Accelerate an urgent sustainable economic recovery from Covid19 in the UK mortgage market : Applying an AI lens

Digilytics是一家快速发展的英国中小企业，专注于人工智能。Digilytics由Arindom Basu领导，他是一名技术企业家，在金融服务领域拥有30年开发和引入颠覆性技术的经验。抵押贷款申请过程是一个复杂而漫长的融资过程。仅抵押贷款发起过程就涉及大约100种不同类型的纸质文件的人工处理。可能出现多次重复，错误会导致长时间和不必要的延迟。Digilytics的创新将结合计算机视觉、机器学习和NLP技术，创建大规模的首次抵押贷款应用程序。2020年5月，英格兰银行警告称，英国经济正面临自1706年以来最严重的衰退。抵押贷款行业是受新冠肺炎危机影响最严重的行业之一。首次置业者、弱势和贫困地区以及中小企业受到很大影响。英国金融表示，200万个还款假期增加了运营成本，贷款人已经撤回了近三分之二的产品，其LTV超过75% （Williams， 2020年6月）。这一创新在许多方面有助于实现更可持续的融资。首先，无纸化将带来环境效益。通过更简单和精简的流程，员工可以被重新部署到需要更多人际互动的地方，提供社会效益、更高的客户满意度和更少的声誉风险，并在现场检查时获得监管机构的好感。这将带来更有利的治理效益。总的来说，这项创新非常符合ESG框架。交易成本的降低应该会带来更实惠的信贷供应和金融稳定。这项创新将利用金融BERT和GPT3\等先进技术实现抵押文件的一次性学习。通过利用大规模并行处理的创新软件架构和工程，可以在文档和跨文档级别实时、大规模地验证提取的数据。总而言之，创新项目是在新冠肺炎疫情后实现更可持续融资的一种手段，兼顾了环境、社会和治理方面的考虑。

Digilytics is a fast growing UK-based SME specialising in Artificial Intelligence. Digilytics is led by Arindom Basu, a technology entrepreneur with 30 years' experience in developing and introducing disruptive technology in financial services. The mortgage application process is a complex and lengthy funding process. The mortgage origination process alone involves the manual processing of around 100 different types of paper documentation. Multiple duplications can occur and errors lead to lengthy and unnecessary delays. Digilytics' innovation will combine computer vision, machine learning and NLP technology to create first-time-right mortgage applications at scale.In May 2020, the Bank of England warned that the UK economy is facing the sharpest downturn since 1706\. The mortgage sector has been one of the worst-affected sectors by the COVID-19 crisis. First-time home buyers, vulnerable and underprivileged areas and SME businesses have been greatly affected. UK Finance states that the two million repayment holidays have increased the cost of operations and lenders have withdrawn almost two-thirds of their products representing over 75% LTV (Williams, June 2020).The innovation contributes to more sustainable financing in a number of ways. Firstly, going paperless will lead to environmental benefits. With a simpler and streamlined process, employees can be redeployed to where more human interaction is necessary, providing social benefits, greater customer satisfaction and less reputational risk as well as favourable views by regulators during on-site examinations. This will lead to more favorable governance benefits. Overall, the innovation fits very well within an ESG framework. The reduction in transaction costs should lead to more affordable credit availability and financial stability.The innovation will achieve one-shot learning of mortgage documents leveraging advanced techniques such as Financial BERT and GPT3\. Validation of extracted data at document and cross-document levels in real-time and at scale will be made possible through innovative software architecture and engineering that leverages massively parallel processing.In summary, the innovation project is a means to more sustainable finance post Covid19 incorporating environmental, social and governance concerns.