Most AI Applications that have real-world business significance for debt collection [today]

Today seem to be in personalizing communications to customers and identifying clusters of similar debtor profiles.

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According to the Consumer Financial Protection Bureau, Americans filed more grievances about debt collections than about any other financial incident. Of the 316,810 complaints received by the CFPB about debt collection in 2017, the most common was, “Continued attempts to collect debt not owed,” which was cited by 39 percent of grievance filers.

Debt collection in finance is starting to be disrupted by artificial intelligence due to the availability of massive amounts of historical records of customers for banks and other financial institutions. Most AI applications that have real-world business significance for debt collection today seem to be in personalizing communications to customers and identifying clusters of similar debtor profiles.

From our research we have segmented the AI applications for debt collection into the following broad segments:

  • Driving Additional Messaging Campaigns
  • Customer Service (Debtor) Personalization
  • Debt Management Service

We delve further into each of these applications and aim to coax out the need-to-know factors for business leaders regarding AI usage for debt collection.

Driving Additional Messaging Campaigns

Tailoring interactions to debtor habits could be possible with AI today. Virtual assistants are starting to be deployed through channels in which collections agencies can reach out to debtors through email SMS, and outbound dialing, allowing organizations to increase the number of individuals that they’re able to contact on a daily basis.

TrueAccord

TrueAccord was founded in 2013 in San Francisco and claims to be offering an AI-driven debt collection solution. The 97-employee company claims to be offering debt collection solutions to banks, eCommerce and telecom companies.

TrueAccord claims that their decision engine uses machine learning to create digital interaction experiences that are customized for each debtor. The company claims its platform can create an interaction model for each debtor.

TrueAccord claims this model provides banks with the best possible channel and time to reach out to existing and new debtors which might eventually result in better debt revenue collections.

The company says more than 1.5 million debtors have already been modeled using their platform. Based on these existing debtor profiles, their software claims to predict an individual’s response time, schedule, best communication channel, and type of content that they’ll respond to.

TrueAccord adds that its decision engine can automatically select the appropriate pre-approved messages from banks to deliver to debtors. The software also tracks, in real time, the action events from the debtor, such as interaction with call centers, or email opens, link clicks and browsing patterns on TrueAccord assets. The software then sends this data to employees at debt collecting agencies so they can plan the ideal style and time of their next message.

What channel the next message should likely https://goo.gl/gGHvYg

Authorities by transferring relatively small amounts over time

Can this information help diagnose important problems, or detect trends that might help the car company improve its products?

Natural language processing (NLP) has become popular in the past two years as more businesses processes implement this technology in different niches. In inviting our guest today, we want to know specifically which industries, businesses or processes NLP could be leveraged to learn from activity logs.

For instance, we aim to understand how car companies can extract insights from the incident reports they receive from individual users or dealerships, whether it is a report related to manufacturing, service or weather.

In the same manner, how can insights be gleaned from the banking or insurance industries based on activity logs? We speak with the University of Texas’s Dr. Bruce Porter to discover the current and future use-cases of NLP in customer feedback.

Expertise: Machine reading, natural language processing

Brief Recognition: As SparkCognition’s Chief Scientist, Dr. Bruce Porter leads the company’s research and development initiatives. He was a two-time chair of the University of Texas, Austin Computer Science department, recently returning to his role as a professor at the university to focus on teaching and research. In 2017, the Austin Chamber of Commerce recognized Dr. Porter, with the Economic Development Volunteer of the Year award for his work in recruiting technology companies to build and innovate throughout the economy across the Austin region.

Big Idea

Many companies and government agencies are deluged with incident reports, customer logs, and information coming in the form of text. To gather insight from these logs, Dr. Porter coined the term “macroreading”, which refers to the detection of patterns in huge masses of unstructured text.

Example 1: Improving Customer Experience in the Auto Industry

In the automobile industry, imagine that a car company receives incident reports on a daily basis car owners or car dealerships. These reports consist of a paragraph or two of text describing a problem that the customer has experienced with a particular car. These incident logs have unstructured information. They come in the form of text, diagrams or pictures. They can also include metadata such as the occasion and other incident details that are structured, Dr. Porter clarifies.

The question is: Can the car company mine the text reports to find patterns at the macrolevel and discover what is happening with the cars in a particular model and year? Can this information help diagnose important problems, or detect trends that might help the car company improve its products?

Data entry might vary widely across different parts of the automotive industry. Car incident reports could be typed if they are received by someone in the office. Technicians in the field could be using audio devices to report a problem. A business with the ability to find patterns and across all of these different data types would be better prepared to find and address problems and opportunities quickly.

Example 2: Preventing Financial Fraud and Money Laundering

Dr. Porter brings us to the financial sector for his second example. He explains that wire transfer reports come with meta information such as the certain amount of money being moved, as well as the source and destination of the wire transfer. The report also contains text information about the nature of the wire transfer and the relationship of the money sender to the bank. In this, a macroreading application has the potential to uncover fraud and money laundering activities.

Dr. Porter further explains that developing a banking application for the government can be challenging, primarily because such an application requires a large quantity of data. That the application could potentially be used as an investigative tool requires it to be a deep, robust system. The application must have the capability to show interrelated actions and participants over time, which when taken together reveal a pattern of suspicious behavior.

Citing money laundering as an example, Dr. Porter explains that one pattern shows a small business such as a car wash or a laundromat collecting cash, and then wire transferring large sums of money through accounts owned by these small businesses (with the intention of “flying under the radar” of authorities by transferring relatively small amounts over time).

Dr. Porter forecasts that industries that would need this kind of insight in the next five to 10 years would be those with significant investments in equipment that is distributed globally. The company would be receiving reports on a regular basis, either hourly or daily, of how that equipment is performing. The challenge for the company is detecting failures early before they get out of hand and meeting the regulatory obligations for large industries.

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Axsesstoday rides the alternative finance boom

The increasing popularity of alternative lenders such as Axsesstoday comes as the Financial Services Royal Commission.

Small business lender Axsesstoday’s half year results showed an increase in its profit after tax to $3.2 million as the alternative lending market grows in popularity.

Axsesstoday focuses on financing in the hospitality and transport sectors and increased its market share with receivables up by 53 per cent over 30 June 2017 to $265 million.

Founded in 2012, the specialist provider of equipment finance listed on the Australian Securities Exchange in 2016 after growing its loan receivables book from zero to over $52 million in four years.

Banking-Leadspace-Animated

For businesses in the hospitality sector Axsesstoday typically offers financing for coffee machines, display units, cooking, refrigeration and dishwashing equipment.

For businesses in the transport sector it finances second-hand trucks, trailers, forklifts and other light trade vehicles.

Co-founder and chief executive Peter Ferizis, says Axsesstoday has built its business by offering an alternative for small businesses.

“We are moving away from finance being a commoditised product to offering a unique value proposition and a unique and proprietary IT core system,” he says.

The increasing popularity of alternative lenders such as Axsesstoday comes as the Financial Services Royal Commission (FSRC) began its public hearings on Monday with concerns about the major banks lending to small business on the agenda.

Insurance-Leadspace-Aniamted

“It’s very early at this stage to undersand what are the changes which might arise out of that,” Ferizis says. “What the Royal Commission means is that customers want to be heard and at the moment it is hard for SMEs to secure finance from the major lenders.”

Axsesstoday assesses small businesses by using algorithims and modelling specifically developed for the hospitality and transport sectors.

Enhanced here http://snip.ly/8z4cf

Brexit: May to meet UK financial services chiefs

We should use the imagination and ingenuity that our two countries and the EU have shown in the past, to craft a bespoke solution.

The Prime Minister is set to meet with business leaders from the UK’s financial services industry as the government attempts to secure a Brexit deal that will include the sector.

Theresa May will talk with Barclays’ chief Jes Staley and Goldman Sachs International boss Richard Gnodde among others on Thursday.

financial-services

The Chancellor Philip Hammond will also attend after travelling to Berlin.

He described financial services as pivotal to a “bespoke” trade deal.

In a joint-article for the Frankfurter Allgemeine newspaper on Wednesday, Mr Hammond and Brexit Secretary David Davis said that “the economic partnership should cover the length and breadth of our economies including the service industries — and financial services”.

They said: “We should use the imagination and ingenuity that our two countries and the EU have shown in the past, to craft a bespoke solution.”

Bloomberg reports that Germany is considering a plan that would give UK financial services companies access to Europe in exchange for payments to the EU budget.

Asked in Berlin if the UK would pay in exchange for bank access, Mr Hammond said: “We will talk about all of these things.”

Juncker: Don’t believe Brexit won’t happen

UK’s no-deal Brexit worries ‘surprise’ EU

Reality Check: Breaking down the deal

Senior executives from the London Stock Exchange will attend the regular meeting at 10 Downing Street along with Mark Tucker, chief executive of insurance group Aviva.

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Ways of applying operational risk management in banks

Because of this, operational risk management in banks is the highest priority for banks.

The banking sector should rank foremost among the many sectors of the economy that have undergone drastic changes in the last couple of decades or so. The convergence of two colossal factors – globalization and the development of technology – has made inroads into the banking sector, impacting it with a force that was seldom seen earlier.

The number one area of the banking sector to be affected by these changes is operations. Many factors such as credit, software, etc. need to be regulated for their risks. However, the core of the banking sector is operations. Because of this, operational risk management in banks is the highest priority for banks.

The Basel Accords

risk-operational

 

The primacy of operational risk management in banks can be understood from the fact that one of the most important regulations aimed at the banking sector, the Basel Accords, a series of plans to regulate the banking sectors around the world; has operational risk management in banks on top of its agenda. Operational risk management in banks is one of the four areas identified at the second of these conferences, Basel II, the others being regulations concerning capital allocation, disclosure requirements and regulatory arbitrage.

operationalRiskManagementInBanks

Operational risk management in banks according to Basel

The Basel Accord takes a very comprehensive view of operational risk. It describes operational risk as loss that can occur from a variety of reasons, all of which are linked to the core banking structure. The Basel Accord sees risk as something that can happen from any of the operations concerning the bank. It requires operational risk management in banks to take all of these factors into consideration before arriving at solutions to prevent loss from these operations.

pentaho

From the Basel Accords perspective, operational risk management in banks need to take into consideration the following events and identify all of these in identifying frauds and losses:

Internal fraud

Any fraud from any of the bank’s employees, insider trading, false reporting of profits are among the kinds of activities listed by Basel as being part of internal fraud.

External fraud

External fraud can happen from a number of sources. It could be robbery, burglary, hacking of security systems or check bounce. These are part of operational risk management in banks.

Employee fraud

Employees can be a major source of bank fraud. Steps towards mitigating actions from employees that endanger the functioning of the bank constitute a major step in operational risk management in banks.

Other kinds of frauds

Operational risk management in banks has to also take other sources of fraud. These can be from wrong entry of accounts, improper documentation for credit or loans, etc.

Ways of applying operational risk management in banks

Basel II has suggested methods which banks can take to apply risk management in their sector. These include:

operationalRiskManagementInBanks

HDFC Bank offers virtual accounts to PayZapp users

Fintech lending is the new kid on the block, which has brought a different way of sourcing customers for loans.

HDFC Bank will soon start offering digital savings bank accounts, credit cards and instant loans to users of its PayZapp app. The bank also plans to enrol additional merchants for acceptance of electronic payments to increase its present network of 1.2 million shops to 5 million in 18 months.

PayZapp, which was launched two years ago, has more than 14 million users. Over half of these are young users who do not have a bank account. “We are marrying a lot of our strategies by integrating changes that are happening in the market into our own business activity.

HDFC Bank is already a scale player in cards and loan assets. We will use our digital back-end strengths in these businesses to bring more scale into PayZapp,” said Parag Rao, group head for marketing, credit cards and payments business.

According to Rao, PayZapp has the potential to become a 50-million customer franchise with capability for instantly opening accounts and offering credit cards and loans.

HDFC Bank is already the market leader in credit cards with over 1 crore in circulation. It currently issues 2.5 lakh new cards every month. The PayZapp platform is expected to take this to 5 lakh a month. The offered savings account will be a completely digital product and the credit cards virtual, with an option to receive the plastic version. The instant loans would be powered by fintech (financial technology). “Fintech lending is the new kid on the block, which has brought a different way of  sourcing customers for loans,” said Rao.

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Ukraine Will Pursue Hard Reforms This Fall, Finance Minister Says

Ukraine’s macroeconomic indicators are good, and Danylyuk has become one of the more convincing reform voices within the government—and someone that Ukraine’s formidable civil society actually respects.

After a week of back-to-back meetings in Washington, Oleksandr Danylyuk is tired. He gladly downs a cup of coffee before we turn on our microphones to discuss Ukraine’s economy. The affable forty-two-year old finance minister is one of the few reformers left in Ukraine’s Cabinet of Ministers and has a reputation as a doer. He’s in town for the International Monetary Fund’s and World Bank’s annual meetings.

When Danylyuk took over after Natalie Jaresko stepped down in April 2016, expectations weren’t high, but he has exceeded everyone’s expectations. My colleague Anders Åslund captured it well: Danylyuk has “turned out to be the reform anchor in a government that has been less committed to reform than the previous government, and he has managed to keep the state finances in good order.”

The former investment banker managed to render elusive value-added tax refunds automatic, which pleases many foreign businesses, and has presided over a period of modest economic growth. In September, Ukraine returned to the international finance markets with the introduction of a $3 billion Eurobond, and analysts expect that there may be more offerings. Ukraine’s macroeconomic indicators are good, and Danylyuk has become one of the more convincing reform voices within the government—and someone that Ukraine’s formidable civil society actually respects.

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