Article | February 19, 2020
Technology has always been the main force behind changes in the banking sector, and now the Internet of Things is going to change the nature of banking itself. If we step back from such isolated technologies like blockchain or the smartphone and try to see the global picture, we easily notice that something is changing, and that’s the way of global digitalization in the financial sector.
Article | February 19, 2020
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.
Article | February 19, 2020
In the ongoing technological era, the outsourcing software development company transports their valuable resources to their core business model and helps businesses to save a lot of time and money. To survive the digital era for financial institutions helps to drive efficiency in Fintech companies. Moreover, software development outsourcing companies offer solutions that enable financial institutions to manage bulk data, tech products, and much more to build an efficient environment with their tech services.
The financial service industries are becoming a leader in software development and corporate new strategies for fintech businesses. Many companies are planning to use this working model that is specialized in all processes and seek more agility and quality.
Outsourcing software development to the fintech industry can bring many gains to companies, so, in this blog we’re going to look at them closely. According to research, investments in fintech are expected to reach $40 billion in 2021. Additionally, software outsourcing companies makes the development process smooth and improves the quality of data analytics in the industry.
Read on to know the benefits of outsourcing software development to the fintech industry and achieve the dedicated digital transformation goals of your business.
What Are The Benefits Of Outsourcing Fintech Software Development?
Expand your business development
The benefits of outsourcing software development services creates a pleasing and commending condition for the fintech industry. It becomes easier to execute actions and plan for the company’s expansion if the management focuses on the core business and internal quality processes.
Additionally, the development service provider also helps to sustain the growth of the operation without investing huge investments in infrastructure and technology.
Economies of scale
If you’re planning to internally develop a software application requires both money and time. And not everyone has an extended IT team with dedicated developers. In such situations, software development outsourcing companies become your partner. The services provided by software outsourcing agencies for fintech development helps businesses to achieve economies of scale and allow them to invest more time on core competencies and perform critical tasks.
However, software development outsourcing offers competitive advantages to fintech industries by minimizing costs, better customer service, and maintaining product quality with an affordable budget.
Optimize time for dedicated professionals and managers
Hiring outsourcing software development services helps businesses a practical and sensible optimization of the time of professionals and managers. If your business is planning to enhance the process of professionalism.
To such a degree, fintech industries can directly help to increase the capital and implement strategic tasks and analyze surveys that collaborate to make the right decisions. Thus, outsourcing software development helps to monitor indicators and supervise the possibility of risk to the company.
Risk Management/ Critical-path method
IT outsourcing software development service providers carry a lot of risks. So to grab the absolute advantages, an organization should build effective risk management plans.
Reducing the number of data breaches is one of the most important challenges faced by many fintech industries. This challenge is even more critical when you consider the information type such as salaries, credit card information, social security numbers, and much more which can be used by criminals for gaining profit. Various components and operations help to reduce risks and provide a successful path for outsourcing when you know the challenges and tackle the situation.
Increased profits through data analytics
Finance is the leading data collection and analytics industry that helps to increase software profit via data analytics. Popular investment banks like Goldman Sachs and JPMorgan have employed specialists who analyze data when issuing trading futures.
These fintech software development industries are now identifying customer data and helping them to increase sales and promote customer loyalty. To analyze creditworthiness and provide services to each customer they use credit scores and demographic data that also helps them to build analytics software with the Python programming language.
Reduce software server load via cloud computing
To implement cloud computing technology, the fintech industry has been reluctant to use web-based storage for bulk data which is vulnerable to hackers. There are few improvements in data security that have led banks to begin integrating modern technology into their core business functionalities.
To store sensitive business information related to accounting and communications, many banks are using cloud computing. In recent years, it is reported that the SaaS model is one of the best models that is implemented by fintech software enterprise to store emails, contact lists, and other important information online.
Faster product development
Hiring software outsourcing companies helps fintech industries to start your projects quicker and complete them before the deadline. The outsourcing enterprise implements traditional hiring processes for software development projects and instructs those dedicated developers to perform critical tasks who can start product development without investing much time on the hiring process.
The dedicated team of developers working at any outsourcing companies help to shorten the fintech software development lifecycle and work on multiple projects to quickly resolve common problems and reduce the overall length of the software.
The fintech enterprise is investing millions of dollars to build custom software according to their business requirement to survive in the new data-driven marketplace. Leveraging a fintech software development service is much bigger than just launching a system that enables the creation of innovative fintech solutions in the future.
Many of these companies are switching to fintech software development that provide a dedicated development team to perform critical and complex tasks of any software and reach their goal without distracting from their core missions.
Article | February 19, 2020
Here are ten steps to defining a data strategy based on a data capability maturity assessment, for a Financial Institution, Identify and Simplify Maturity models, and customize the yardstick as well as benchmarks based on local study and future organization strategy. Conduct workshop with leaders and grassroots to sensitize the assessment and questionnaires.