Speed Up Claims Processing & Expense Reporting by Automating HEIC Conversion

In the world of claims processing and expense reporting, Java-based backend systems often struggle to keep pace with the devices in customers’ pockets.

While users capture high-quality HEIC images on modern iPhones, many legacy enterprise servers lack the native capability to process them.

The Business Impact

When a client uploads a photo of a car accident or an employee submits a travel receipt, they expect a seamless experience. However, legacy server environments often reject these modern formats. This leads to:

• Customer Friction: Users are forced to manually convert files, leading to abandoned claims.
• Operational Delays: Back-office teams receive “black box” files they can’t open, requiring manual intervention.
• Increased Costs: Training staff to handle file workarounds kills productivity.

While cloud-based APIs exist, finance and insurance firms often require the security of a native Java library to keep sensitive customer data on-premise.

By using JDeli, you can automate HEIC conversion entirely within your JVM, ensuring strict regulatory compliance and eliminating the latency of external third-party processing.

The Emerging Challenge: The “HEIC Gap”

The “HEIC Gap” represents the growing disconnect between modern mobile hardware and legacy enterprise systems. While Apple made HEIC the mobile standard years ago to save storage without sacrificing quality, many Java-based servers in the finance and insurance sectors remain locked into older imaging libraries.

This gap turns a simple photo upload into a technical failure, leaving backend systems blind to the high-quality images modern customers are submitting.

Why Legacy Systems Struggle

For the backend systems at banks and insurance firms, HEIC is often a foreign language. Many server-side environments remain locked into legacy imaging libraries that haven’t been updated to handle modern compression standards.

For these enterprises, the solution wasn’t a massive infrastructure overhaul. It was a targeted implementation that turned a potentially huge project into a small integration task.

Why JDeli for Document Intake?

• Security: Process sensitive insurance photos entirely within your JVM (no third-party cloud uploads).
• Speed: Instant conversion means claims adjusters see photos seconds after they are uploaded.
• Reliability: Eliminates “File Type Not Supported” errors that lead to abandoned claims.

There is no need to retrain staff or build complex workarounds. It effectively future-proofs the intake process against whatever format mobile manufacturers decide to use next.

The Implementation (for Developers)

For engineering teams, JDeli turns a complex infrastructure project into a simple library integration. It allows your system to silently detect HEIC files and convert them to standard formats like JPEG or PNG on the fly.

Code Example: Reading an HEIC Image

Integrating HEIC support into your existing Java workflow is straightforward:

1. Add JDeli to Your Project: Add JDeli to your class or module path. (download the trial jar ).
2. Point to Your Heic Picture: Create a file handle, input Stream pointing to the raw Heic image. Alternatively, you can also use a byte[] containing the image data if your data is in that format.
3. Read Heic pictures easily: Use JDeli to read the Heic image into a BufferedImage.

File heicFile = new File("/path/to/image.heic");

BufferedImage image = JDeli.read(heicFile);

Code Example: Converting HEIC to JPEG

1. Download the JDeli trial jar.

// Read HEIC image into Java

BufferedImage bufferedImage = JDeli.read(new File("heicImageFile.heic"));

2. Process image if needed (scale, sharpen, lighten, watermark, etc)

// Process image (Optional)

bufferedImage = operations.apply(BufferedImage bufferedImage);

3. Write out BufferedImage as JPG image file

// Write out BufferedImage as your desired format (JPEG in this example)

JDeli.write(bufferedImage, "jpg", new File("jpgImageFile.jpg"));

The Final Result: Seamless Image Processing

By solving for the “HEIC Gap,” these companies didn’t just fix a bug; they smoothed out the entire customer journey. They moved from a process that required manual hand-holding to one that is automated, invisible, and efficient.

As experienced Java developers, we help you work with images in Java and bring over a decade of hands-on experience with many image file formats.

Want to know more about how we can help you with your HEIC files? Talk to us to get insights from a Java developer team with more than 2 decades of experience with image formats!

// Read an image
BufferedImage bufferedImage = JDeli.read(avifImageFile);

// Write an image
JDeli.write(bufferedImage, "avif", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(dicomImageFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(heicImageFile);

// Write an image
JDeli.write(bufferedImage, "heic", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(jpegImageFile);

// Write an image
JDeli.write(bufferedImage, "jpeg", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(jpeg2000ImageFile);

// Write an image
JDeli.write(bufferedImage, "jpx", outputStreamOrFile);

// Write an image
JDeli.write(bufferedImage, "pdf", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(pngImageFile);

// Write an image
JDeli.write(bufferedImage, "png", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(tiffImageFile);

// Write an image
JDeli.write(bufferedImage, "tiff", outputStreamOrFile);

// Read an image
BufferedImage bufferedImage = JDeli.read(webpImageFile);

// Write an image
JDeli.write(bufferedImage, "webp", outputStreamOrFile);