The role of Big Data and Machine learning in Financial Services Industry

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The Financial service industry produces a massive amount of data. Banks have internal data on deposits, payments, balances, investments. Then there is external data form websites, social network data and government data. Tech-savvy millennials prefer digital platforms all adding to Big data.

Business Analysts have been using data to understand what is happening. Data scientists use machine learning to tell us why and how it happened and make predictions.

Applications of Big data & ML in Financial Services Industry

Loan Processing –

ML tool can take a call on creditworthiness. Risk analytics can make immediate decisions on customer loan eligibility. Imagine your Loan getting processed in minutes. Deserving Loan applicants would get approvals faster, while bad loans will be reduced.

Customer Service –

Data collected from chatbots and IVR’s can help improve customer services. Instant customer profiling can help cross-sell or up-sell and reduce the burden on the sales team.

Fraud Detection –

A neural network program can detect fraud in real time by using input data. This can block the bank card in seconds of the fraudulent transactions and avoid losses. The Flagged card is then verified by a human.

Better Financial Products with Better Price Points –

A McKinsey Global Institute Report found that marketing and sales consume about 15 percent of costs for banks. Big data will help to arrive at better products and price points. This will increase revenue and margins in the competitive financial services industry.

Market Prediction –

The need to analyse Big Data arose in the aftermath of the 2008 financial meltdown. Big Data can make accurate future market predictions.

RegTech –

ML tools can be programmed to follow protocols to comply with regulatory requirements which are labour intensive. This improves the back office efficiency as about 70–80% percent of the bank staff are in back offices.

Applications in UAE

On 19th October UAE appointed its first Minister of State for Artificial Intelligence (AI). The government will need to collaborate with private businesses on private public partnership (PPP) format to achieve it’s Artificial Intelligence Strategy 2031.

Mashreq is using AI for customer service with chatbots which answer basic queries. Emirates NBD has its bilingual robot which converses in English and Arabic and voice-enabled EVA which answers basic queries. Read more here.

Challenges

Banks are currently overwhelmed by their internal data. Also, siloed legacy systems are not equipped to process big data. The unavailability of higher skilled data scientists is also a hurdle. Financial services industry will see a big change in coming years in the field of Big data and the blockchain tech. A study by Juniper predicts that Fintech industry would grow up to 10 folds by 2022. World Retail Banking Report, 2016, states that Banks that apply analytics to customer data have a 4% point lead in market share.

Privacy is going to be the elephant in the room. What data is ethical to analyse, do we need explicit permissions? Yes, It is our duty to inform customers what personal data is being mined and for what purpose.

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About the author

Financial advisor to UHNWI, private entities, family offices, and companies. Certified Anti-Corruption Manager from The American Anti-Corruption Institute

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