What separates digital finance leaders from the laggards? How can CFOs better use advanced analytics to their advantage? This article offers a framework to help CFOs assess the finance office's current level of data sophistication and discusses the key areas finance teams should focus on to improve their analytics capabilities.
During an Allianz Benelux SA (Allianz) board meeting held in early 2019, Allianz’s chief financier officer (CFO) had a profound discussion with Allianz’s chief data and analytics officer (CDAO) on improving the company’s profit and loss (P&L) statement by targeting problematic cases among disability claims related to Allianz’s life insurance product. It appeared that certain claims had very long durations, leading to recurrent payouts surpassing the total amount of premiums. Consequently, there were too many claims that could translate into future losses. If this phenomenon persisted, Allianz could lose millions of dollars in revenues. Therefore, the CFO contacted the CDAO and his data office and requested that the team identify the client segments in which the most problematic cases of disability claims occurred. Additionally, the CFO wanted the data office to build a predictive model that could estimate the duration of a claim, to adapt the premium coverage to specific customer segments.
During an Allianz Benelux SA (Allianz) board meeting held in early 2019, Allianz's chief financier officer (CFO) had a profound discussion with Allianz's chief data and analytics officer (CDAO) on improving the company's profit and loss (P&L) statement by targeting problematic cases among disability claims related to Allianz's life insurance product. It appeared that certain claims had very long durations, leading to recurrent payouts surpassing the total amount of premiums. Consequently, there were too many claims that could translate into future losses. If this phenomenon persisted, Allianz could lose millions of dollars in revenues. Therefore, the CFO contacted the CDAO and his data office and requested that the team identify the client segments in which the most problematic cases of disability claims occurred. Additionally, the CFO wanted the data office to build a predictive model that could estimate the duration of a claim, to adapt the premium coverage to specific customer segments.
In January 2021, the chief data and analytics officer (CDAO) at Allianz Benelux SA (Allianz) spotted a possible opportunity to optimize cash flow with direct debit. Direct debit was a pre-authorized financial transaction between two parties where the amount due was directly and automatically collected from the payer’s bank account. Direct debit would allow Allianz to shorten payment processes, reduce risks by anticipating payments, and improve customer loyalty. Despite the clear advantages of direct debit for both clients and insurers, only a few of Allianz’s clients were currently making use of direct debit. It was not clear what drove Allianz’s customers or brokers to implement direct debit. This was where the CDAO and his data office team came in. The data office possessed a large amount of data on Allianz’s property and casualty insurance contracts and customers. Now the team needed to investigate how this data could be leveraged to determine the value drivers and develop a strategy to convert more clients to direct debit payments.
In January 2021, the chief data and analytics officer (CDAO) at Allianz Benelux SA (Allianz) spotted a possible opportunity to optimize cash flow with direct debit. Direct debit was a pre-authorized financial transaction between two parties where the amount due was directly and automatically collected from the payer's bank account. Direct debit would allow Allianz to shorten payment processes, reduce risks by anticipating payments, and improve customer loyalty. Despite the clear advantages of direct debit for both clients and insurers, only a few of Allianz's clients were currently making use of direct debit. It was not clear what drove Allianz's customers or brokers to implement direct debit. This was where the CDAO and his data office team came in. The data office possessed a large amount of data on Allianz's property and casualty insurance contracts and customers. Now the team needed to investigate how this data could be leveraged to determine the value drivers and develop a strategy to convert more clients to direct debit payments.
In October 2019, the regional chief data and analytics officer at Allianz AG, Belgium, attended a two-hour strategy meeting with the Allianz Benelux chief executive officer, who had expressed concerns about the company’s digitalization strategy. A few days earlier, the marketing department had found that online sales channel results had fallen unexpectedly. The chief executive officer was worried that the company could lose market share if it did not react accordingly, which would damage the company’s competitive position in the market. Therefore, the regional chief data and analytics officer was asked to gather a team to investigate why online sales were low and to design an effective customer acquisition strategy. In addition to his data office staff, the regional chief data and analytics officer asked for the business transformation unit to provide assistance. He had to consider how best to approach this challenging task.
In October 2019, the regional chief data and analytics officer at Allianz AG, Belgium, attended a two-hour strategy meeting with the Allianz Benelux chief executive officer, who had expressed concerns about the company's digitalization strategy. A few days earlier, the marketing department had found that online sales channel results had fallen unexpectedly. The chief executive officer was worried that the company could lose market share if it did not react accordingly, which would damage the company's competitive position in the market. Therefore, the regional chief data and analytics officer was asked to gather a team to investigate why online sales were low and to design an effective customer acquisition strategy. In addition to his data office staff, the regional chief data and analytics officer asked for the business transformation unit to provide assistance. He had to consider how best to approach this challenging task.
Berendsen Island, an outsourced workwear service, uses the standard costing model to determine its profitability. Because the company recently reported a loss, the plant manager and the business controller investigate time-driven activity-based costing in an effort to gain insights into its cost structures. The company also needs to provide a quote to two potential new customers.
Berendsen Island, an outsourced workwear service, uses the standard costing model to determine its profitability. Because the company recently reported a loss, the plant manager and the business controller investigate time-driven activity-based costing in an effort to gain insights into its cost structures. The company also needs to provide a quote to two potential new customers.