Hybrid Approach to Document Anomaly Detection: An Application to Facilitate RPA in Title Insurance
- Title
- Hybrid Approach to Document Anomaly Detection: An Application to Facilitate RPA in Title Insurance
- Creator
- Guha A.; Samanta D.
- Description
- Anomaly detection (AD) is an important aspect of various domains and title insurance (TI) is no exception. Robotic process automation (RPA) is taking over manual tasks in TI business processes, but it has its limitations without the support of artificial intelligence (AI) and machine learning (ML). With increasing data dimensionality and in composite population scenarios, the complexity of detecting anomalies increases and AD in automated document management systems (ADMS) is the least explored domain. Deep learning, being the fastest maturing technology can be combined along with traditional anomaly detectors to facilitate and improve the RPAs in TI. We present a hybrid model for AD, using autoencoders (AE) and a one-class support vector machine (OSVM). In the present study, OSVM receives input features representing real-time documents from the TI business, orchestrated and with dimensions reduced by AE. The results obtained from multiple experiments are comparable with traditional methods and within a business acceptable range, regarding accuracy and performance. 2020, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature.
- Source
- International Journal of Automation and Computing, Vol-18, No. 1, pp. 55-72.
- Date
- 2021-01-01
- Publisher
- Chinese Academy of Sciences
- Subject
- Anomaly detection; autoencoder; dimensionality reduction; one-class support vector machine (OSVM); robotic process automation; term frequency inverse document frequency (TF-IDF); title insurance
- Coverage
- Guha A., Data Science Department, CHRIST (Deemed to be University), Bangalore, 560029, India, First American India Private Ltd., Bangalore, 560038, India; Samanta D., Computer Science Department, CHRIST (Deemed to be University), Bangalore, 560029, India
- Rights
- Restricted Access
- Relation
- ISSN: 14768186
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Guha A.; Samanta D., “Hybrid Approach to Document Anomaly Detection: An Application to Facilitate RPA in Title Insurance,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 23, 2025, https://archives.christuniversity.in/items/show/15894.