Fighting financial crime at IBM Think 2018

DWIJ CHATTERJEE | March 13, 2018

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Regulatory pressure, in terms of policy changes and increased scrutiny, is forcing banks to seek technological changes and advancements to meet evolving regulatory and compliance requirements. This is resulting in financial institutions spending heavily on KYC, AML and surveillance solutions. IBM is committed to bring the newest and best advances in technology to tackle these challenges.

Spotlight

OneSavings Bank plc

One Savings Bank plc floated on the London Stock Exchange main market on 5 June 2014. The Group, which is headquartered in Chatham, Kent, is a specialist lending and retail savings group serving the UK, Jersey and Guernsey, and is authorised by the PRA, part of the Bank of England, and regulated by the FCA. The Group focuses its specialist lending activities on selected sub-sectors of the lending market in which it has an established presence and expertise. The Group’s specialist segments include Residential and Buy-to-Let/SME Mortgages. The Group’s other specialist segment is Personal Loans. The Group originates almost all of its organic lending through specialist intermediaries. One Savings Bank lends through the Kent Reliance and associated Channel Islands brands, InterBay Commercial, Prestige Finance and Reliance Property Loans brands.

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DEMYSTIFYING AI IN BANKING: THE CASE FOR A UNIFIED STRATEGY

Article | June 4, 2021

Digital transformation can mean different things to each financial institution (FI). For some, it’s a push to modernise legacy systems and acquire fresh talent. For others, a journey to adopt an organisational strategy that unites departments and teams. No matter the motive, nearly all FIs want the same result—to drive efficiency, revenue and cost savings. For many forward-thinking FIs, artificial intelligence (AI) is a key part of this process. At first, implementing AI can feel like an arbitrary effort that requires too many stakeholders, too much technology, and too big a transformation. Yet, as AI in banking matures, it brings the potential for higher-complexity solutions that generate positive ROI across business segments. A recent financial services study showed that 85 percent of respondents had successfully implemented AI within their organisation. [i]An additional 64 percent plan to use AI across a wide variety of use cases including process automation, risk management, and new revenue generation. These studies prove that AI is not only becoming more mainstream, but is necessary to help FIs achieve their business goals, strengthen customer relationships, and remain competitive. To demystifying AI and reap its benefits, FIs must embrace a multi-functional strategy that sparks innovation and encourages collaboration. The three use cases below show how AI can be implemented to most immediately impact a financial services organisation. Elevating employees, not replacing them AI has historically created fears of job loss and obsolescence. However, within financial services, AI is well equipped to automate manual and repetitive tasks - such as rekeying data - rather than autonomously make critical financial decisions on behalf the organisation. Due to the complexity of the decisions, degree of regulation, and importance of qualitative factors these tasks are – and for the foreseeable future will be – better managed by employees. A key use case of AI for automation is the utilisation of optical character recognition to streamline the process of spreading financials when underwriting commercial loans. Previously, credit analysts would have to invest hours painstakingly transferring borrower financial data into various systems, reducing time for holistic credit analysis and increasing loan underwriting times. However, by employing AI-driven solutions in combination with powerful workflow automation, banks have been able to significantly increase efficiency in lending processes, reducing processing and cycle times by more than 50 percent and seeing a 10 percent increase in front-office capacity to focus on true value-add analysis and customer relationships. [ii] Additionally, AI has the ability to empower bankers, not only by eliminating manual tasks, but also by being able to equip them with powerful insights around relationship profitability and credit risk. By refining sophisticated, machine-learning based models, banks can more accurately predict and leverage metrics such as probability of default and loss given default within risk-based pricing models to provide competitive lending rates to borrowers, while still maintaining healthy profitability at the relationship and portfolio level. Reshaping customer engagement The acceleration of digital banking due to the COVID-19 pandemic and the rise of customer-centric titans have put significant pressure on financial institutions to modernise and reshape their approach to digital banking to appease rising customer expectations. Customers not only expect a frictionless and seamless onboarding process, but for their bank to act as an ever-present financial advisor, offering personalised insights on spending habits, money management and financial decisions. AI-powered virtual assistants and chatbots offer new levels of accessibility to common questions by utilising natural language processing to find past transactions, access credit scores, and view balances. However, institutions can take a further step of both anticipating customer needs and offering targeted product suggestions based on propensity scoring models. Proactively offering recommendations can be helpful to customers due to the complexity of different financial products and enables banks to simultaneously satisfy customers while unlocking new revenue opportunities. FIs can leverage AI to operate as a dedicated advisor, offer a differentiated customer experience, and reduce customer churn. However, equally important to the underlying predictive models is having a single, end-to-end platform to drive direct actionability by delivering insights to the right banker at the right time. Boosting back-end efficiency In addition to empowering employees to focus on true value-added activities, AI offers enhanced methods to improve operational efficiency and risk management. Analysis of IDC data shows that AI technologies can improve the cost efficiency of financial institutions by over 25 percent across IT operations[iii]. As a part of fraud detection, institutions can leverage AI to oversee thousands of transactions and efficiently flag anomalies that are indicative of fraud. Historically, transaction monitoring has struggled with false positives, through which genuine transactions are incorrectly flagged. However, through machine learning, actual, fraudulent transactions can be compared to false positives, which can then be fed into the model, improving accuracy over time as the system incorporates learned, differentiating factors. Finally, the COVID-19 pandemic has caused institutions to revaluate how they assess credit risk and problem loan management. Lenders have had to segment their portfolio by geography and industry to differentiate sectors which were more severely affected by the pandemic versus those that were less challenged. Additionally, there is now a greater emphasis on utilising real-time and transactional data in addition to other data sources to truly understand business performance and borrower resilience. As the uncertain pandemic recovery continues, leveraging AI-powered predictive models in combination with delinquency tracking, credit migration modelling, and other tools will continue to be critical to align actual portfolio risk with the risk appetite of the institution. As AI adoption continues to mature, FIs should avoid sporadically focusing on isolated use cases. Instead, organisations should strive to align strategy, organisational culture, and digital infrastructure under a united AI strategy. This will help enable them to capitalise on revenue growth, operating efficiency and cost savings, from the front to the back office, and across all lines of business.

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Taking Advantage of AI and ML in Financial Services

Article | June 4, 2021

Many financial services organizations have already begun to take advantage of ML technology because of its proven ability to reduce operational costs, increase revenues, improve productivity, enhance compliance, bolster security, and enrich the customer experience. However, most companies are in the early stages of exploiting the benefits of ML.

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Collateral Business Loans: What You Need to Know

Article | June 4, 2021

It’s a fact: to succeed in business, sometimes you need to borrow money to keep cash flow steady. But what do you do if you have bad credit? What business financing options do you have? Not to worry. Even if your business and personal credit scores are too low to qualify you for traditional business financing, you still may qualify for a secured business loan with the right lender, also called a collateral business loan.

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A bank account - A concept of the past

Article | June 4, 2021

Almost every recent article written about banking starts with the statement that the banking industry is being disrupted by new competitors, new innovations and new technologies. Although this statement is definitely true, the extend of the disruption can still be debated. Even the most innovative neo-banks still work with bank (current, saving, term and investment) accounts, cards (credit and debit), traditional credits, existing payment infrastructure… The user experience surrounding the origination and servicing of these products has dramatically improved (and will continue to evolve), but the underlying banking products are not really disrupted.

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Spotlight

OneSavings Bank plc

One Savings Bank plc floated on the London Stock Exchange main market on 5 June 2014. The Group, which is headquartered in Chatham, Kent, is a specialist lending and retail savings group serving the UK, Jersey and Guernsey, and is authorised by the PRA, part of the Bank of England, and regulated by the FCA. The Group focuses its specialist lending activities on selected sub-sectors of the lending market in which it has an established presence and expertise. The Group’s specialist segments include Residential and Buy-to-Let/SME Mortgages. The Group’s other specialist segment is Personal Loans. The Group originates almost all of its organic lending through specialist intermediaries. One Savings Bank lends through the Kent Reliance and associated Channel Islands brands, InterBay Commercial, Prestige Finance and Reliance Property Loans brands.

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