Case Study

Automated loan granting

A securities loan in 15 minutes with just a few clicks: this is what the innovative automation solution from a leading service provider in the banking and securities sector makes possible for neo-brokers. The innovative framework is a first step towards generative RPA.

#Financial industry
#Generative AI


Taking robotic process automation to the next level.

The scenario

A securities loan in just a few clicks

Neo-brokers enable investors to trade shares and ETFs online. Depositary banks play an important role in the background. With their various services, they ensure that all trading transactions run smoothly and enable the granting of credit, for example. One of the leading banks for securities and banking services in Europe wanted to further simplify and accelerate this process.

The vision: to offer customers a securities loan in the app of a neo-broker in just a few clicks to free up more scope when investing.


The challenge

Too complex for traditional RPA

It usually takes two to three weeks from application to approval of a securities loan. Behind this is a complex process which, in the case of our client, comprises around 150 steps in 8 different systems with a wide variety of interfaces and is based on individual decisions. Traditional automation with RPA was therefore out of the question. Solutions like this can take over rule-based and repetitive tasks, thereby speeding them up. However, they are not suitable for complex, decision-based processes such as the granting of loans - at least not without further ado.

The solution

Automated loan granting thanks to an innovative framework

Thanks to an innovative RPA solution, our client's complex and decision-based loan granting process is now fully automated. To achieve this, the experts at Leadvise Reply have significantly enhanced the classic RPA approach. The new framework comprises a large number of new processes, databases, APIs as well as control and decision-making mechanisms in which recurring data is generated, structured and processed. On this basis, the system independently draws up loan contracts and grants loans. A first and important step towards generative RPA, which will open up a completely new business area for the securities and banking service provider in the future.

How did we do it

Intelligently adapting legally compliant structures

The granting of loans is highly regulated by law. To be able to implement the automation of lending in a legally compliant manner, the securities and banking service provider had to be cleverly integrated into the process at certain points without holding up the process flow. Together with the experts from Leadvise Reply, the service provider also integrated a real-time transmission of documents and set up long-term cloud archiving, which enables the audit-proof storage of all loan agreements.

The project at a glance

Efficient development and accelerated decisions

Taking out a securities loan and trading it on the stock exchange: The intelligent automation solution now makes this possible in the shortest possible time. The concept is convincing. Numerous neo-brokers have already expressed interest to the securities and banking service provider in making the solution available to their customers. All in all, a successful project:


intelligent automation solution that opens up a new area of business


minutes instead of 2-3 weeks waiting time until loan approval


complex process steps automated in 8 systems


Leadvise Reply specialises in management consulting for the challenges of digitalisation with a focus on industries such as telecommunications, chemicals, pharmaceuticals or the banking and stock exchange environment. Leadvise Reply supports companies in digitalisation, organisation and implementation projects using advanced technologies such as Robotic Process Automation, Intelligent Process Automation, Process Mining or Cognitive Assistants. The focus is on end-to-end process transformation, including strategy, business model development and roll-out management.