Finnova Analytical Framework
How Finnova, a leading Swiss banking software provider used by more than 100 banks, embedded Prospero's DetectX® predictive analytics into their Finnova Analytical Framework, reducing false alerts by 98 percent.
A predictive analytics framework inside the banking software
Finnova is a leading provider of banking software in the Swiss financial centre. Finnova supports banks and outsourcing providers in achieving digital transformation and open banking, and their solutions are used by more than 100 banks.
At a glance
- Sector
- Banking
- Location
- Switzerland
- Solution
- DetectX®
- Website
- finnova.com
The story, as Prospero publishes it
About Finnova
A banking platform, and an open ecosystem around it
- Finnova is recognised for their powerful innovative banking solutions, in development, in operation and in advisory. Together with their partners, Finnova supports over a hundred customers from the financial services sector in being profitable and competitive. Through Finnova's Open Platform, which enables open ecosystems, banks are able to be more innovative, agile, and better satisfy their clients' needs. Finnova supports their customers' individual digitalisation strategies, both with their own products and with a broad-based partner network.
Starting position and challenge
Rule-based systems can only go so far
- Banks have to meet complex regulatory requirements. Rule-based systems can only provide limited support. Without the use of powerful, precise analytics, these requirements are managed with high risks and costs.
Solution
One analytical framework, embedded in the banking software
- The solution was to create the Finnova Analytical Framework, a business solution based on Prospero's software platform for predictive analytics, DetectX®. It is embedded in the Finnova banking software and responds to requirements from all suites and modules. DetectX® can be used to map the entire range of applications of machine intelligence for optimising the business processes of a bank in a uniform platform. The examples the source gives are anti-money laundering, fraud prevention, risk management, robo-advisory and potential-oriented sales management.
Functionality
Supervised learning, unsupervised learning and expert knowledge, combined
- DetectX® offers analytical approaches such as supervised learning, unsupervised learning, and rules based on expert knowledge. Supervised learning uses a target variable on which the model is built: a representative sample is drawn and separated into train and test datasets, and the optimised model is then applied to the universe of data in the productive environment. Within unsupervised learning the entire data is taken and used in the analysis and modelling process in an unbiased way, so unknown and suspicious behavioural patterns can be revealed. The combined use of both methods is what the source credits for accurate and stable models. Expert knowledge is no longer used in isolation but in combination with the other two, with profiling as a preliminary processing stage based on static and dynamic customer data.
The smart core of the framework
An engine that validates, optimises and calibrates in the background
- The heart of the framework is the DetectX® Analytical Engine, which validates, optimises and calibrates models continuously in the background. Whether the models are for fraud detection, transaction analysis, link analysis, robo-advisory or analytical CRM, the engine ensures maximum precision and stability of the modelling process. Data from different sources is loaded for processing, checked for completeness and distortion, transformed, supplemented and enriched. In a complex optimisation process, millions of combinations are calculated and the relevant factors are continuously determined with their weightings, all in an automated process so that expert intervention is reduced to a minimum. Model creation and model application run in parallel in an unlimited, scalable process.
What Finnova also said
- Nikolai Tsenov, Product Manager Analytics and Compliance, finnova AG Bankware
- We have evaluated the market and it has been shown that Prospero with its approach of a new generation of Prescriptive Analytics achieves the best model qualities in a highly automated process.
What Finnova published
Two figures and three awards. Prospero footnotes neither figure, and the awards are named with their year and their awarding body.
Published result
98% fewer false alerts
The reduction in false alerts achieved with the framework, as Prospero states it. No baseline, sample, period or measuring party is published alongside it.
A 360 degree view
Banks get a 360 degree view of their customers, and of their risks and opportunities. A capability claim rather than a measurement.
Three awards
Best Predictive Analytics Platform and Best Financial Transaction Company at the 2022 Fintech Breakthrough Awards, and earlier the Banking IT-Innovation Award from the Universities of St. Gallen and Leipzig.
Prospero's insights save time, resources, costs, and reduce the probability of operational risks and losses.
Every figure above is Prospero's own, carried from the case study it publishes. None is footnoted or dated, and none of it should be read as a benchmark.
Where to look next
The platform the framework is built on, the sector page that lists the banking modules, and the two other banking stories.
- DetectX® platform
- The analytical engine underneath the framework, and the capabilities it exposes.
- Banking
- Why banks choose DetectX®, and which modules answer which pressure.
- Sparkasse Zollernalb
- The same analytics applied to sales rather than to compliance.
- Risk Solution Network
- Credit risk rating models built, validated and calibrated for more than 30 banks.
Prospero also publishes this case study as a PDF. That file is not held in this site's assets, so there is no download here yet, and nothing above is taken from it.