At AQRISK our key focus is to provide fintech solutions that make it much easier for banks to optimize their core banking business and become more efficient and profitable. Pricing functionality is a key component in succeeding at this.
The AQBANKING Solution Suite includes the AQOPTIMIZER solution, which incorporates all the functionality needed to perform optimized pricing and beyond.
By "pricing", in the core banking business, we mean the process of setting interest rates and fees on banking products and services.
In banks, income from interest rates and fees typically make out most (often 70-90%) of the total revenue streams. Enhancing the process of setting interest rates and fees in an optimized fashion, is therefore a highly important activity and makes a great difference in the profitability of the bank.
“In our estimation the AQOPTIMIZER solution - by supporting optimized decision-making and pricing at scale, across the bank - provides a 6-21% increase of interest rate and fee revenue streams and very high value-creation to our clients.” – Morten Virenfeldt, CEO at AQRISK
Pricing products and services is, of course, a common and fundamental activity in any business, but performing rational, fair and optimized pricing in banking is particularly complex, because of the amount of input, calculations and conditions that need to be considered, as well as the the large number of advisors etc. applying it to customers.
To accomplish holistic pricing - where all relevant input is considered - requires a great deal of information about the customers, products, collateral, other income, risks, capital requirements, return requirements including strategic adjustments and the bank’s cost and funding structure etc. Providing this is no small task, regardless of the size of bank.
The proportion of mid-size and smaller banks running centralized pricing models is quite low. This is largely due to a lack of resources and IT and quantitative specialists.
In our experience, however, the mind-set and openness towards running pricing models, does not have much to do with the size of the bank, but rather how progressive it is towards allowing more data and advanced analytics deeper into the decision-making process. In fact, we see that business benefits form implementing pricing models are typically relatively higher for mid-size and smaller banks - because they often come from a place of comparative disadvantage.
No pricing models
Without the support of pricing models, bank advisors are often left with static, written procedures to follow. To effectively capture the nuance and complexity of pricing thousands of products and customers via simple procedures is simply not possible.
In our experience, such written procedures are furthermore often not clear, unnuanced and maybe even hard to understand for advisors.
Another problem is that rational pricing of products and customers requires a lot of information that is just not available to advisors, or that they cannot be expected to know - like the costs of the bank or the effects of capital requirements from adding collateral, products, changing credit rating etc.
Also, most bank advisors are typically very busy, tending to hundreds of customers, and they do not have resources to spend a lot of time on every single customer assessment and pricing – it must be very fast, and speed is of the essence.
"By moving to AQOPTIMIZER we have reduced time used for client assessments and pricing by a factor 12 - this provides great user satisfaction and makes implementation and banking optimization very efficient." - Erik Nejrup Kjærside, Head of Business Development – Corporates at Vestjysk Bank
One of the great advantages of the AQOPTIMIZER solution is that customer assessments and pricing is performed in seconds. It not only frees up time in the organization, but also allows for applying pricing models to the private customer segments, where many banks currently do not offer rigorous pricing support to advisors.
The consequence of little or no pricing model support to bank advisors, is that customer assessments and pricing becomes an impossible task, that ends up becoming a largely ad-hoc process and often on the premise of the customer. This is evident from empirical evidence when comparing interest rates set on products from advisors with and without pricing model support - it is illustrated in the figure below.
The figure shows an illustration of 1.000 loans with required (and defined by Management) interest rate limits between 2-10%. We assume the loans belong to bank customers, that are evenly distributed in creditworthiness and all other matters that impact the pricing.
The boxplots show the distribution of interest rates from the 1.000 loans within the defined 2-10% interest rate spread, with pricing model support (green) and ad-hoc (red).
A high-quality pricing model will provide estimated required interest rates that are evenly distributed across the interest rate spread. Bank customers, with low creditworthiness will require higher rates and customers with high creditworthiness lower interest rates.
Without pricing model support, it becomes ad-hoc and looks more like the red case, with most loans being 'priced' in the lower end of the spread – regardless of the characteristics of the customer.
Some of the reasons for this, is that when advisors are not supported by rational and objective interest rate indicators, other factors take control, like wanting to nurture the good relationship with the customer and thus often being too generous from a cost and risk-adjusted bank profitability perspective.
The consequence from providing advisors with holistic, rational, and optimized pricing is massive and will significantly strengthen the profitability of the bank.
"The AQOPTIMIZER application has already shifted the understanding of department managers and financial advisors, towards a holistic view of the profitability of a customer or customer group." – Nikolai Krogh-Hansen, Head of Corporate Banking at Sparekassen Thy
Over-simplified models
Some banks apply very simplified pricing support systems, often using Excel or similar. Besides the obvious operational issues of using such programs, banks risk biased/wrong pricing from dependence on over-simplified frameworks. In our experience such frameworks rarely incorporate all relevant input and so do not capture the relevant pricing effects appropriately.
Some problematic issues often include:
The risk from using such over-simplified frameworks, is that they exacerbate unintended biases as they turn systemic and thus may generate highly problematic bank-level consequences.
When applying pricing models, it is therefore very important, that they have high quality and consider all the relevant information and precisely reflect risk, capital requirements and management’s risk appetite etc.
The proportion of large banks having some sort of centralized pricing models is higher than for mid-size and smaller banks. These pricing models are primarily internal build within the bank. This is largely due to the availability of more internal resources and specialist know-how. It generally provides large banks with a comparative advantage of effectively assessing and pricing customers and thus assuring desired profitability levels are met.
When considering pricing models in large banks, a wider number of problematic challenges are visible:
So even in large banks building, maintaining, and running pricing models often presents major challenges.
A trend with large banks is an enforced focus on running the core banking business and realigning to scale down internal IT resources in areas where attractive vendor alternatives exist.
For large banks it is much faster, more cost effective and futureproof to partner with AQRISK than running internal development.
At AQRISK we are working very hard to succeed on our mission to become a primary fintech partner to mid-size and smaller banks by allowing them to benefit from access to vital solutions and business optimization at affordable prices and without high costs to quantitative and IT specialists. We want to help provide a level playing field in utilizing business benefits from data.
Many mid-size and smaller banks do not have the resources and specialist know-how to build and run advanced pricing models. They achieve great benefits from partnering with AQRISK in this area. Our experience is that many mid-size and smaller banks are acutely aware of the need to adapt stronger approaches for optimizing the core banking business.
We are proud that our customer-base includes both large, mid-size and smaller banks, it shows the broad appeal of our solutions have, and we really see no lower limit to the size of banks being able to implement and gain great business benefits from the AQOPTIMIZER solution.
Our mission furthermore includes providing large banks with easy and fast access to innovative new solutions, without having to invest massive internal resources in development and maintenance.
The main benefits for larger banks to migrate to the AQOPTIMIZER solution include:
There is no doubt that optimized risk-based pricing in banking will become much more prevalent in the future – it is required to effectively optimize the core banking business and has huge positive benefits.
AQRISK is here to help make this happen in close cooperation with our treasured clients.
We find that AQRISK has a strong focus on continuously developing and improving the application in collaboration with the banks. The development and implementation of concrete improvement proposals is very rapid. - Frank Mortensen, CFO & Board of Management at Arbejdernes Landsbank
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For enquiries, please contact: Esge Räder (CCO): mail: esge.rader@aqrisk.com | mobile: +45 31328848
