn driven by the growth of aggressive competitors in ever more crowded market.
The foundation of Sales Optimizer lies in the lending business triangle
Many banks struggle to find the optimal trade-off between sales volume, profit margin, and credit risk appetite. It is critical for businesses to grow, but not at the expense of squeezed profit margins. For banks, it’s even more acute as, in addition to the “traditional” costs of a normal business ecosystem, banks are tied to credit losses and Basel accords which define capital requirements and impact the profitability of invested capital. This poses a considerable challenge for the human (brain) but presents a vast opportunity for AI.
Sales Optimizer combines business domain knowledge, cutting-edge cloud-native technology and the latest academic data science research. Advanced mathematical modelling enables it to overcome the multidimensional optimization issue and deliver smart portfolio optimization. Additionally, modern machine learning appraises the portfolio on a quantitative, customer-by-customer basis, defining price elasticity level, and estimating churn and credit risk probabilities, among other things. These unique capabilities make Sales Optimizer a business critical tool for banks that wish to grow market share while maximizing return on equity.
Sales Optimizer analyzes potential profitability levels based on your sales targets and the current market conditions, and suggests the most profitable way for you to reach your sales targets. To do this, it applies an individualized price elasticity principle, in the form of a dynamic pricing model that ensures your target audience receives the best deals, while minimizing the bank’s credit risks.
In today’s uncertain times, we need to look to innovative technology to meet the needs of customers, uphold banks’ profitability and help drive the economy forward. Tools such as Sales Optimizer do just that. As more banks onboard the technology, the industry as a whole will be able to offer customers more sustainable bank loans without eating away unnecessarily at profit margins. And lower interest rates for end customers is ultimately beneficial for both household economies and for society as it stimulates economic growth.
If you want to hear more about our AI-based solutions, please do not hesitate to contact us. Let’s have a data transformation journey together!
Aleksandr leads the data science domain development in Financial Services. He has worked in several international banks within risk management and business development, with a strong track record of business growth and intensifying corporate performance in Nordics, Baltics, and Poland.