USE OF ARTIFICIAL NEURAL NETWORK FOR THE SELECTION OF SALES INTERMEDIARIES

Recently, compliance and regulation has been number one threat; not only for the area of financial services, but also across a spectrum of sectors, ranging from oil and gas, through life sciences and technology to automotive. The main reason for the tougher stand against corrupt business practices is the increased enforcement actions against companies. When companies go global and extend their network in different countries, they will surely get into business relationships with third parties, especially sales intermediaries. Therefore, all companies have to pay special attention to the selection process of their ethical business partners. A systematic detailed check of the prospective sales intermediaries questioning their economical, legal and ethical aspects, aiming to reveal any issue which could cast doubt on the integrity is called due diligence. This costly examination usually carried forth by external professionals has become a business standard of almost all multi-national companies. In this study, a practical decision support tool using pattern recognition of artificial neural networks is developed to assist companies in their selection of sales intermediaries by way of minimizing any future risk of a compliance and regulation violation, which could result in severe sanctions and punishments against such companies