Unleashing automation to unlock visibility, control, and efficiency in liquidity management

By ditching a web of spreadsheets and emails in favour of Salmon Software’s Treasury Management System, the liquidity management team at the Zurich Insurance business unit Switzerland and CI EMEA has been able to facilitate accurate and insightful short- and long-term cash forecasts as well as enhance its treasury payments and reporting capabilities

by | April 25, 2022 | Salmon Software Limited

Celebrating its 150th anniversary this year, Zurich Insurance Group (Zurich) is a global multiline insurer with around 55,000 employees. It provides a suite of insurance products and services to a range of customers in more than 215 countries and territories.

With a market capitalization of CHF60.0bn (US$65.38bn) in 2021 and a recently announced 2021 business operating profit of US$5.7bn, Zurich is entering its next 150 years on a solid footing. This is particularly the case for the Swiss-based liquidity management team, which has recently implemented a new treasury management system, Salmon Treasurer.

Before the implementation, the liquidity management team’s main challenge was manual processes. For example, there was a significant dependency on partners due to various services being outsourced to Zurich’s service centres around the world, resulting in a vast number of daily emails containing business-critical data.

Mauro D’Ambros, head of Liquidity Management at Zurich, recalls his team would receive the same information from various sources in various formats.

“We had to be very mindful of this – we could receive something on February 11 from Person B that we’d already received on February 7 from Person A,” he says. “The numbers could be slightly different for the same payment as well, where the first email might be an assumption and the second one was the real payment, for example.”

The use of spreadsheets was also a challenge. Depending on the day and month, the team dealt with outflows which could vary greatly. All of this information was managed in excel, which could only be accessed by one employee at a time.

Another area where the use of spreadsheets was hampering efficiency was counterparty risk analysis. To calculate Zurich’s exposure to a counterparty for the past six months, D’Ambros had to open a huge number of Excel spreadsheets before keying in said respective number into another spreadsheet and then manually draw a graph.

Zurich’s treasury management team also wanted to be able to support its cash forecasts; figures from the various departments for its long-term liquidity planning could only be compared with the actual data.

“The entire project aimed at getting away from these highly manual processes and the dependencies that we have to make a state-of-the-art treasury solution,” recalls D’Ambros. “We also wanted to be able to run reports and do analysis at the click of a button.”

Scoping, analysing, selecting

Having identified the issues, they wanted to fix; Zurich embarked upon a rigorous selection process, eventually leading them to Salmon Treasurer. This began with an analysis phase and the scoping of the project to identify exactly what was required.

“This process looked at what our current daily tasks were and what they should look like in the future,” notes D’Ambros. “We did an analysis of cash flow data sources to map out where we were getting the information from. We had to identify various dependencies that rely on our data and understand from whom we wanted to get the data in future.”

Several internal challenges had to be overcome. For example, the team required a functional and technical data blueprint for the entire IT environment. Data classification from Zurich’s numerous upstream systems and data privacy also needed to be tackled in advance of any system implementations.

An initial market analysis of potential vendors revealed many of the ‘usual suspects’ for Zurich, but reference calls to contacts known to the team members and trusted consultants broadened the list of potential partners.

“The next step was to carefully structure our RFP,” continues D’Ambros. “We put together a thorough document with 230 questions and involved the procurement function in this process.” The RFP also considered the system landscape.

Evaluating the feedback from the RFP enabled Zurich to start ruling out some of the potential vendors. Zurich held a half-day workshop with the remaining potential vendors, who were provided with design specifications and reporting requirements. During the workshops, participants were scored and there was a weighting per agenda topic in the scoring.

“The top two potential vendors from the workshops were presented to the steering committee, which had been involved from the very beginning,” comments D’Ambros. The final step was a financial viability process at which point Zurich selected Salmon Software.

There were various reasons why Zurich selected Salmon. One important driver emerged during the workshop process, as D’Ambros explains. “We gave every system provider some vendor homework to do. Some did this well and others less so. From Salmon’s response, it was clear that they really cared about us.”

D’Abrose notes Salmon’s dashboards presented at the workshop were “amazing”, a clear sign “they were taking [the process] seriously”. For Salmon, Zurich would also be their first customer in Switzerland and their first insurance company client.

The Zurich team also knew some of the other vendors had significant programming changes in the pipeline and were essentially developing new systems. “We knew we would not be presented with a completely new Salmon Software within the next five years,” D’Abros explains. “There will be enhancements every year, but we don’t have to expect a dramatic change that requires us to adapt everything again.”

New system swings into action

At the time of the signing, Zurich had already started the cloud-approval process for the system with Salmon. This included delivering IT solution blueprints and a specification regarding the architecture and security due diligence, software procurement, governance processes and gaining legal approval.

Following this, work began on ensuring the optimal number of interfaces between the treasury management system and the various data sources with which Zurich’s team wanted to work.

“We started defining and agreeing on the requirements and testing the implementation of the interfaces,” recalls D’Ambros. “This took quite a long time, almost a year in fact. Having started with 10 to 12 interfaces, we are now up to 15!”

In parallel with the interface work, phase one of the implementation began. This included setting up both the short-term forecast and the static data. This included bank account data, which D’Ambos says was “quite a challenge” to collate as there were various teams within Zurich taking care of different bank accounts.

“It was hard to know if we had the complete picture or not because we were dealing with a huge number of bank accounts,” he admits. Once the bank account information had been collated, the entire set-up of the system could begin including the naming conventions.

“Once we had that ready, we imported the static data and then started working with Salmon on designing and testing the dashboards,” explains D’Ambros, who notes the dashboards are “extremely flexible”.

“They have a variety of standard dashboards, but you can tell them exactly what you want, and they will configure the dashboards that way,” he says. While the team were clear they did not want to replicate the old spreadsheets, they were used as a starting point for the dashboards’ design.

User training on the short-term cash management also started with Salmon during this initial phase, and included testing of the application to ensure it did exactly what was required. “In a typical corporate treasury environment, you often try to adapt the existing processes in such a way that few adjustments have to be made to the new treasury management software.” D’Ambrod says.

However, due to the complexity of our business, the system needed to be able to adapt. “[Salmon] presented their TMS but wanted to hear our needs and how we wanted to work with it. They added updates to align with our wishes, so we didn’t have to change too many processes,” D’Ambros says.

Phase one implementation ran in parallel with the existing operations for a near six months before going live in September 2021. Phase two, the long-term forecast, had already begun – the main challenge here was also an Excel-based issue.

Salmon Treasurer has a module designed for long term-forecasts. During the workshop phase, Zurich’s teams stressed they wanted to enhance this module to “work even better” and align with Zurich’s long term forecasting needs, says D’Ambros. “We agreed with Salmon that if we selected their offering, they would implement a brand-new module from scratch based on our inputs.”

With this module, Zurich again went through the static data set up, testing and gave Salmon feedback about potential enhancements for the next versions. Having received and tested the final version, the conversation again turned to dashboards. The system went live on January 1, 2022.

The benefits of automation, visibility and control

Salmon Treasurer has allowed Zurich to achieve its goal of reducing the amount of manual intervention in its cash flow data. The data which previously was keyed in manually is now being automatically populated in the system via various interfaces.

“Out of our 15 interfaces, 13 to 14 interfaces deliver the data, so all the manual queueing data has been drastically reduced,” D’Ambros says. “Around 95% of the emails we used to receive have gone and we’ve reduced the amount of duplicate information being received.”

In addition, Zurich’s team are now not only importing outflows but also importing expected inflows which helps the team with daily cash management. The new system also provides daily visibility of some hundred bank accounts. This enables the team to run risk analysis, such as monitoring counterparty exposures, for example.

“We have certain regulatory requirements where, in the past, the control of a potential breach was time-consuming and done manually,” D’Ambos says. Using the new platform, Zurich has introduced an automated pre-warning system which signals an alert should a breach or something unexpected happened on a specific bank account.

This visibility marks a huge change for Zurich, which has a vast database where some hundred thousand bank transactions are imported annually and up to several thousand transactions daily.

“We now have an amazing data hub where we can run comparisons,” says D’Ambros.

During December and January, D’Ambros says the ‘big money’ for insurance companies comes in. Using Salmon’s system, Zurich can compare December 2021 with December 2020 more easily and efficiently. The team can also run comparisons between specific days which helps them spot patterns and have a much better understanding of when the money really comes in.

“It is a good tool to use in the future for forecasts and, importantly, it’s not only the liquidity management team using this,” D’Ambros says. “Various other departments are also using Salmon to run their reports for management.”

Treasury payments have also greatly benefitted from the new system. In the past, payments involved emailed communication with some of Zurich’s service centres which would capture the payment using third party software. The manual nature of this process meant errors could occur along the way. Now all treasury payments are managed directly by Salmon Treasurer.

D’Ambros says more than 30 users are now actively using the systems’ dashboards where they can compare their forecasts with real-time cash flows and positions. “This helps them improve their processes, which is a huge step forward for us,” he says.

Reporting has also changed drastically for the better since the implementation. Where analysing counterparty exposure used to involve opening numerous spreadsheets and manually adding data to another one, that is now all consolidated in Salmon.

“We have our dashboards, we have the graphs, we can use the various filters and quickly see the results onscreen,” states D’Ambros. “Then we can export it to a PDF, we can drill down or we can export the underlying data to Excel if anybody wants to see some of the data in a different way. That is a great step forward.

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