Reforming and innovating: SINOSURE’s digital transformation in trade credit insurance
SINOSURE has embarked on a transformative digital journey, as its core process re-engineering programme has significantly improved corporate governance and operational efficiency in its trade credit insurance business. Moving forward, SINOSURE will enhance its data ecosystem and leverage AI tools to better manage global trade risks amidst economic uncertainties.
Since 2019, China Export & Credit Insurance Corporation Limited (SINOSURE) has been embarking on the path of digital transformation with its own distinctive features. With the implementation in 2022 of the core process re-engineering programme for its trade credit insurance business, at the end of 2022, SINOSURE has taken a major step toward a lasting digital transformation. The innovation and reform represented by this ambitious programme have already led to significant effective improvements in corporate governance.
Enhancing data governance and building a data ecosystem to create added value
With China having led the world in export volume for 15 consecutive years, SINOSURE has been at the forefront among Berne Union members in terms of the total value of insured trade. SINOSURE has consistently played a counter-cyclical and cross-cyclical role in navigating unprecedented challenges - the Global Financial Crisis, European debt crisis, Covid-19 pandemic, and other major global issues - and has accumulated a large quantity of valuable data. Nevertheless, given the volume and quality of data needed to drive the digital transformation, several challenges remain to be addressed: inconsistent data standards and classification; difficulty in data sharing between different business lines; insufficient interaction with external data; and high data acquisition costs.
SINOSURE’s trade credit core process re-engineering programme is underpinned by the construction of a data center. Our long-term and fundamental data governance reform focuses on three aspects. The first is unifying data definition across all business lines within the company, enabling the transformation of accumulated business information into structured and standard data. The second involves formulating structured data rules based on data standardisation, establishing more effective standards of conduct, and setting the rules for data collection and transmission. This ensures that the management requirements traditionally applied to written documents and regulations are better implemented, and that the business structure and IT structure are better aligned. Structured data rules allow us to introduce technical tools such as data dashboards, facilitating fast and accurate decision-making. The third aspect is building a vibrant data ecosystem with the aim of facilitating more effective interactions between internal and external data, thus fostering more interactive business collaboration with external partners.
Initiating reform to improve business operations and risk control capabilities
Throughout the past two decades, SINOSURE has developed assorted trade credit insurance products and business models, most of which have operated online. However, as these products and business models were developed years ago, it became increasingly difficult for the ever-updating management requirements to be equally applied to all products and to the entire business process. This was not just a question of using an outdated operating system. It was more about the necessity of conducting a fundamental business reform, without which we might struggle to continue to provide quality services to our customers or adequately control business risks.
Under the guidance of the company’s Enterprise Business Architecture Planning, SINOSURE has redesigned its trade credit insurance business process from a holistic perspective. We have identified the goal of enhancing risk management capabilities by drawing a blueprint which standardises and clarifies all links between business work flows, including marketing, underwriting, post-underwriting, claims settlement, recovery, and finance. Based on this blueprint, we have promoted process modelling, product modelling, and business entity modelling, and have constructed credit granting models based on internal credit rating. We have also focused on reshaping the original credit underwriting work flow. Following the implementation of a new operational system in late 2022, which represented a major milestone for the core process re-engineering programme, we spent all of 2023 optimising the new system. This has already led to a marked improvement in underwriting efficiency, customer service, and risk control capabilities[1].
Driving internal synergy for successful digital transformation
Like many other financial institutions, SINOSURE must face and tackle two major issues to effectively facilitate digital transformation. The first is how to improve the lack of internal synergy in problem-solving, which results from different departments having diverging understandings about the best path to achieving key objectives. The second is how to balance the real day-to-day working pressures of the department and the long-term goals for building the company’s business architecture.
We have consistently aimed to synchronise the implementation of real business reform with building business architecture. First, we have taken efforts to break the boundaries of departmental functions and set up an architecture-building mechanism led by the company’s Chairman and coordinated by the Office for Deepening Reforms. This was undertaken during the critical period of getting the core process re-engineering programme online. We have also built up a special joint task force, comprised of people from the headquarters and branch offices, to respond to all kinds of business demands in an agile manner and to ensure each key task is completed as planned.
Being aware from the outset that “Rome wasn’t built in a day”, we have taken each half year as one phase, implementing the programme steadily and taking the available resources and the high priority placed on problem-solving into account. Now the programme has entered its ninth phase By adopting this pragmatic working method, we have made innovative breakthroughs in our reform, adjusting the goals for each phase to conform to new external requirements and promoting wider contributions from more departments.
As our digital transformation has accomplished the goal of going “from zero to one” in a number of fields, we now face the immediate challenges of going “from good to great”. We firmly believe that the new dynamics of digital transformation cannot be fully unleashed without consistently adhering to the principles of “innovating on the basis of what has worked in the past” and “seeking truth from facts”.
Optimising human-machine interaction amid new challenges
At present, world politics and the global economy face prolonged and severe turbulence. We expect that global trade risks will remain at a high level for a long time, which will make it increasingly difficult for all credit insurers to balance risk control with business development. These challenges also necessitate higher requirements on data channels, data efficiency, and data quality to expedite the digital transformation of credit insurers. We suggest that all global credit insurers share risk data and risk-mitigating experiences, working together to better adapt to the ever-changing global risk landscape.
During the process of digital transformation, the responsibilities of our trade insurance underwriters will undergo significant changes. On the one hand, they must be closer to the customers, go deeper into the market, and play a leading role in policy research, formulation of regulations, and business innovation. On the other hand, they must continue to improve their data mining and modelling capabilities to integrate their underwriting experiences into data modelling. We need to nurture a team of underwriters with composite competencies. These underwriters will play a key role particularly in scenarios where important decisions need to be taken.
Artificial intelligence (AI) is and will continue to be a hotly debated and widely discussed topic in social media and across all major industries. As credit insurers, we should actively embrace the coming changes, exploring the application of AI tools in business practices to help decision-makers acquire data and actionable information in a more convenient and comprehensive way. Through this process, the AI tools we use will also be continuously driven toward self-improvement. As SINOSURE continues to reform and innovate in trade credit insurance, proactive adaptation to these technologies and strategic enhancement of data capabilities will help redefine industry standards and drive growth in the face of evolving trade risks.
- Note: B the end of 2023, about 78% of credit is auto-approved, with all the risk indicators controlled within the pre-set thresholds. ↑
