IFG Life Modernizes and Unlocks the Power of Data With MongoDB
Financial services customers across the Asia-Pacific (APAC) region speak often about the need to modernize their infrastructures to unlock the full potential of data. Frequently, companies are encumbered by legacy data architectures that create inefficiencies and complexities for their developer teams.
IFG Life
overcame these challenges by migrating to
MongoDB Atlas
. Garry Alfanzo, Head of IT and Architecture for IFG Life, shared insights during a presentation at
MongoDB.local Jakarta 2024
.
Modernizing by migrating to the cloud
A subsidiary of Indonesia Finance Group (IFG), IFG Life specializes in life and health insurance. The company was established in 2020 with an initial purpose of migrating policies from former state-owned insurance company Jiwasraya and bringing them under the IFG umbrella.
IFG Life had to overhaul an outdated infrastructure, which included multiple legacy systems and coding frameworks. To kick-start its modernization journey and enhance agility, IFG Life migrated to the cloud and adopted a microservices architecture. This led to the creation of the Customer 360 model, a platform designed to manage IFG Life’s four main user applications: customer, corporate, sales force, and hospital network.
“The purpose of developing this division [was] to create a single integrated platform. In this digital era, we realized that just having an outstanding app is not the only thing that matters. Data is also crucial,’ said Alfanzo.
The need for a robust database solution to support Customer 360 operations became evident.
Getting a false start with a graph database
“In 2022 the hype around graph databases was very high, leading up to a surge in various graph database solutions,” said Alfanzo.
IFG Life began pursuing this option. However, while implementing a graph database, the company experienced resource and knowledge challenges.
“In 2022, the hype around graph databases was very high, leading to a surge in various graph database solutions. However, this excitement was not matched by sufficient resources in Indonesia,” said Alfanzo.
This prompted IFG Life to shift its focus and seek a database that would meet its engineering team’s needs.
Finding the optimal solution with MongoDB Atlas
IFG Life needed a database with integrated graph capabilities—one that was widely adopted and supported by a large community in Indonesia. Additionally, the company needed to ensure access to a robust pool of local expertise.
“The solution we aimed to implement revolves around data integration, allowing us to unify our various cores and streamline our storage solutions,” said Alfanzo. “Data mining is essential to extract the collected data, and we require data science to perform analytics, including data streaming through CDC [change data capture] and batch processing, alongside visualization.”
Alfanzo’s team had already determined that it needed to move away from a relational approach, which was deemed ill equipped to meet IFG Life’s requirements. The team evaluated several NoSQL vendors, and
MongoDB Atlas
ticked all the boxes, and more.
“When we evaluated MongoDB, we identified features that were essential for us,” said Alfanzo. Among these were
$graphLookup
,
MongoDB Atlas Triggers
, and
MongoDB Atlas Device SDKs
. “There’s also
MongoDB Aggregation Pipeline
, which is crucial for crunching data, creating views, and performing queries,” Alfanzo added.
Alfanzo also mentioned how
JSON
, the text-based data format MongoDB uses, simplified IFG Life’s process of storing, retrieving, and viewing data.
However, what Alfanzo highlighted the most was the unique expertise, knowledge, and support that the MongoDB team in Indonesia provided: “One of the critical factors during our evaluation was the ecosystem and community support,” said Alfanzo. “Having access to people with technology skills is essential, as it has been our biggest problem. That’s why we chose MongoDB. What I truly appreciate is that [it is] not just focused on selling but also [focused on] providing solutions for the future.”
Integrating MongoDB into IFG Life’s ecosystem was a strategic decision that paid off. It facilitated the creation of a customer-to-system model, crucial for the Customer 360 initiative. This advancement enables IFG Life to better understand and serve its customers and has paved the way for more personalized and effective service offerings.
Unlocking generative AI capabilities with MongoDB Atlas Vector Search
Looking ahead, IFG Life is eyeing new frontiers with MongoDB, particularly as gen AI is fast spreading and being adopted by Indonesian enterprises.
“We’ve already used MongoDB for our Customer 360, which is currently ongoing,” said Alfanzo. “To stay aligned with this trend, we recognize that MongoDB offers a feature that enhances query similarity—
MongoDB Atlas Vector Search
—and we plan to incorporate this into our future implementations.”
Moreover, IFG Life intends to implement
retrieval-augmented generation
(RAG) to handle personally identifiable information (PII) securely.
“We understand that PII should not be sent to large language models (LLMs). Incorporating sensitive data can expose the system to vulnerabilities,” explained Alfanzo. “In this context, RAG is a more suitable solution as, when querying RAG, we can add an additional layer to provide context, and this context enhances [the] query—we can ensure that we have real-time context that aligns with the standards of insurance or banking.”
IFG Life is a great example of how MongoDB Atlas’s capabilities can help companies modernize their complex legacy systems in the data-dependent, highly regulated banking and insurance industry. This story also shows how the MongoDB Atlas platform can prepare organizations that want to reap the benefits of gen AI.
To learn more about
MongoDB Atlas
, visit our product page.
Get started with Atlas Vector Search today by checking out our
quickstart guide
.
March 18, 2025
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