Financial service companies are now betting big on data

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MUMBAI: Many banking, financial services and insurance (BFSI) players have turned data worshippers. Data can precisely map demographics, individual preferences and financial tendencies that help risk projection and customer relationship management.

And the field is vast and diverse from private weather bureaus to food app payment gateways, telecom bill payments and even social media records.

Take meteorologist Jatin Singh and his team. They pore over hundreds of drone captured pictures and satellite images to map agriculture across central India. The founder of Skymet Weather Services demarcates farmlands on the basis of government records and uploads them onto a platform secured by a pay-wall.

Banks and insurers are Skymet’s clients. “Over the next few months, we’ll cover other regions too… This data is turning out to be very useful for banks,” says Singh, whose reports have helped lenders disburse over 10,000 crop loans.

Drone-captured images, acreage data, yield prediction, market price analysis and weather forecasts arms Skymet’s clients to price their risk suitably, besides cross sell opportunities — to wheedle a prosperous farmer to apply for a tractor loan or mark up his personal insurance cover.

Data has changed the way BFSI operate. Data analytics has become the key determinant in matters pertaining to core BFSI operations, risk projection and customer relationship management.

“Data is now used across the customer value chain… It helps us to ‘hyper-personalise’ our products and services,” admits Abonty Banerjee, chief digital officer of Tata Capital.

Tata Capital uses data across functions — and almost indispensably in ‘collection analytics’, which helps the NBFC to put its money back on time. Tata Capital created a model on basis of debtor responses to collection calls. Factors such as — did the debtor promise to pay on a specified date, did he act upon his promise, number of failed contact attempts, number of successful contact attempts, borrower reaction while on call with collection agent et al were used to create the model.

While most BFSI players use credit bureau records even for routine business decisions, the niftier ones also run ‘alternative data’ checks on the customers. Alternative data could be sourced from anywhere — from private weather bureaus to food app payment gateways, telecom bill payments and even social media records.

THE BIG ALTERNATIVE
L&T Finance, a large lender with a rural focus, uses secondary data (rainfall, reservoir levels and irrigation coverage) to formulate business strategies. It helped the L&T slash default rates by 64% since 2017.

“This is precision bombing, and not carpet bombing… Data and analytics help us to do just that,” said Dinanath Dubhashi MD-CEO of L&T Finance.

Shriram City Union Finance underwrites nearly ?200 crore of personal loans monthly solely on data analytics and relies on alternative data sources to evaluate customers. The NBFC peeps into social media accounts of its borrowers prior to closing a loan deal and is wary of lending to 25-year-olds who spend hours on Facebook during work hours. Shriram City also stays away from borrowers who update their LinkedIn job profiles every so often.

“Credit bureau numbers are not of much use to us. I get to know a lot more about customers looking at external data points. I can predict a customer’s repayment pattern and free cash flows through proxy data. With these data points, I am able to lend to a person with a credit score of 550,” said V Lakshmi Narasimhan, executive director at Shriram City Union Finance.

NEW DATA PLAN
New-age insurer Acko General Insurance is primarily driven by data, analytics. It has 200 employees. A year ago it launched ‘Ola trip insurance’ a year ago — a one-rupee cover for Ola cab users against missed flights, accidents and baggage losses — designed solely by reading data.

Acko built a lot of ‘possibilities’ using data modelling tools. Most of the time, Ola customers missed flights due to unexpected traffic blocks or client delays (Ola customer delays); baggage losses and accidents were rare, Acko found out. These summations were the outcome of processing several micro-data bits such as Ola accidents-per-day, driver delays, customer delays, missed flight records and baggage loss complaints.

“Wherever data was not available, we considered relatable proxies,” says Animesh Das, product strategy head at Acko GI. Acko has processed close to 2,000 Ola trip insurance claims over the past eleven months and Das said the product is sustainable at the premium of ?1.

Acko also offers a data-modelled car insurance product — which differentiates between a 22-year-old unmarried collegian and a 40-year-old married man who both own cars. So, a collegian commuting to his college in Delhi from Gurugram daily and is frequently booked by traffic police, he is likely to pay more premium than a middle-aged car owner from Lajpat Nagar who drops kids to school before reaching office.

RattanIndia Finance, a new-age NBFC, uses alternative data for customer acquisition and loan underwriting. It uses foodapp payment receipts, Ola-Uber billings, online seller receipts to predict client cash flows — mostly SMEs and individuals. “We’re a new entity, without much captive data… So we mine data from alternate sources — much like what other fintech companies are doing now,” says Amit Mande, retail & SME head, RattanIndia Finance.

Puneet Kapoor, senior executive VP at Kotak Mahindra BankNSE -0.95 %, likens data to oil and gold. “We started using data to understand cross-sell opportunities within our customer pool,” says Kapoor.

Kotak has tempted a lot ‘cash-withdrawing customers’ to its digital platform, given personal loans to customers with “lower-than-usual” cash balances, home loans and locker facilities to those who turned individual accounts to jointly accounts (usually post marriage) and consumer durable loans to those changing their mailing addresses.

Mahindra Finance has built ‘Bharat-Maps’, a data-driven financial and consumption map, to track consumption, lending patterns and also target micromarkets to reach out to new customers.

Data is taking centre-stage in investment management too. Accuracap Consultancy, with a ?1,000 crore PMS book, is solely managed using quants and algorithms. The founders of Accuracap are software engineers who held senior positions at Adobe.

“We use data modelling tools and algos to pick stocks… These engines also tell us at what point to enter or exit specific counters,” says Raman Nagpal, CIO, Accuracap.

Accuracap could spot very lucrative entry and exit points in stocks such as TTK Prestige, HCL Tech and Venky’s, among others. The fund has logged a yearly return of close to 8%, almost mirroring the BSE-100 index and beating ‘category averages’ of 3.8%, Nagpal claims.

“We don’t let human emotions come in the way of investing… This strategy has helped our investors,” Nagpal says.

“Qualitative inputs could mitigate risk, reduce operational cost and enable faster rollout of appropriate products to targeted customer groups,” says S Siddhartha, CEO of Intain Technologies, which offers artificial intelligence and blockchain solutions to BFSI players.

[“source=economictimes.indiatimes”]