{"id":31581,"date":"2020-01-22T09:59:19","date_gmt":"2020-01-22T09:59:19","guid":{"rendered":"https:\/\/www.intelligentcio.com\/africa\/?p=31581"},"modified":"2020-01-23T14:53:25","modified_gmt":"2020-01-23T14:53:25","slug":"ai-helps-unlock-data-potential-of-banks","status":"publish","type":"post","link":"https:\/\/www.intelligentcio.com\/africa\/2020\/01\/22\/ai-helps-unlock-data-potential-of-banks\/","title":{"rendered":"AI helps unlock data potential of banks"},"content":{"rendered":"\n

Artificial Intelligence (AI) provides banks with the means to make better use of the massive amount of data at their disposal. In doing so, they can identify opportunities for growth faster and gain significant competitive advantage at a time when more agile digital counterparts are emerging. Patrick Ashton, a Managing Executive at SilverBridge Holdings, believes that without this insight, it is difficult to modernise processes or to understand how best to introduce new technologies into back-end systems.<\/strong><\/p>\n\n\n\n

When it comes to product development, the offerings of banks typically evolve slowly over time. Part of the problem is that legacy mainframe systems are expensive and AI helps unlock data potential of banks to update while people resources for these systems are scarce (and becoming more so). <\/p>\n\n\n\n

This creates a\nbottleneck in the process as the mainframe systems are typically the central\nrecord for all data. This means they must form part of any new solution\ndeveloped. Front-end applications are relatively quick to develop but back-end\nintegration or changes to core systems become the stumbling block.\u201d<\/p>\n\n\n\n

Banks must\ntherefore work with experienced and trusted partners to extract data from\nmainframes into modern database architectures that can use the data more\neffectively. <\/p>\n\n\n\n

In most\ninstances, curated data extracts taken from the mainframe are very large,\nmaking it difficult for individuals to work with. These are typically put into\na spreadsheet format for users to work with. However, this is inefficient,\nprone to error and carries significant risk due to human involvement.<\/p>\n\n\n\n

Instead, banks\nneed the ability to extract their data and present this to users in a modern\napplication interface for task processing. Risks are managed better, and\noperational efficiencies are dramatically improved when simple rule-based\nactions and decisions are removed from the human function.  <\/p>\n\n\n\n

People can then\nbe empowered to add higher levels of value into processes through the analysis\nof data insights gained, a better customer-centric service model and\nre-imagining of traditional processes. AI-led technologies enable this\ntransformation. <\/p>\n\n\n\n

Of course, all\nof this must be done within a strong governance framework. It is about building\nrobust solutions that involve risk officers from early in the process to ensure\nall the necessary requirements are taken care of.<\/p>\n\n\n\n

Transforming\ninsights<\/strong><\/p>\n\n\n\n

Getting insights\nfrom data is the first step to understanding where efficiency can be built into\nthe internal processes of banks. In many instances, banks have been relying on\nthe same data processes put in place decades ago. These have gradually been\ntweaked over time without major overhaul. Adoption of new technologies tends to\nbe slow resulting in toolsets, like traditional spreadsheets, remaining the\nprimary environment used to analyse datasets. However, this is neither\nefficient nor secure.<\/p>\n\n\n\n

Even so, one of\nthe most significant challenges revolves around exception handling. Most\nbanking transactions require little human intervention. However, in cases where\nitems are flagged (for example, AML, fraud or screening checks), this requires\nhuman intervention. Given the high volumes involved this comes at significant\ncost to the organisation.<\/p>\n\n\n\n

It is therefore\nan excellent place to deploy new AI technologies such as Intelligent Process\nAutomation (IPA). This streamlines processes and automates steps usually\nperformed by people. Think of AI virtualising the human experience. It is about\nbuilding technology solutions that consider the exception handling process and\nautomate as much of this as possible, introducing efficiencies and mitigating\nrisk simultaneously.<\/p>\n\n\n\n

Furthermore, in\nmany instances, banks require multiple levels of human approval for\ntransactions to be cleared. This is another time-consuming process that can be\ntransformed through AI. Instead of having two or three people view each\ntransaction, the AI process can deliver the same level of expertise\nconsistently in real time to improve SLA management and improve service to\ncustomers.<\/p>\n\n\n\n

It is not about\nreinventing the wheel but optimising the robust processes banks already have in\nplace when it comes to managing their data and processes. Through refining and\nautomation of processes, a significant amount of human activity can be taken\nout of the system and this can be repurposed to give the bank more capacity to\nfocus on areas such as improved customer service or the design of new\nofferings.<\/p>\n\n\n\n

Modern practices<\/strong><\/p>\n\n\n\n

Using modern\napplications that can integrate with existing data and processes, banks are\nable to generate insights from start to finish. <\/p>\n\n\n\n

For example,\nlook at the typical ATM infrastructure that must be managed daily. Transactions\nand GL account balances must be reconciled to ensure machines are working\ncorrectly, that no fraud is taking place, and there is always the right amount\nof cash available for banking customers without over exposure of capital\nreserves. <\/p>\n\n\n\n

Using people to\nreconcile and investigate discrepancies is slow and inefficient. But using AI\ntoolsets mean these tasks can be managed consistently, at high speed and with\nfull auditability. Volume or capacity constraints are then no longer an issue. <\/p>\n\n\n\n

This extends\ninto customer service as well, improving the customer experience when queries\nor complaints arise as there can be immediate action taken rather than waiting\nfor a human to perform analysis and then take a decision.<\/p>\n\n\n\n

An AI layer can\nbe implemented to sit on top of existing processes while integrating into\nback-end legacy systems to deliver the value banks require. Banks have high\nquality data, but it is not always accessible. Using AI to help manage the high\ndata volumes can bring about significant improvements in operational efficiency\nwhich will ultimately deliver a better customer experience.<\/p>\n","protected":false},"excerpt":{"rendered":"

Artificial Intelligence (AI) provides banks with the means to make better use of the massive amount of data at their disposal. In doing so, they can identify opportunities for growth faster and gain significant competitive advantage at a time when more agile digital counterparts are emerging. Patrick Ashton, a Managing Executive at SilverBridge Holdings, believes […]<\/p>\n","protected":false},"author":25,"featured_media":31583,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[4950,565,275,399,183,262],"tags":[496,12343,386,1818,8144,12344,8209,1926,4386],"class_list":["post-31581","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analysis","category-banking-finance","category-intelligent-technology-newsletter","category-more-news","category-software","category-used","tag-ai","tag-aml","tag-artificial-intelligence","tag-atm","tag-intelligent-process-automation","tag-ipa","tag-patrick-ashton","tag-silverbridge-holdings","tag-sla"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/posts\/31581","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/users\/25"}],"replies":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/comments?post=31581"}],"version-history":[{"count":8,"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/posts\/31581\/revisions"}],"predecessor-version":[{"id":31592,"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/posts\/31581\/revisions\/31592"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/media\/31583"}],"wp:attachment":[{"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/media?parent=31581"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/categories?post=31581"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/africa\/wp-json\/wp\/v2\/tags?post=31581"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}