AI can be utilised in many different ways when pursuing debt collection. Firstly, software engineered by LATERAL can harness predictive data and analytics to pre-empt debt delinquency by generating actions based on a customer's previous behaviour. Businesses can rely on AI to monitor, provide alerts and even automate responses when there are changes to any key data elements that constitute a customer's risk profile. Using statistical analysis of the historical data of those owing debt, AI can predict the most effective way to ensure a future response from those customers and contact them accordingly – may it be by SMS, WhatsApp, email or Chat. Actions are simplified, automated and personalised.
AI works to overcome the limitations of existing, antiquated database systems, through increasing automation and providing compliance management to its users. Furthermore, AI applications focus on productivity and efficiency; they determine the most effective communication method for each debtor, and use machine learning tools to predict and analyse customer behaviour (more on machine learning below). The overall impact is debt recovery and collection is streamlined as a process. The traditional process of debt collection via a human workforce can be incredibly labour intensive, and therefore expensive. Company's collection departments place calls, send emails manually, and manage accounts by updating databases by hand.
In 2020 it’s widely accepted that traditional call-centre led debt collection practices are inefficient and prone to human error. Those debtors you’re chasing often perceive that collectors are being intrusive and disrespectful. And likewise, many creditors feel that when they approach debtors via a telephone call, they’re left facing evasiveness and a lack of co-operation. So new practices have emerged. Ones which reduce debt collection costs for creditors, vastly increase customer satisfaction, and improve overall collection results. This new approach is based around multi-channel digital communications. The truth is digital multi-channel communications have a dramatic impact on collections success. They reduce the cost of all customer interactions whilst also enhancing the customer experience. It’s a win win. But what are the best communication channels to boost collections results?
Ditto is live in Pokémon GO. It marks an important occasion what we might call a struggling sensation: not only is the creature the last of the non-legendary original Pokémon to be introduced into the game, it's also the end of a long, complicated guessing game on the part of the Pokémonning public. Ditto is the first Pokémon added into the game since launch, and that, on its own, marks a major milestone and something to watch as the game prepares to release more creatures either in large groups or piecemeal. This is not the only new content we've gotten since launch. We've also had appraisals, the buddy system, catch-bonuses for medals and the regular series of tweaks to gyms and various other gameplay systems.
In the same way technology is changing the financial services industry, technology is also changing how the industry and supervisory authorities implement and enforce regulations. Today, an increasing number of supervisory authorities are turning to technology to support their work, leveraging so-called supervisory technology (suptech) applications to digitize report and regulatory processes. Suptech refers to the use of innovative technology such as artificial intelligence (AI) and machine learning (ML) by supervisory agencies to support supervision. As with other regtech solutions, suptech is about improving efficiency through the use of automation, streamlining administrative and operational procedures, and digitalizing data and working tools. The main goal here is to reduce the burden on firms and allow for more proactive monitoring, better reporting, oversight and overall compliance on the regulator's side.