Image Technologies in Financial Services

The images are all prevalent and robust, and they cannot be copied easily. The human brain interprets the surrounding environment based on the visual medium.

The lack of ability to distinguish and process information present through images has been a major drawback in computer technologies since computers process data (bits and bytes). There is a requirement for the computer to function like the human mind in interpreting the images.

The development of visual technologies in relation with artificial intelligence has led the way for interpreting the visually available data, thereby heralding new opportunities in computer-aided decision making.

The defence and healthcare sectors were among the first to adopt image technologies since the sectors utilize a huge amount of image data.

The financial services sector is making slow progress in utilizing images to enhance their business performance along with modifying their offerings to deliver exceptional customer service.

The bank that expeditiously processes a loan application would often clinch the business. Banks are constantly looking at applying image technologies to enhance their customer service.

Spread of Imaging Data and Related Analytics

Images are authentic and ubiquitous, which cannot be manipulated easily. Hence, images are a repository of big data. The use of such data can provide invaluable information to the financial institutions.

To get an understanding of the quantity of information present, consider the following scenarios:

• Facebook has more than 100 billion images while the number is increasing on a daily basis.
• YouTube is projected to have around 690 million videos.

Within the financial sector, insurance firms have a significant amount of data - vehicle images, x-rays, scans, medical reports which are rarely used by stakeholders - legacy underwriting, policy management, claims, and MIS during processing.

Again, banks have a huge amount of disorganized data and if interpreted properly, it can deliver an insight on the growth potential for the financial institution.

Currently, advanced IT can interpret data in the form of images. Therefore, the image data can be utilized in several manners. Image analytics are the method of transforming uncontrolled data - images/videos to system interpretable framework/variables to provide useful information.

Image technologies conduct various transformations on the image to change them into a relevant output framework in the pattern of top-notch time series.

Data is organized into relevant clusters by finding out the low-level features. After the data are organized logically, it can be reviewed in various methods - algorithms (boundary, edge detection, color histograms and vector detection) are utilized for processing the imaging information.

The Transformation Period

The early years of imaging technologies saw its usage in the digitization of documents. Technological advancement enabled the recognition of patterns within images. Later on, it was used in biometrics as well.

Currently, it is being used across various applications - shopping to banking. Gradually, the use of imaging analytics in financial services witnessed its shift from simple extraction to smart decision making.

At the beginning, imaging technology solutions emphasized decreasing human resources cost through digitization of forms. OCR and ICT technologies were widely used for extracting the data content from images.

The financial sector identified its use in the digitization of application/KYC forms, document workflow solutions, check imaging and truncation systems. According to estimates, digitization decreases the processing costs by 80%.

Several organizations are utilizing image-segment based analytics to index complete libraries of images, videos, Geo spatial catalogs.

Some insurance firms are using the camera and bar code features in smart phones for pre-filling automotive insurance applications, by utilizing images of the ‘driving license’ and ‘vehicle identification number’.

The next step in imaging technologies is creating patterns from the image, and corresponding the patterns in the future. A perfect example of pattern recognition is facial-biometrics, wherein, banks utilize imaging technology to identify and validate a customer.

Banks such as HSBC have established ‘facial biometrics access control units’ in the data centres.

Forecasting Results

Advancement in the use of image/video as a repository of unknown data has encouraged certain financial institutions to forecast results on the basis of data present in the images.

Several systems have been created to evaluate the changes in video/images, and provide signals for specific unwanted attitude.

Banks are using predictive video analytics to counter unwanted events in ATMs/branches by informing the security on time. Certain firms are utilizing image distribution through social media for monitoring the level of impact through the organization.

The requirement for facilitating innovation and enhancing operational efficiencies has motivated firms to integrate the image-based technologies.

Technological advancements in faster image processing and storage have accelerated the change. The technology has been used in a wide variety of products - barcode reading, QR code reading, fraud detection, security improvement and claim processing.

Image technology would essentially transform the innovation process in the financial services sector.

The increase in the usage of smart phones, mobile apps and the technological progress made in interpreting information from images/videos expeditiously have provided the incentive to use imaging technologies. The presence of wearable technology like Google Glass has enhanced the transformation process.

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Christine is an experienced freelance business and finance writer. Currently writing for Academy of Financial Trading reviews.