Ever since the phrase “Big Data” was coined in the 1990s, the benefits of leveraging large amounts of data in business have been clear. Yet in 2021, only a quarter of executives described their companies as being data-driven. [1]
We’re proud to be among the minority that fully embraces data science. But what does that actually mean? And how does data science help us enhance our predictive capabilities?
Data science can seem a bit like a crystal ball. But it’s actually a combination of machine learning, programming skills and statistical analysis. Using these techniques and tools, we identify patterns in historical data to create models that predict what could happen in the future.
These data-driven models are tailored to meet specific business needs. They can be trained to identify the warning signs of customer dissatisfaction, and on the flip side, find potential new customers. They also play an integral role in risk management, detecting fraud and providing early warning signals of potential financial difficulty among buyers.
While data science is a relatively new field, insurance companies have always worked with actuaries who use similar statistical techniques to predict risks. But what puts data science in a league of its own is that it can comprehensively analyze so much data. Much more than a simple Excel spreadsheet ever could.
Machine learning can gather information from millions of companies, analyzing key factors like debt, liquidity, and country and sector risks. With this information, we’re able to highlight which companies may be at risk of non-payment, or even filing for bankruptcy.
However, we also rely on "human power.” We update and adapt the models constantly with the help of risk analysts who review company financials daily and check the model for accuracy. So, while our advice is informed by large volumes of high-quality data, human analysis is the key. Thanks to this powerful combination, we can help our clients make safe, confident decisions and protect themselves against risk.
As we move further into the digital age, the power of data-driven decision-making is becoming undeniable. At Allianz Trade, we’re taking full advantage of this opportunity. We’re using data science to improve our predictive capabilities and gain efficiencies by detecting weak signals across a large range of subjects, from fraud detection to debt collection.
But we’re not stopping there. As the field of data science evolves, so too do we. We stay at the forefront of the latest technologies and techniques to continuously improve our models, enhance the complementarity of data science and our expert analysis, and provide clients with the best possible service. The future of data science in trade credit insurance is bright, and we’re excited to be leading the way.
[1] https://www.zippia.com/advice/big-data-statistics/
Felipe Rugeles Ospina
Group Data Science Manager
Allianz Trade
