FG Life case study

Anaplan supports financial institution’s rapid expansion



Founded in 1993, Financial Group Life (FG Life) is an innovative organization that focuses on providing financial services to Russian industrial companies to help boost development of critical market sector enterprises. After a decade plus run of private growth and expansion, FG Life acquired six other monetary institutions under its unified brand. Today, the business is one of Russia’s fastest growing banking groups, with a choice spot on the Forbes rating’s Top 50 to prove it. More than 800 offices across 75 regions provide services for over three million private customers and 100,000 organizations.

FG Life’s corporate structure is designed to support the company’s performance-oriented methodology. Unlike the majority of banks, which use computer-driven predictive analytics for credit scoring, FG Life powers its analytic credit scoring with human intelligence. The organization trains and certifies sales managers to assign credit scores. These managers are then evaluated on the efficacy of their choices. The approach has proved enormously profitable for the bank, but the bottom-up focus on individual performance has in turn put massive demands on data models. Last year, as FG Life continued the aggressive expansion of its branches and customer base across three banking divisions (Corporate, SME, and Retail) the strain to produce complex rolling plans, manually produce budgets, and track performance at a more granular level was taking its toll. It had become impossible to cover new business requirements with the existing Excel-based systems. It was time for a new solution.

The Business Challenge

After guiding one of FG Life’s banks through an EPM implementation, the Russian consulting group FinScience was asked to help the organization’s SME division find an Excel alternative. FinScience CEO Oleg Zimin had just completed his training as an Anaplan reseller and saw an enormous opportunity to bring the new platform to the bank. “FG Life’s business needs were changing very fast, both in terms of rapidly growing office branches and a dynamic product portfolio,” comments Oleg. “I saw no chance of them succeeding with any of the traditional EPM solutions.” The bank sent Oleg an Excel model to prototype and he was able to convert it into Anaplan in just three hours. Impressed by what they saw, the executive team made an immediate decision to move forward.

FG Life’s Excel problems encompassed all the usual suspects: scale issues, manual processing lags, slow calculation times, and an inability to reflect the true complexity of the data. To settle on a pilot project Oleg sat down with Tatiana Vlasova, the head of financial management, and Konstantin Malchushkin, the head of strategic development and analysis. They decided to create a target planning model for the SME division that would incorporate four product strategies (credits, credit lines, deposits, accounts) across offices and managers.


Soon after, the president of Life Group approved Anaplan as a strategic initiative, paving the way for a streamlined roll out. Oleg and a team of four freshly trained power analysts built out a target model for 185 SME offices and 600 sales managers across 4 FG Life banks (ProbusinessBank, Express-Volga Bank, VUZbank, GazenergoBank). The model performed calculations for two different strategies (active and passive) across 10 product groups and four product logics. The real-time implementation from design through the build, the establishment of an automatic import from two separate data warehouses, and the final go live, was completed in just 80 hours of work.

Sales Forecasting and Financial Benchmarking


The New Transparency

Now that Anaplan has been fully adopted it is bringing previously unthinkable analytic and planning powers to FG Life SME’s office directors, enabling them to test scenarios and evaluate the impact of different drivers at the speed of thought. “Previously, Excel limited our planning to territories and office structures. With Anaplan, models reach down to managers and employees across different versions and dimensions,” notes Tatiana Vlasova. “We are also seeing an increase in the level of detail for banking products and services.“

In purely quantitative terms, FG Life SME has experienced a 150-fold increase in the amount of actual data running through its models. But this considerable figure doesn’t quite speak to the new analytic horizons Anaplan has opened at the division. Konstantin Malchushkin states, “After years of struggling to track our team’s work, Anaplan provided us a dynamic solution that allows users to zoom in on any aspect of performance.” The influx of customer information is then folded back into an ever-evolving strategy, which, thanks to Anaplan’s highly flexible modeling capabilities, can be implemented in the timeframe of a single work day.

After years of struggling to track our team’s work, Anaplan provided us a dynamic solution that allows users to zoom in on any aspect of performance.

Konstantin Malchushkin FG Life


Beyond the ability to dive into detailed financial sales planning, Anaplan has given the entire bank a corporate benchmarking system that offers feedback at the office level all the way down to the individual. Depending on their level of access, employees, managers, and executives can check in to see how they are performing against targets in real-time and across a variety of metrics. One such metric is a scoring system for the comparison of unit sales across multiple dimensions, so now offices and managers can check in to see where they stand vis-à-vis one another. Tatiana explains, ”The new metrics have been a huge boon to our performance-oriented culture. We thrive in an atmosphere of ‘every sale counts.’ Now, quite literally, employees count every sale. Everyone knows where he or she stands and no one is left in the dark. Anaplan has changed the company’s analytical approach from one of hurried conjecture to one of fact-based action.”

Ease of Adoption

There was never doubt that Anaplan would bring more power, flexibility, and subtlety to FG Life’s modeling processes; but the more important question was: would people take advantage of the platform’s capabilities? How would it be adopted? “Anaplan was not just a change of systems for FG Life,” notes Oleg, “But a change in the approach to daily business across the board.” In a matter of weeks the bank’s Excel masters had adopted Anaplan’s natural business language and were beginning to ask more sophisticated questions.

The successful cross-company embrace of Anaplan has been a result of several factors working in concert. Firstly, FG Life’s analyst team has worked hard to promote Anaplan awareness within the organization, and moved quickly to roll it out. Secondly, Anaplan’s self-sufficient “don’t wait, act now” ethos has turned out to be a natural fit for FG Life’s highly motivated employees. Thirdly, the intuitive platform has proved a very easy transition for the Excel-savvy workforce.


The increased planning power has resulted in significantly better forecasting quoting for the business. But it has also enriched the level of communication. In February, Tatiana sat down for a video conference call with the other analysts and office managers at FG Life across Russia. For the first time, everyone was looking at one model, with total confidence that all parties understood the budget up for approval. The conversation was not focused on whether the numbers were right, but what to do about them.

Moving Forward

Plans are already in motion to scale up to 400 users and build out five or six more applications, including a sales commissions model that will bring even more sophistication to the incentivizing process. In tandem with these initiatives, FG Life has plans to create an internal Anaplan competence center, where users will be encouraged to share their knowledge as the implementation scales. In the long term, FG Life intends to push Anaplan out to every bank and division in its brand consortium. “Anaplan is the perfect platform to support the rapid expansion of our business,” says Tatiana. “And we’ve got big scale and big plans to match it.”

Use Cases
  • Sales Forecasting
  • Profitability Analysis
  • Operations Planning
  • Incentive Compensation Planning
  • Bank budget formation driven by hundreds of disconnected territorial Excel spreadsheets
  • Inefficient manual import of actuals from various separate data warehouses
  • Complex formulas for rolling planning
  • Cloud-based system provides a single data source across bank branches and territories
  • Platform delivers immediate post-sale information on credit/deposit rates, product terms, treasury rates, and other figures to anyone with access
  • Ability to test scenarios and evaluate driver impact at the speed of thought
Results at a Glance
  • 80 hours real-time implementation from design through go live for 185 offices and 600 sales managers
  • 150-fold increase in actuarial data running through models allows for granular views on employees and product lines
  • New corporate benchmarking system provides immediate feedback from office level
    down to individual level
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